From f0742f6f582c467ca3bb0d31fa1319046373af96 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 15 Nov 2024 15:03:04 +0100 Subject: [PATCH 01/31] removed fastqc, multiqc. Removed max_multiqc_email_size from schema. Added input=null for linting in the nextflow.config --- lib/WorkflowDrugresponseeval.groovy | 67 --- lib/WorkflowMain.groovy | 47 --- modules.json | 14 - modules/nf-core/fastqc/environment.yml | 5 - modules/nf-core/fastqc/tests/main.nf.test | 309 -------------- .../nf-core/fastqc/tests/main.nf.test.snap | 392 ------------------ modules/nf-core/fastqc/tests/tags.yml | 2 - modules/nf-core/multiqc/environment.yml | 5 - modules/nf-core/multiqc/tests/main.nf.test | 92 ---- .../nf-core/multiqc/tests/main.nf.test.snap | 41 -- modules/nf-core/multiqc/tests/nextflow.config | 5 - modules/nf-core/multiqc/tests/tags.yml | 2 - nextflow.config | 1 + nextflow_schema.json | 11 +- 14 files changed, 4 insertions(+), 989 deletions(-) delete mode 100755 lib/WorkflowDrugresponseeval.groovy delete mode 100755 lib/WorkflowMain.groovy delete mode 100644 modules/nf-core/fastqc/environment.yml delete mode 100644 modules/nf-core/fastqc/tests/main.nf.test delete mode 100644 modules/nf-core/fastqc/tests/main.nf.test.snap delete mode 100644 modules/nf-core/fastqc/tests/tags.yml delete mode 100644 modules/nf-core/multiqc/environment.yml delete mode 100644 modules/nf-core/multiqc/tests/main.nf.test delete mode 100644 modules/nf-core/multiqc/tests/main.nf.test.snap delete mode 100644 modules/nf-core/multiqc/tests/nextflow.config delete mode 100644 modules/nf-core/multiqc/tests/tags.yml diff --git a/lib/WorkflowDrugresponseeval.groovy b/lib/WorkflowDrugresponseeval.groovy deleted file mode 100755 index f1ccbb7..0000000 --- a/lib/WorkflowDrugresponseeval.groovy +++ /dev/null @@ -1,67 +0,0 @@ -// -// This file holds several functions specific to the workflow/drugresponseeval.nf in the nf-core/drugresponseeval pipeline -// - -import nextflow.Nextflow -import groovy.text.SimpleTemplateEngine - -class WorkflowDrugresponseeval { - - - public static void initialise(params, log) { - } - - public static String toolCitationText(params) { - - // TODO Optionally add in-text citation tools to this list. - // Can use ternary operators to dynamically construct based conditions, e.g. params["run_xyz"] ? "Tool (Foo et al. 2023)" : "", - // Uncomment function in methodsDescriptionText to render in MultiQC report - def citation_text = [ - "Tools used in the workflow included:", - "." - ].join(' ').trim() - - return citation_text - } - - public static String toolBibliographyText(params) { - - // TODO Optionally add bibliographic entries to this list. - // Can use ternary operators to dynamically construct based conditions, e.g. params["run_xyz"] ? "
  • Author (2023) Pub name, Journal, DOI
  • " : "", - // Uncomment function in methodsDescriptionText to render in MultiQC report - def reference_text = [ - "
  • Andrews S, (2010) FastQC, URL: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
  • ", - "
  • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. doi: /10.1093/bioinformatics/btw354
  • " - ].join(' ').trim() - - return reference_text - } - - public static String methodsDescriptionText(run_workflow, mqc_methods_yaml, params) { - // Convert to a named map so can be used as with familar NXF ${workflow} variable syntax in the MultiQC YML file - def meta = [:] - meta.workflow = run_workflow.toMap() - meta["manifest_map"] = run_workflow.manifest.toMap() - - // Pipeline DOI - meta["doi_text"] = meta.manifest_map.doi ? "(doi: ${meta.manifest_map.doi})" : "" - meta["nodoi_text"] = meta.manifest_map.doi ? "": "
  • If available, make sure to update the text to include the Zenodo DOI of version of the pipeline used.
  • " - - // Tool references - meta["tool_citations"] = "" - meta["tool_bibliography"] = "" - - // TODO Only uncomment below if logic in toolCitationText/toolBibliographyText has been filled! - //meta["tool_citations"] = toolCitationText(params).replaceAll(", \\.", ".").replaceAll("\\. \\.", ".").replaceAll(", \\.", ".") - //meta["tool_bibliography"] = toolBibliographyText(params) - - - def methods_text = mqc_methods_yaml.text - - def engine = new SimpleTemplateEngine() - def description_html = engine.createTemplate(methods_text).make(meta) - - return description_html - } - -} diff --git a/lib/WorkflowMain.groovy b/lib/WorkflowMain.groovy deleted file mode 100755 index b83d8f9..0000000 --- a/lib/WorkflowMain.groovy +++ /dev/null @@ -1,47 +0,0 @@ -// -// This file holds several functions specific to the main.nf workflow in the nf-core/drugresponseeval pipeline -// - -import nextflow.Nextflow - -class WorkflowMain { - - // - // Citation string for pipeline - // - public static String citation(workflow) { - return "If you use ${workflow.manifest.name} for your analysis please cite:\n\n" + - // TODO nf-core: Add Zenodo DOI for pipeline after first release - //"* The pipeline\n" + - //" https://doi.org/10.5281/zenodo.XXXXXXX\n\n" + - "* The nf-core framework\n" + - " https://doi.org/10.1038/s41587-020-0439-x\n\n" + - "* Software dependencies\n" + - " https://github.com/${workflow.manifest.name}/blob/master/CITATIONS.md" - } - - - // - // Validate parameters and print summary to screen - // - public static void initialise(workflow, params, log) { - - // Print workflow version and exit on --version - if (params.version) { - String workflow_version = NfcoreTemplate.version(workflow) - log.info "${workflow.manifest.name} ${workflow_version}" - System.exit(0) - } - - // Check that a -profile or Nextflow config has been provided to run the pipeline - NfcoreTemplate.checkConfigProvided(workflow, log) - - // Check that conda channels are set-up correctly - if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { - Utils.checkCondaChannels(log) - } - - // Check AWS batch settings - NfcoreTemplate.awsBatch(workflow, params) - } -} diff --git a/modules.json b/modules.json index 74a4465..62cedcb 100644 --- a/modules.json +++ b/modules.json @@ -3,20 +3,6 @@ "homePage": "https://github.com/nf-core/drugresponseeval", "repos": { "https://github.com/nf-core/modules.git": { - "modules": { - "nf-core": { - "fastqc": { - "branch": "master", - "git_sha": "666652151335353eef2fcd58880bcef5bc2928e1", - "installed_by": ["modules"] - }, - "multiqc": { - "branch": "master", - "git_sha": "b8d36829fa84b6e404364abff787e8b07f6d058c", - "installed_by": ["modules"] - } - } - }, "subworkflows": { "nf-core": { "utils_nextflow_pipeline": { diff --git a/modules/nf-core/fastqc/environment.yml b/modules/nf-core/fastqc/environment.yml deleted file mode 100644 index 691d4c7..0000000 --- a/modules/nf-core/fastqc/environment.yml +++ /dev/null @@ -1,5 +0,0 @@ -channels: - - conda-forge - - bioconda -dependencies: - - bioconda::fastqc=0.12.1 diff --git a/modules/nf-core/fastqc/tests/main.nf.test b/modules/nf-core/fastqc/tests/main.nf.test deleted file mode 100644 index e9d79a0..0000000 --- a/modules/nf-core/fastqc/tests/main.nf.test +++ /dev/null @@ -1,309 +0,0 @@ -nextflow_process { - - name "Test Process FASTQC" - script "../main.nf" - process "FASTQC" - - tag "modules" - tag "modules_nfcore" - tag "fastqc" - - test("sarscov2 single-end [fastq]") { - - when { - process { - """ - input[0] = Channel.of([ - [ id: 'test', single_end:true ], - [ file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true) ] - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - // NOTE The report contains the date inside it, which means that the md5sum is stable per day, but not longer than that. So you can't md5sum it. - // looks like this:
    Mon 2 Oct 2023
    test.gz
    - // https://github.com/nf-core/modules/pull/3903#issuecomment-1743620039 - { assert process.out.html[0][1] ==~ ".*/test_fastqc.html" }, - { assert process.out.zip[0][1] ==~ ".*/test_fastqc.zip" }, - { assert path(process.out.html[0][1]).text.contains("File typeConventional base calls") }, - { assert snapshot(process.out.versions).match() } - ) - } - } - - test("sarscov2 paired-end [fastq]") { - - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - [ file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_2.fastq.gz', checkIfExists: true) ] - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert process.out.html[0][1][0] ==~ ".*/test_1_fastqc.html" }, - { assert process.out.html[0][1][1] ==~ ".*/test_2_fastqc.html" }, - { assert process.out.zip[0][1][0] ==~ ".*/test_1_fastqc.zip" }, - { assert process.out.zip[0][1][1] ==~ ".*/test_2_fastqc.zip" }, - { assert path(process.out.html[0][1][0]).text.contains("File typeConventional base calls") }, - { assert path(process.out.html[0][1][1]).text.contains("File typeConventional base calls") }, - { assert snapshot(process.out.versions).match() } - ) - } - } - - test("sarscov2 interleaved [fastq]") { - - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_interleaved.fastq.gz', checkIfExists: true) - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert process.out.html[0][1] ==~ ".*/test_fastqc.html" }, - { assert process.out.zip[0][1] ==~ ".*/test_fastqc.zip" }, - { assert path(process.out.html[0][1]).text.contains("File typeConventional base calls") }, - { assert snapshot(process.out.versions).match() } - ) - } - } - - test("sarscov2 paired-end [bam]") { - - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/bam/test.paired_end.sorted.bam', checkIfExists: true) - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert process.out.html[0][1] ==~ ".*/test_fastqc.html" }, - { assert process.out.zip[0][1] ==~ ".*/test_fastqc.zip" }, - { assert path(process.out.html[0][1]).text.contains("File typeConventional base calls") }, - { assert snapshot(process.out.versions).match() } - ) - } - } - - test("sarscov2 multiple [fastq]") { - - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - [ file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_2.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test2_1.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test2_2.fastq.gz', checkIfExists: true) ] - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert process.out.html[0][1][0] ==~ ".*/test_1_fastqc.html" }, - { assert process.out.html[0][1][1] ==~ ".*/test_2_fastqc.html" }, - { assert process.out.html[0][1][2] ==~ ".*/test_3_fastqc.html" }, - { assert process.out.html[0][1][3] ==~ ".*/test_4_fastqc.html" }, - { assert process.out.zip[0][1][0] ==~ ".*/test_1_fastqc.zip" }, - { assert process.out.zip[0][1][1] ==~ ".*/test_2_fastqc.zip" }, - { assert process.out.zip[0][1][2] ==~ ".*/test_3_fastqc.zip" }, - { assert process.out.zip[0][1][3] ==~ ".*/test_4_fastqc.zip" }, - { assert path(process.out.html[0][1][0]).text.contains("File typeConventional base calls") }, - { assert path(process.out.html[0][1][1]).text.contains("File typeConventional base calls") }, - { assert path(process.out.html[0][1][2]).text.contains("File typeConventional base calls") }, - { assert path(process.out.html[0][1][3]).text.contains("File typeConventional base calls") }, - { assert snapshot(process.out.versions).match() } - ) - } - } - - test("sarscov2 custom_prefix") { - - when { - process { - """ - input[0] = Channel.of([ - [ id:'mysample', single_end:true ], // meta map - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true) - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert process.out.html[0][1] ==~ ".*/mysample_fastqc.html" }, - { assert process.out.zip[0][1] ==~ ".*/mysample_fastqc.zip" }, - { assert path(process.out.html[0][1]).text.contains("File typeConventional base calls") }, - { assert snapshot(process.out.versions).match() } - ) - } - } - - test("sarscov2 single-end [fastq] - stub") { - - options "-stub" - when { - process { - """ - input[0] = Channel.of([ - [ id: 'test', single_end:true ], - [ file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true) ] - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert snapshot(process.out).match() } - ) - } - } - - test("sarscov2 paired-end [fastq] - stub") { - - options "-stub" - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - [ file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_2.fastq.gz', checkIfExists: true) ] - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert snapshot(process.out).match() } - ) - } - } - - test("sarscov2 interleaved [fastq] - stub") { - - options "-stub" - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_interleaved.fastq.gz', checkIfExists: true) - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert snapshot(process.out).match() } - ) - } - } - - test("sarscov2 paired-end [bam] - stub") { - - options "-stub" - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/bam/test.paired_end.sorted.bam', checkIfExists: true) - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert snapshot(process.out).match() } - ) - } - } - - test("sarscov2 multiple [fastq] - stub") { - - options "-stub" - when { - process { - """ - input[0] = Channel.of([ - [id: 'test', single_end: false], // meta map - [ file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_2.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test2_1.fastq.gz', checkIfExists: true), - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test2_2.fastq.gz', checkIfExists: true) ] - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert snapshot(process.out).match() } - ) - } - } - - test("sarscov2 custom_prefix - stub") { - - options "-stub" - when { - process { - """ - input[0] = Channel.of([ - [ id:'mysample', single_end:true ], // meta map - file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastq/test_1.fastq.gz', checkIfExists: true) - ]) - """ - } - } - - then { - assertAll ( - { assert process.success }, - { assert snapshot(process.out).match() } - ) - } - } -} diff --git a/modules/nf-core/fastqc/tests/main.nf.test.snap b/modules/nf-core/fastqc/tests/main.nf.test.snap deleted file mode 100644 index d5db309..0000000 --- a/modules/nf-core/fastqc/tests/main.nf.test.snap +++ /dev/null @@ -1,392 +0,0 @@ -{ - "sarscov2 custom_prefix": { - "content": [ - [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:02:16.374038" - }, - "sarscov2 single-end [fastq] - stub": { - "content": [ - { - "0": [ - [ - { - "id": "test", - "single_end": true - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "1": [ - [ - { - "id": "test", - "single_end": true - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "2": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "html": [ - [ - { - "id": "test", - "single_end": true - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "versions": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "zip": [ - [ - { - "id": "test", - "single_end": true - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ] - } - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:02:24.993809" - }, - "sarscov2 custom_prefix - stub": { - "content": [ - { - "0": [ - [ - { - "id": "mysample", - "single_end": true - }, - "mysample.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "1": [ - [ - { - "id": "mysample", - "single_end": true - }, - "mysample.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "2": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "html": [ - [ - { - "id": "mysample", - "single_end": true - }, - "mysample.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "versions": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "zip": [ - [ - { - "id": "mysample", - "single_end": true - }, - "mysample.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ] - } - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:03:10.93942" - }, - "sarscov2 interleaved [fastq]": { - "content": [ - [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:01:42.355718" - }, - "sarscov2 paired-end [bam]": { - "content": [ - [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:01:53.276274" - }, - "sarscov2 multiple [fastq]": { - "content": [ - [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:02:05.527626" - }, - "sarscov2 paired-end [fastq]": { - "content": [ - [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:01:31.188871" - }, - "sarscov2 paired-end [fastq] - stub": { - "content": [ - { - "0": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "1": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "2": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "html": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "versions": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "zip": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ] - } - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:02:34.273566" - }, - "sarscov2 multiple [fastq] - stub": { - "content": [ - { - "0": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "1": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "2": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "html": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "versions": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "zip": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ] - } - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:03:02.304411" - }, - "sarscov2 single-end [fastq]": { - "content": [ - [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:01:19.095607" - }, - "sarscov2 interleaved [fastq] - stub": { - "content": [ - { - "0": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "1": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "2": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "html": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "versions": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "zip": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ] - } - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:02:44.640184" - }, - "sarscov2 paired-end [bam] - stub": { - "content": [ - { - "0": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "1": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "2": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "html": [ - [ - { - "id": "test", - "single_end": false - }, - "test.html:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ], - "versions": [ - "versions.yml:md5,e1cc25ca8af856014824abd842e93978" - ], - "zip": [ - [ - { - "id": "test", - "single_end": false - }, - "test.zip:md5,d41d8cd98f00b204e9800998ecf8427e" - ] - ] - } - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.3" - }, - "timestamp": "2024-07-22T11:02:53.550742" - } -} \ No newline at end of file diff --git a/modules/nf-core/fastqc/tests/tags.yml b/modules/nf-core/fastqc/tests/tags.yml deleted file mode 100644 index 7834294..0000000 --- a/modules/nf-core/fastqc/tests/tags.yml +++ /dev/null @@ -1,2 +0,0 @@ -fastqc: - - modules/nf-core/fastqc/** diff --git a/modules/nf-core/multiqc/environment.yml b/modules/nf-core/multiqc/environment.yml deleted file mode 100644 index 6f5b867..0000000 --- a/modules/nf-core/multiqc/environment.yml +++ /dev/null @@ -1,5 +0,0 @@ -channels: - - conda-forge - - bioconda -dependencies: - - bioconda::multiqc=1.25.1 diff --git a/modules/nf-core/multiqc/tests/main.nf.test b/modules/nf-core/multiqc/tests/main.nf.test deleted file mode 100644 index 33316a7..0000000 --- a/modules/nf-core/multiqc/tests/main.nf.test +++ /dev/null @@ -1,92 +0,0 @@ -nextflow_process { - - name "Test Process MULTIQC" - script "../main.nf" - process "MULTIQC" - - tag "modules" - tag "modules_nfcore" - tag "multiqc" - - config "./nextflow.config" - - test("sarscov2 single-end [fastqc]") { - - when { - process { - """ - input[0] = Channel.of(file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastqc/test_fastqc.zip', checkIfExists: true)) - input[1] = [] - input[2] = [] - input[3] = [] - input[4] = [] - input[5] = [] - """ - } - } - - then { - assertAll( - { assert process.success }, - { assert process.out.report[0] ==~ ".*/multiqc_report.html" }, - { assert process.out.data[0] ==~ ".*/multiqc_data" }, - { assert snapshot(process.out.versions).match("multiqc_versions_single") } - ) - } - - } - - test("sarscov2 single-end [fastqc] [config]") { - - when { - process { - """ - input[0] = Channel.of(file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastqc/test_fastqc.zip', checkIfExists: true)) - input[1] = Channel.of(file("https://github.com/nf-core/tools/raw/dev/nf_core/pipeline-template/assets/multiqc_config.yml", checkIfExists: true)) - input[2] = [] - input[3] = [] - input[4] = [] - input[5] = [] - """ - } - } - - then { - assertAll( - { assert process.success }, - { assert process.out.report[0] ==~ ".*/multiqc_report.html" }, - { assert process.out.data[0] ==~ ".*/multiqc_data" }, - { assert snapshot(process.out.versions).match("multiqc_versions_config") } - ) - } - } - - test("sarscov2 single-end [fastqc] - stub") { - - options "-stub" - - when { - process { - """ - input[0] = Channel.of(file(params.modules_testdata_base_path + 'genomics/sarscov2/illumina/fastqc/test_fastqc.zip', checkIfExists: true)) - input[1] = [] - input[2] = [] - input[3] = [] - input[4] = [] - input[5] = [] - """ - } - } - - then { - assertAll( - { assert process.success }, - { assert snapshot(process.out.report.collect { file(it).getName() } + - process.out.data.collect { file(it).getName() } + - process.out.plots.collect { file(it).getName() } + - process.out.versions ).match("multiqc_stub") } - ) - } - - } -} diff --git a/modules/nf-core/multiqc/tests/main.nf.test.snap b/modules/nf-core/multiqc/tests/main.nf.test.snap deleted file mode 100644 index 2fcbb5f..0000000 --- a/modules/nf-core/multiqc/tests/main.nf.test.snap +++ /dev/null @@ -1,41 +0,0 @@ -{ - "multiqc_versions_single": { - "content": [ - [ - "versions.yml:md5,41f391dcedce7f93ca188f3a3ffa0916" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.4" - }, - "timestamp": "2024-10-02T17:51:46.317523" - }, - "multiqc_stub": { - "content": [ - [ - "multiqc_report.html", - "multiqc_data", - "multiqc_plots", - "versions.yml:md5,41f391dcedce7f93ca188f3a3ffa0916" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.4" - }, - "timestamp": "2024-10-02T17:52:20.680978" - }, - "multiqc_versions_config": { - "content": [ - [ - "versions.yml:md5,41f391dcedce7f93ca188f3a3ffa0916" - ] - ], - "meta": { - "nf-test": "0.9.0", - "nextflow": "24.04.4" - }, - "timestamp": "2024-10-02T17:52:09.185842" - } -} \ No newline at end of file diff --git a/modules/nf-core/multiqc/tests/nextflow.config b/modules/nf-core/multiqc/tests/nextflow.config deleted file mode 100644 index c537a6a..0000000 --- a/modules/nf-core/multiqc/tests/nextflow.config +++ /dev/null @@ -1,5 +0,0 @@ -process { - withName: 'MULTIQC' { - ext.prefix = null - } -} diff --git a/modules/nf-core/multiqc/tests/tags.yml b/modules/nf-core/multiqc/tests/tags.yml deleted file mode 100644 index bea6c0d..0000000 --- a/modules/nf-core/multiqc/tests/tags.yml +++ /dev/null @@ -1,2 +0,0 @@ -multiqc: - - modules/nf-core/multiqc/** diff --git a/nextflow.config b/nextflow.config index 6a656f3..ffe8664 100644 --- a/nextflow.config +++ b/nextflow.config @@ -34,6 +34,7 @@ params { save_datasets = false // Boilerplate options + input = null outdir = 'results' publish_dir_mode = 'copy' email = null diff --git a/nextflow_schema.json b/nextflow_schema.json index ec54c1a..7d57ead 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -242,14 +242,6 @@ "fa_icon": "fas fa-remove-format", "hidden": true }, - "max_multiqc_email_size": { - "type": "string", - "description": "File size limit when attaching MultiQC reports to summary emails.", - "pattern": "^\\d+(\\.\\d+)?\\.?\\s*(K|M|G|T)?B$", - "default": "25.MB", - "fa_icon": "fas fa-file-upload", - "hidden": true - }, "monochrome_logs": { "type": "boolean", "description": "Do not use coloured log outputs.", @@ -293,6 +285,9 @@ { "$ref": "#/$defs/randomization_options" }, + { + "$ref": "#/$defs/data_options" + }, { "$ref": "#/$defs/robustness_options" }, From 246d54dbb8da1ae139e525c7a90b392ede1f38ee Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 15 Nov 2024 15:05:32 +0100 Subject: [PATCH 02/31] changed gitignore to include intellij .idea folder --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 5124c9a..d425acf 100644 --- a/.gitignore +++ b/.gitignore @@ -6,3 +6,4 @@ results/ testing/ testing* *.pyc +*.idea/ From eed2178c51726db69534ee364c9242ef65e21413 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 15 Nov 2024 16:07:44 +0100 Subject: [PATCH 03/31] fixed linting --- .gitignore | 2 +- .nf-core.yml | 22 ++++++- README.md | 19 ++---- .../nf-core-drugresponseeval_logo_light.png | Bin 91916 -> 90998 bytes conf/base.config | 2 - conf/test.config | 2 +- .../nf-core-drugresponseeval_logo_dark.png | Bin 25538 -> 25407 bytes docs/output.md | 43 +++++------- docs/usage.md | 61 ++++-------------- modules.json | 9 ++- nextflow_schema.json | 12 ++++ .../nf-core/utils_nextflow_pipeline/main.nf | 30 +++++---- .../tests/main.workflow.nf.test | 10 +-- .../nf-core/utils_nfcore_pipeline/main.nf | 10 +-- .../utils_nfschema_plugin/tests/main.nf.test | 4 +- 15 files changed, 100 insertions(+), 126 deletions(-) diff --git a/.gitignore b/.gitignore index d425acf..a42ce01 100644 --- a/.gitignore +++ b/.gitignore @@ -6,4 +6,4 @@ results/ testing/ testing* *.pyc -*.idea/ +null/ diff --git a/.nf-core.yml b/.nf-core.yml index 667b2a6..2a18a04 100644 --- a/.nf-core.yml +++ b/.nf-core.yml @@ -1,6 +1,19 @@ bump_version: null -lint: null -nf_core_version: 3.0.1 +lint: + files_exist: + - conf/igenomes.config + - conf/igenomes_ignored.config + - assets/multiqc_config.yml + - conf/igenomes.config + - conf/igenomes_ignored.config + - assets/multiqc_config.yml + files_unchanged: + - .github/CONTRIBUTING.md + - assets/sendmail_template.txt + - .github/CONTRIBUTING.md + - assets/sendmail_template.txt + multiqc_config: false +nf_core_version: 3.0.2 org_path: null repository_type: pipeline template: @@ -15,6 +28,9 @@ template: name: drugresponseeval org: nf-core outdir: . - skip_features: null + skip_features: + - igenomes + - multiqc + - fastqc version: 1.0dev update: null diff --git a/README.md b/README.md index 39e2b75..f03b199 100644 --- a/README.md +++ b/README.md @@ -36,16 +36,6 @@ DrEval catalog, you can increase your work's exposure, reusability, and transfer # ![DrEval_pipeline](assets/DrEval_pipeline_simplified.png) - - - - - 1. The response data is loaded 2. All models are trained and evaluated in a cross-validation setting 3. For each CV split, the best hyperparameters are determined using a grid search per model @@ -66,8 +56,6 @@ For baseline models, no randomization or robustness tests are performed. Now, you can run the pipeline using: - - ```bash nextflow run nf-core/drugresponseeval \ -profile \ @@ -95,10 +83,13 @@ Berlin). We thank the following people for their extensive assistance in the development of this pipeline: - - ## Contributions and Support +Contributors to nf-core/drugresponseeval and the drevalpy PyPI package: +- [Judith Bernett](https://github.com/JudithBernett) (TUM) +- [Pascal Iversen](https://github.com/PascalIversen) (FU Berlin) +- [Mario Picciani](https://github.com/picciama) (TUM) + If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md). 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and recognised by default in DSL2 files hosted on nf-core/modules. // If possible, it would be nice to keep the same label naming convention when // adding in your local modules too. - // TODO nf-core: Customise requirements for specific processes. // See https://www.nextflow.io/docs/latest/config.html#config-process-selectors withLabel:process_single { cpus = { 1 } diff --git a/conf/test.config b/conf/test.config index 1599590..2198b34 100644 --- a/conf/test.config +++ b/conf/test.config @@ -22,7 +22,7 @@ params { config_profile_name = 'Test profile' config_profile_description = 'Minimal test dataset to check pipeline function' - //TODO do this for the proper pipeline + // TODO nf-core: do this for the proper pipeline // Input data // TODO nf-core: Specify the paths to your test data on nf-core/test-datasets // TODO nf-core: Give any required params for the test so that command line flags are not needed diff --git a/docs/images/nf-core-drugresponseeval_logo_dark.png 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diff --git a/docs/output.md b/docs/output.md index 42d511c..a961714 100644 --- a/docs/output.md +++ b/docs/output.md @@ -12,38 +12,25 @@ The directories listed below will be created in the results directory after the The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data using the following steps: -- [FastQC](#fastqc) - Raw read QC -- [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline -- [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution +1. [Load response](#load-response) The response data is loaded +2. All models are trained and evaluated in a cross-validation setting +3. For each CV split, the best hyperparameters are determined using a grid search per model +4. The model is trained on the full training set (train & validation) with the best + hyperparameters to predict the test set +5. If randomization tests are enabled, the model is trained on the full training set with the best + hyperparameters to predict the randomized test set +6. If robustness tests are enabled, the model is trained N times on the full training set with the + best hyperparameters +7. Plots are created summarizing the results +8. [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution -### FastQC +### Load response +The response data is loaded into the pipeline. This step is necessary to provide the pipeline with the response data that will be used to train and evaluate the models. -
      -Output files - -- `fastqc/` - - `*_fastqc.html`: FastQC report containing quality metrics. - - `*_fastqc.zip`: Zip archive containing the FastQC report, tab-delimited data file and plot images. - -
      - -[FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) gives general quality metrics about your sequenced reads. It provides information about the quality score distribution across your reads, per base sequence content (%A/T/G/C), adapter contamination and overrepresented sequences. For further reading and documentation see the [FastQC help pages](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/). - -### MultiQC - -
      -Output files - -- `multiqc/` - - `multiqc_report.html`: a standalone HTML file that can be viewed in your web browser. - - `multiqc_data/`: directory containing parsed statistics from the different tools used in the pipeline. - - `multiqc_plots/`: directory containing static images from the report in various formats. - -
      +### Train and evaluate models -[MultiQC](http://multiqc.info) is a visualization tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in the report data directory. +All models are trained and evaluated in a cross-validation setting. The models are trained on the training set and evaluated on the validation set. The performance of the models is evaluated using various metrics such as accuracy, precision, recall, F1-score, and ROC-AUC. -Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see . ### Pipeline information diff --git a/docs/usage.md b/docs/usage.md index 7d69c7b..88cf27d 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -8,65 +8,26 @@ -## Samplesheet input - -You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. - -```bash ---input '[path to samplesheet file]' -``` - -### Multiple runs of the same sample - -The `sample` identifiers have to be the same when you have re-sequenced the same sample more than once e.g. to increase sequencing depth. The pipeline will concatenate the raw reads before performing any downstream analysis. Below is an example for the same sample sequenced across 3 lanes: - -```csv title="samplesheet.csv" -sample,fastq_1,fastq_2 -CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz -CONTROL_REP1,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz -CONTROL_REP1,AEG588A1_S1_L004_R1_001.fastq.gz,AEG588A1_S1_L004_R2_001.fastq.gz -``` - -### Full samplesheet - -The pipeline will auto-detect whether a sample is single- or paired-end using the information provided in the samplesheet. The samplesheet can have as many columns as you desire, however, there is a strict requirement for the first 3 columns to match those defined in the table below. - -A final samplesheet file consisting of both single- and paired-end data may look something like the one below. This is for 6 samples, where `TREATMENT_REP3` has been sequenced twice. - -```csv title="samplesheet.csv" -sample,fastq_1,fastq_2 -CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz -CONTROL_REP2,AEG588A2_S2_L002_R1_001.fastq.gz,AEG588A2_S2_L002_R2_001.fastq.gz -CONTROL_REP3,AEG588A3_S3_L002_R1_001.fastq.gz,AEG588A3_S3_L002_R2_001.fastq.gz -TREATMENT_REP1,AEG588A4_S4_L003_R1_001.fastq.gz, -TREATMENT_REP2,AEG588A5_S5_L003_R1_001.fastq.gz, -TREATMENT_REP3,AEG588A6_S6_L003_R1_001.fastq.gz, -TREATMENT_REP3,AEG588A6_S6_L004_R1_001.fastq.gz, -``` - -| Column | Description | -| --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `sample` | Custom sample name. This entry will be identical for multiple sequencing libraries/runs from the same sample. Spaces in sample names are automatically converted to underscores (`_`). | -| `fastq_1` | Full path to FastQ file for Illumina short reads 1. File has to be gzipped and have the extension ".fastq.gz" or ".fq.gz". | -| `fastq_2` | Full path to FastQ file for Illumina short reads 2. File has to be gzipped and have the extension ".fastq.gz" or ".fq.gz". | - -An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. - ## Running the pipeline The typical command for running the pipeline is as follows: ```bash -nextflow run nf-core/drugresponseeval --input ./samplesheet.csv --outdir ./results --genome GRCh37 -profile docker +nextflow run nf-core/drugresponseeval \ + -profile \ + --models \ + --baselines \ + --dataset_name \ + --path_data \ ``` -This will launch the pipeline with the `docker` configuration profile. See below for more information about profiles. +This will launch the pipeline with the `docker/singularity/.../institute` configuration profile. See below for more information about profiles. Note that the pipeline will create the following files in your working directory: ```bash work # Directory containing the nextflow working files - # Finished results in specified location (defined with --outdir) + # Finished results in specified location (defined with --outdir), defaults to 'results' .nextflow_log # Log file from Nextflow # Other nextflow hidden files, eg. history of pipeline runs and old logs. ``` @@ -88,9 +49,11 @@ nextflow run nf-core/drugresponseeval -profile docker -params-file params.yaml with: ```yaml title="params.yaml" -input: './samplesheet.csv' +models: 'ElasticNet' +baselines: 'NaivePredictor,NaiveCellLineMeanPredictor,NaiveDrugMeanPredictor' outdir: './results/' -genome: 'GRCh37' +dataset_name: 'GDSC2' +path_data: '/path/to/data' <...> ``` diff --git a/modules.json b/modules.json index 62cedcb..4566ec2 100644 --- a/modules.json +++ b/modules.json @@ -3,21 +3,24 @@ "homePage": "https://github.com/nf-core/drugresponseeval", "repos": { "https://github.com/nf-core/modules.git": { + "modules": { + "nf-core": {} + }, "subworkflows": { "nf-core": { "utils_nextflow_pipeline": { "branch": "master", - "git_sha": "9d05360da397692321d377b6102d2fb22507c6ef", + "git_sha": "56372688d8979092cafbe0c5c3895b491166ca1c", "installed_by": ["subworkflows"] }, "utils_nfcore_pipeline": { "branch": "master", - "git_sha": "772684d9d66f37b650c8ba5146ac1ee3ecba2acb", + "git_sha": "1b6b9a3338d011367137808b49b923515080e3ba", "installed_by": ["subworkflows"] }, "utils_nfschema_plugin": { "branch": "master", - "git_sha": "bbd5a41f4535a8defafe6080e00ea74c45f4f96c", + "git_sha": "2fd2cd6d0e7b273747f32e465fdc6bcc3ae0814e", "installed_by": ["subworkflows"] } } diff --git a/nextflow_schema.json b/nextflow_schema.json index 7d57ead..7804e2b 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -53,6 +53,18 @@ "fa_icon": "fas fa-envelope", "help_text": "Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file (`~/.nextflow/config`) then you don't need to specify this on the command line for every run.", "pattern": "^([a-zA-Z0-9_\\-\\.]+)@([a-zA-Z0-9_\\-\\.]+)\\.([a-zA-Z]{2,5})$" + }, + "input": { + "type": "string", + "format": "file-path", + "exists": true, + "schema": "assets/schema_input.json", + "mimetype": "text/csv", + "pattern": "^\\S+\\.csv$", + "description": "Unnecessary parameter for the pipeline, added to satisfy linting.", + "help_text": "Unnecessary parameter for the pipeline, added to satisfy linting.", + "fa_icon": "fas fa-file-csv", + "hidden": true } } }, diff --git a/subworkflows/nf-core/utils_nextflow_pipeline/main.nf b/subworkflows/nf-core/utils_nextflow_pipeline/main.nf index 2b0dc67..0fcbf7b 100644 --- a/subworkflows/nf-core/utils_nextflow_pipeline/main.nf +++ b/subworkflows/nf-core/utils_nextflow_pipeline/main.nf @@ -3,9 +3,9 @@ // /* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SUBWORKFLOW DEFINITION -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ workflow UTILS_NEXTFLOW_PIPELINE { @@ -44,9 +44,9 @@ workflow UTILS_NEXTFLOW_PIPELINE { } /* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FUNCTIONS -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ // @@ -106,17 +106,19 @@ def checkCondaChannels() { def channels_missing = ((required_channels_in_order as Set) - (channels as Set)) as Boolean // Check that they are in the right order - def channel_priority_violation = false - - required_channels_in_order.eachWithIndex { channel, index -> - if (index < required_channels_in_order.size() - 1) { - channel_priority_violation |= !(channels.indexOf(channel) < channels.indexOf(required_channels_in_order[index + 1])) - } - } + def channel_priority_violation = required_channels_in_order != channels.findAll { ch -> ch in required_channels_in_order } if (channels_missing | channel_priority_violation) { - log.warn( - "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n" + " There is a problem with your Conda configuration!\n\n" + " You will need to set-up the conda-forge and bioconda channels correctly.\n" + " Please refer to https://bioconda.github.io/\n" + " The observed channel order is \n" + " ${channels}\n" + " but the following channel order is required:\n" + " ${required_channels_in_order}\n" + "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" - ) + log.warn """\ + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + There is a problem with your Conda configuration! + You will need to set-up the conda-forge and bioconda channels correctly. + Please refer to https://bioconda.github.io/ + The observed channel order is + ${channels} + but the following channel order is required: + ${required_channels_in_order} + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" + """.stripIndent(true) } } diff --git a/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test b/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test index ca964ce..02dbf09 100644 --- a/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test +++ b/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test @@ -52,10 +52,12 @@ nextflow_workflow { } then { - assertAll( - { assert workflow.success }, - { assert workflow.stdout.contains("nextflow_workflow v9.9.9") } - ) + expect { + with(workflow) { + assert success + assert "nextflow_workflow v9.9.9" in stdout + } + } } } diff --git a/subworkflows/nf-core/utils_nfcore_pipeline/main.nf b/subworkflows/nf-core/utils_nfcore_pipeline/main.nf index b78273c..5cb7baf 100644 --- a/subworkflows/nf-core/utils_nfcore_pipeline/main.nf +++ b/subworkflows/nf-core/utils_nfcore_pipeline/main.nf @@ -3,9 +3,9 @@ // /* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SUBWORKFLOW DEFINITION -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ workflow UTILS_NFCORE_PIPELINE { @@ -21,9 +21,9 @@ workflow UTILS_NFCORE_PIPELINE { } /* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FUNCTIONS -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ // @@ -62,7 +62,7 @@ def checkProfileProvided(nextflow_cli_args) { def workflowCitation() { def temp_doi_ref = "" def manifest_doi = workflow.manifest.doi.tokenize(",") - // Using a loop to handle multiple DOIs + // Handling multiple DOIs // Removing `https://doi.org/` to handle pipelines using DOIs vs DOI resolvers // Removing ` ` since the manifest.doi is a string and not a proper list manifest_doi.each { doi_ref -> diff --git a/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test b/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test index 842dc43..8fb3016 100644 --- a/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test +++ b/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test @@ -42,7 +42,7 @@ nextflow_workflow { params { test_data = '' - outdir = 1 + outdir = null } workflow { @@ -94,7 +94,7 @@ nextflow_workflow { params { test_data = '' - outdir = 1 + outdir = null } workflow { From 7e02d4496a458e8fa56e8c735275f0ed31e7b133 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 15 Nov 2024 16:09:12 +0100 Subject: [PATCH 04/31] fixed pre-commit --- README.md | 1 + docs/output.md | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index f03b199..c230cd7 100644 --- a/README.md +++ b/README.md @@ -86,6 +86,7 @@ We thank the following people for their extensive assistance in the development ## Contributions and Support Contributors to nf-core/drugresponseeval and the drevalpy PyPI package: + - [Judith Bernett](https://github.com/JudithBernett) (TUM) - [Pascal Iversen](https://github.com/PascalIversen) (FU Berlin) - [Mario Picciani](https://github.com/picciama) (TUM) diff --git a/docs/output.md b/docs/output.md index a961714..66baf6a 100644 --- a/docs/output.md +++ b/docs/output.md @@ -25,13 +25,13 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d 8. [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution ### Load response + The response data is loaded into the pipeline. This step is necessary to provide the pipeline with the response data that will be used to train and evaluate the models. ### Train and evaluate models All models are trained and evaluated in a cross-validation setting. The models are trained on the training set and evaluated on the validation set. The performance of the models is evaluated using various metrics such as accuracy, precision, recall, F1-score, and ROC-AUC. - ### Pipeline information
      From a6acf5336c76d979ce53a0f07eca30bd0fea9434 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 15 Nov 2024 16:28:14 +0100 Subject: [PATCH 05/31] trying to get the new logos --- .gitignore | 1 + assets/nf-core-drugresponseeval_logo_light.png | Bin 90998 -> 0 bytes .../nf-core-drugresponseeval_logo_dark.png | Bin 25407 -> 0 bytes .../nf-core-drugresponseeval_logo_light.png | Bin 21349 -> 0 bytes 4 files changed, 1 insertion(+) delete mode 100644 assets/nf-core-drugresponseeval_logo_light.png delete mode 100644 docs/images/nf-core-drugresponseeval_logo_dark.png delete mode 100644 docs/images/nf-core-drugresponseeval_logo_light.png diff --git a/.gitignore b/.gitignore index a42ce01..14290da 100644 --- a/.gitignore +++ b/.gitignore @@ -7,3 +7,4 @@ testing/ testing* *.pyc null/ +.idea/ diff --git a/assets/nf-core-drugresponseeval_logo_light.png b/assets/nf-core-drugresponseeval_logo_light.png deleted file mode 100644 index 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This step is necessary to provide All models are trained and evaluated in a cross-validation setting. The models are trained on the training set and evaluated on the validation set. The performance of the models is evaluated using various metrics such as accuracy, precision, recall, F1-score, and ROC-AUC. +### Determine best hyperparameters + +### Train model on full training set + +### Randomization tests + +### Robustness tests + +### Create plots + ### Pipeline information
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It compares it against existing deep learning models and baseline models. Additionally, it tests the model for overfitting, consistency, robustness, and - generalization. " + generalization. force: false is_nfcore: true name: drugresponseeval From a981ca7c4daf035bcac4fb0018877bb351d7635a Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 15 Nov 2024 17:43:58 +0100 Subject: [PATCH 14/31] it didn't update? --- .nf-core.yml | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/.nf-core.yml b/.nf-core.yml index bc4c4fd..a06ac73 100644 --- a/.nf-core.yml +++ b/.nf-core.yml @@ -18,11 +18,7 @@ org_path: null repository_type: pipeline template: author: Judith Bernett - description: This pipeline takes a drug response prediction model architecture - as input and evaluates its performance by using custom training, validation, and - test sets. It compares it against existing deep learning models and baseline models. - Additionally, it tests the model for overfitting, consistency, robustness, and - generalization. + description: This pipeline evaluates drug response models in various settings on a variety of datasets. force: false is_nfcore: true name: drugresponseeval From d18dfc58cceb005bb27ef2caab0ff23c6b69fe78 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 18 Nov 2024 10:21:23 +0100 Subject: [PATCH 15/31] fixed -profile test but still need to put the requirements on docker and the dataset on nf-core/test-datasets --- conf/base.config | 6 +++--- conf/modules.config | 12 ++++++------ conf/test.config | 9 +++++---- conf/test_full.config | 3 +++ modules/local/load_response/main.nf | 2 +- modules/local/params_check/main.nf | 3 ++- modules/local/predict_full/main.nf | 2 +- modules/local/train_and_predict_cv/main.nf | 2 +- nextflow.config | 6 +++--- subworkflows/local/model_testing/main.nf | 7 ++++--- subworkflows/local/run_cv/main.nf | 5 +++-- workflows/drugresponseeval.nf | 9 ++++++--- 12 files changed, 38 insertions(+), 28 deletions(-) diff --git a/conf/base.config b/conf/base.config index 933ff63..87dc864 100644 --- a/conf/base.config +++ b/conf/base.config @@ -40,9 +40,9 @@ process { time = { 8.h * task.attempt } } withLabel:process_high { - cpus = { check_max( 18 * task.attempt, 'cpus' ) } - memory = { check_max( 72.GB * task.attempt, 'memory' ) } - time = { check_max( 16.h * task.attempt, 'time' ) } + cpus = { 12 * task.attempt } + memory = { 72.GB * task.attempt } + time = { 16.h * task.attempt } } withLabel:process_long { time = { 20.h * task.attempt } diff --git a/conf/modules.config b/conf/modules.config index c2b986f..13057f3 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -20,7 +20,7 @@ process { withName: 'LOAD_RESPONSE' { publishDir = [ - path: { params.save_datasets ? "${params.outdir}/${params.run_id}/datasets" : params.outdir }, + path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, mode: params.publish_dir_mode, saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } ] @@ -28,7 +28,7 @@ process { withName: 'CV_SPLIT' { publishDir = [ - path: { params.save_datasets ? "${params.outdir}/${params.run_id}/datasets" : params.outdir }, + path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, mode: params.publish_dir_mode, saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } ] @@ -52,7 +52,7 @@ process { withName: 'HPAM_SPLIT' { publishDir = [ - path: { params.save_datasets ? "${params.outdir}/${params.run_id}/hpams" : params.outdir }, + path: { params.save_datasets ? "${params.path_data}/${params.run_id}/hpams" : params.path_data }, mode: params.publish_dir_mode, saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } ] @@ -61,7 +61,7 @@ process { withName: 'TRAIN_AND_PREDICT_CV' { publishDir = [ - path: { params.save_datasets ? "${params.outdir}/${params.run_id}/datasets" : params.outdir }, + path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, mode: params.publish_dir_mode, saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } ] @@ -107,7 +107,7 @@ process { withName: 'EVALUATE_FIND_MAX' { publishDir = [ - path: { params.save_datasets ? "${params.outdir}/${params.run_id}/datasets" : params.outdir }, + path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, mode: params.publish_dir_mode, saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } ] @@ -115,7 +115,7 @@ process { withName: 'RANDOMIZATION_SPLIT' { publishDir = [ - path: { params.save_datasets ? "${params.outdir}/${params.run_id}/datasets" : params.outdir }, + path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, mode: params.publish_dir_mode, saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } ] diff --git a/conf/test.config b/conf/test.config index 2198b34..7fa6d8e 100644 --- a/conf/test.config +++ b/conf/test.config @@ -13,7 +13,7 @@ process { resourceLimits = [ cpus: 4, - memory: '15.GB', + memory: '3.GB', time: '1.h' ] } @@ -22,12 +22,13 @@ params { config_profile_name = 'Test profile' config_profile_description = 'Minimal test dataset to check pipeline function' - // TODO nf-core: do this for the proper pipeline // Input data // TODO nf-core: Specify the paths to your test data on nf-core/test-datasets // TODO nf-core: Give any required params for the test so that command line flags are not needed //input = params.pipelines_testdata_base_path + 'viralrecon/samplesheet/samplesheet_test_illumina_amplicon.csv' - // Genome references - //genome = 'R64-1-1' + run_id = 'test_run' + dataset_name = 'Toy_Data' + n_cv_splits = 2 + } diff --git a/conf/test_full.config b/conf/test_full.config index 278c654..e19d5f8 100644 --- a/conf/test_full.config +++ b/conf/test_full.config @@ -22,4 +22,7 @@ params { // Genome references //genome = 'R64-1-1' + run_id = 'test_run' + dataset_name = 'Toy_Data' + n_cv_splits = 5 } diff --git a/modules/local/load_response/main.nf b/modules/local/load_response/main.nf index 3221d63..69790b9 100644 --- a/modules/local/load_response/main.nf +++ b/modules/local/load_response/main.nf @@ -9,7 +9,7 @@ process LOAD_RESPONSE { // 'biocontainers/python:3.8.3' }" input: val dataset_name - val path_data + path path_data val cross_study_datasets output: diff --git a/modules/local/params_check/main.nf b/modules/local/params_check/main.nf index 4eb69c1..ecc6e63 100755 --- a/modules/local/params_check/main.nf +++ b/modules/local/params_check/main.nf @@ -21,9 +21,10 @@ process PARAMS_CHECK { val optim_metric val n_cv_splits val response_transformation + val path_data output: - + path path_data, emit: path_data when: task.ext.when == null || task.ext.when diff --git a/modules/local/predict_full/main.nf b/modules/local/predict_full/main.nf index 53fa12a..9d9b513 100644 --- a/modules/local/predict_full/main.nf +++ b/modules/local/predict_full/main.nf @@ -11,7 +11,7 @@ process PREDICT_FULL { input: tuple path(cross_study_datasets), val(model_name), val(test_mode), val(split_id), path(split_dataset), path(hpam_combi) val(response_transformation) - val(path_data) + path(path_data) output: tuple val(test_mode), val(model_name), path('**predictions*.csv'), emit: ch_vis diff --git a/modules/local/train_and_predict_cv/main.nf b/modules/local/train_and_predict_cv/main.nf index 6ba2682..28d3cae 100644 --- a/modules/local/train_and_predict_cv/main.nf +++ b/modules/local/train_and_predict_cv/main.nf @@ -5,7 +5,7 @@ process TRAIN_AND_PREDICT_CV { input: tuple val(model_name), val(test_mode), path(cv_data), path(hyperparameters) - val path_data + path path_data val response_transformation output: diff --git a/nextflow.config b/nextflow.config index ffe8664..54fc92a 100644 --- a/nextflow.config +++ b/nextflow.config @@ -18,19 +18,19 @@ params { // For this pipeline run_id = 'my_run' - models = 'SimpleNeuralNetwork' + models = 'NaiveDrugMeanPredictor' baselines = 'NaivePredictor' test_mode = 'LPO' randomization_mode = 'None' randomization_type = 'permutation' n_trials_robustness = 0 - dataset_name = 'GDSC1' + dataset_name = 'GDSC2' cross_study_datasets = '' curve_curator = false optim_metric = 'RMSE' n_cv_splits = 10 response_transformation = 'None' - path_data = 'data/' + path_data = './data' save_datasets = false // Boilerplate options diff --git a/subworkflows/local/model_testing/main.nf b/subworkflows/local/model_testing/main.nf index 5617454..6f88958 100644 --- a/subworkflows/local/model_testing/main.nf +++ b/subworkflows/local/model_testing/main.nf @@ -14,6 +14,7 @@ workflow MODEL_TESTING { randomizations // from input cross_study_datasets // from LOAD_RESPONSE ch_models // from RUN_CV + path_data // from input main: if (params.cross_study_datasets == '') { @@ -30,7 +31,7 @@ workflow MODEL_TESTING { PREDICT_FULL ( ch_predict_final, params.response_transformation, - params.path_data + path_data ) ch_vis = PREDICT_FULL.out.ch_vis @@ -59,7 +60,7 @@ workflow MODEL_TESTING { RANDOMIZATION_TEST ( ch_randomization, - params.path_data, + path_data, params.randomization_type, params.response_transformation ) @@ -82,7 +83,7 @@ workflow MODEL_TESTING { ch_robustness = ch_best_hpams_per_split_rob.combine(ch_trials_robustness, by: 0) ROBUSTNESS_TEST ( ch_robustness, - params.path_data, + path_data, params.randomization_type, params.response_transformation ) diff --git a/subworkflows/local/run_cv/main.nf b/subworkflows/local/run_cv/main.nf index ca2d47b..ec84980 100644 --- a/subworkflows/local/run_cv/main.nf +++ b/subworkflows/local/run_cv/main.nf @@ -11,9 +11,10 @@ workflow RUN_CV { test_modes // LPO,LDO,LCO models // model names for full testing baselines // model names for comparison + path_data // path to data main: - LOAD_RESPONSE(params.dataset_name, params.path_data, params.cross_study_datasets) + LOAD_RESPONSE(params.dataset_name, path_data, params.cross_study_datasets) ch_test_modes = channel.from(test_modes) ch_data = ch_test_modes.combine(LOAD_RESPONSE.out.response_dataset) @@ -73,7 +74,7 @@ workflow RUN_CV { TRAIN_AND_PREDICT_CV ( ch_test_combis, - params.path_data, + path_data, params.response_transformation ) // [model_name, test_mode, split_id, diff --git a/workflows/drugresponseeval.nf b/workflows/drugresponseeval.nf index 84c0149..3c89a36 100644 --- a/workflows/drugresponseeval.nf +++ b/workflows/drugresponseeval.nf @@ -60,13 +60,15 @@ workflow DRUGRESPONSEEVAL { params.curve_curator, params.optim_metric, params.n_cv_splits, - params.response_transformation + params.response_transformation, + params.path_data ) RUN_CV ( test_modes, models, - baselines + baselines, + PARAMS_CHECK.out.path_data ) MODEL_TESTING ( @@ -74,7 +76,8 @@ workflow DRUGRESPONSEEVAL { RUN_CV.out.best_hpam_per_split, randomizations, RUN_CV.out.cross_study_datasets, - RUN_CV.out.ch_models + RUN_CV.out.ch_models, + PARAMS_CHECK.out.path_data ) VISUALIZATION ( From 6ea8f84c2127474c768b44af8373bae3e36ffdc3 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Thu, 21 Nov 2024 14:23:14 +0100 Subject: [PATCH 16/31] added container with latest drevalpy version --- nextflow.config | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/nextflow.config b/nextflow.config index 54fc92a..4117454 100644 --- a/nextflow.config +++ b/nextflow.config @@ -6,13 +6,7 @@ ---------------------------------------------------------------------------------------- */ -// Wave containers -// Docker: Comment in for ARM64 build: -// process.container = 'community.wave.seqera.io/library/pip_drevalpy:23d68e736486ab16' -// Docker: Comment in for AMD64 build: -// process.container = 'community.wave.seqera.io/library/pip_drevalpy:7d8f30cda5f4887b' -// Singularity: Comment in for AMD64 build: -// process.container = 'oras://community.wave.seqera.io/library/pip_drevalpy:6ca244fae0c2fa29' +process.container = 'ghcr.io/daisybio/drevalpy:main' // Global default params, used in configs params { From f43dbbc71ac94e07b395fd9aa020e945004f784a Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 22 Nov 2024 10:11:05 +0100 Subject: [PATCH 17/31] added conda support --- env.yml | 9 +++++++++ nextflow.config | 1 + 2 files changed, 10 insertions(+) create mode 100644 env.yml diff --git a/env.yml b/env.yml new file mode 100644 index 0000000..33d431f --- /dev/null +++ b/env.yml @@ -0,0 +1,9 @@ +name: nf-core-drugresponseeval +channels: + - conda-forge + - defaults +dependencies: + - ray-tune + - pip + - pip: + - drevalpy==1.0.10 diff --git a/nextflow.config b/nextflow.config index 4117454..1b47b13 100644 --- a/nextflow.config +++ b/nextflow.config @@ -7,6 +7,7 @@ */ process.container = 'ghcr.io/daisybio/drevalpy:main' +process.conda = 'env.yml' // Global default params, used in configs params { From a3ea0d63134d0ec5a38678d27bd7ffd1c136c0ff Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 22 Nov 2024 12:09:43 +0100 Subject: [PATCH 18/31] Proper usage documentation --- docs/usage.md | 120 ++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 116 insertions(+), 4 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index 88cf27d..53dc9a8 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -6,7 +6,38 @@ ## Introduction - +DrugResponseEval is a workflow designed to ensure that drug response prediction models are evaluated in a consistent and +reproducible manner. We offer three settings: + +- **Leave-Pair-Out (LPO)**: Random pairs of cell lines and drugs are left out for testing but both the drug and the + cell line might already be present in the training set. This is the **easiest setting** for your model but also the + most uninformative one. The only application scenario for this setting is when you want to test whether your model + can **complete the missing values in the training set**. +- **Leave-Cell-Line-Out (LCO)**: Random cell lines are left out for testing but the drugs might already be present in + the training set. This setting is **more challenging** than LPO but still relatively easy. The application scenario + for this setting is when you want to test whether your model can **predict the response of a new cell line**. This + is very relevant for **personalized medicine or drug repurposing**. +- **Leave-Drug-Out (LDO)**: Random drugs are left out for testing but the cell lines might already be present in the + training set. This setting is the **most challenging** one. The application scenario for this setting is when you + want to test whether your model can **predict the response of a new drug**. This is very relevant for **drug + development**. + +An underlying issue is that drugs have a rather unique IC50 range. That means that by just predicting the mean IC50 +that a drug has in the training set (aggregated over all cell lines), you can already achieve a rather good +prediction. This is why we also offer the possibility to compare your model to a **NaivePredictor** that predicts +the mean IC50 of all drugs in the training set. We also offer two more advanced naive predictors: +**NaiveCellLineMeanPredictor** and **NaiveDrugMeanPredictor**. The former predicts the mean IC50 of a cell line in +the training set and the latter predicts the mean IC50 of a drug in the training set. + +Furthermore, we offer a variety of more advanced **baseline models** and some **state-of-the-art models** to compare +your model against. Similarly, we provide commonly used datasets to evaluate your model on (GDSC1, GDSC2, CCLE, +CTRPv2). You can also provide your **own dataset or your own model by contributing to our PyPI package +[drevalpy](https://github.com/daisybio/drevalpy.git)** Before contributing, you can pull our respective repositories. +More information will be supplied soon. + +We first identify the best hyperparameters for all models and baselines in a cross-validation setting. Then, we +train the models on the whole training set and evaluate them on the test set. Furthermore, we offer randomization +and robustness tests. ## Running the pipeline @@ -15,14 +46,28 @@ The typical command for running the pipeline is as follows: ```bash nextflow run nf-core/drugresponseeval \ -profile \ + --run_id myRun \ + --test_mode \ --models \ --baselines \ --dataset_name \ - --path_data \ + --path_data ``` This will launch the pipeline with the `docker/singularity/.../institute` configuration profile. See below for more information about profiles. +In your `outdir`, a folder named `myRun` will be created containing the results of the pipeline run. + +The `test_mode` parameter specifies the evaluation setting, e.g., `--test_mode LCO`. + +The `models` and `baselines` parameters are lists of models and baselines to be evaluated, e.g., +`--models ElasticNet,RandomForest --baselines NaivePredictor,NaiveCellLineMeanPredictor,NaiveDrugMeanPredictor`. + +The `dataset_name` parameter specifies the dataset to be used for evaluation, e.g., `--dataset_name GDSC2`. + +If you do not want to re-download the data every time you run the pipeline, you can specify the path to the data with +the `path_data` parameter, e.g., `--path_data /path/to/data`. + Note that the pipeline will create the following files in your working directory: ```bash @@ -32,7 +77,8 @@ work # Directory containing the nextflow working files # Other nextflow hidden files, eg. history of pipeline runs and old logs. ``` -If you wish to repeatedly use the same parameters for multiple runs, rather than specifying each flag in the command, you can specify these in a params file. +If you wish to repeatedly use the same parameters for multiple runs, rather than specifying each flag in the command, +you can specify these in a params file. Pipeline settings can be provided in a `yaml` or `json` file via `-params-file `. @@ -51,7 +97,6 @@ with: ```yaml title="params.yaml" models: 'ElasticNet' baselines: 'NaivePredictor,NaiveCellLineMeanPredictor,NaiveDrugMeanPredictor' -outdir: './results/' dataset_name: 'GDSC2' path_data: '/path/to/data' <...> @@ -59,6 +104,73 @@ path_data: '/path/to/data' You can also generate such `YAML`/`JSON` files via [nf-core/launch](https://nf-co.re/launch). +### Available Models + +**Single-Drug Models** fit one model for each drug in the training set. They also cannot generalize to new drugs, +hence those models cannot be used in the LDO setting. **Multi-Drug Models** fit one model for all drugs in the training +set. They can be used in all three settings. + +The following models are available: + +| Model Name | Baseline / Published Model | Multi-Drug Model / Single-Drug Model | Description | +| -------------------------- | -------------------------- | ------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| NaivePredictor | Baseline Method | Multi-Drug Model | Most simple method. Predicts the mean response of all drugs in the training set. | +| NaiveCellLineMeanPredictor | Baseline Method | Multi-Drug Model | Predicts the mean response of a cell line in the training set. | +| NaiveDrugMeanPredictor | Baseline Method | Multi-Drug Model | Predicts the mean response of a drug in the training set. | +| ElasticNet | Baseline Method | Multi-Drug Model | Fits an [Sklearn Elastic Net](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html), [Lasso](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html), or [Ridge](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html) model on gene expression data and drug fingerprints (concatenated input matrix). | +| GradientBoosting | Baseline Method | Multi-Drug Model | Fits an [Sklearn Gradient Boosting Regressor](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html) gene expression data and drug fingerprints. | +| RandomForest | Baseline Method | Multi-Drug Model | Fits an [Sklearn Random Forest Regressor](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html) on gene expression data and drug fingerprints. | +| MultiOmicsRandomForest | Baseline Method | Multi-Drug Model | Fits an [Sklearn Random Forest Regressor](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html) on gene expression, methylation, mutation, copy number variation data, and drug fingerprints (concatenated matrix). The dimensionality of the methylation data is reduced with a PCA to the first 100 components before it is fed to the model. | +| SingleDrugRandomForest | Baseline Method | Single-Drug Model | Fits an [Sklearn Random Forest Regressor](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html) on gene expression data for each drug separately. | +| SVR | Baseline Method | Multi-Drug Model | Fits an [Sklearn Support Vector Regressor](https://scikit-learn.org/1.5/modules/generated/sklearn.svm.SVR.html) gene expression data and drug fingerprints. | +| SimpleNeuralNetwork | Baseline Method | Multi-Drug Model | Fits a simple feedforward neural network (implemented with [Pytorch Lightning](https://lightning.ai/docs/pytorch/stable/)) on gene expression and drug fingerprints (concatenated input) with 3 layers of varying dimensions and Dropout layers. | +| MultiOmicsNeuralNetwork | Baseline Method | Multi-Drug Model | Fits a simple feedforward neural network (implemented with [Pytorch Lightning](https://lightning.ai/docs/pytorch/stable/)) on gene expression, methylation, mutation, copy number variation data, and drug fingerprints (concatenated input) with 3 layers of varying dimensions and Dropout layers. The dimensionality of the methylation data is reduced with a PCA to the first 100 components before it is fed to the model. | +| SRMF | Published Model | Multi-Drug Model | [Similarity Regularization Matrix Factorization](https://doi.org/10.1186/s12885-017-3500-5) model by Wang et al. on gene expression data and drug fingerprints. Re-implemented Matlab code into Python. The basic idea is represent each drug and each cell line by their respective similarities to all other drugs/cell lines. Those similarities are mapped into a shared latent low-dimensional space from which responses are predicted. | +| MOLIR | Published Model | Single-Drug Model | Regression extension of [MOLI: multi-omics late integration deep neural network.](https://doi.org/10.1093/bioinformatics/btz318) by Sharifi-Noghabi et al. Takes somatic mutation, copy number variation and gene expression data as input. MOLI reduces the dimensionality of each omics type with a hidden layer, concatenates them into one representation and optimizes this representation via a combined cost function consisting of a triplet loss and a binary cross-entropy loss. We implemented a regression adaption with MSE loss and an adapted triplet loss for regression. | +| SuperFELTR | Published Model | Single-Drug Model | Regression extension of [SuperFELT: supervised feature extraction learning using triplet loss for drug response](https:://doi.org/10.1186/s12859-021-04146-z) by Park et al. Very similar to MOLI(R). In MOLI(R), encoders and the classifier were trained jointly. Super.FELT(R) trains them independently. MOLI(R) was trained without feature selection (except for the Variance Threshold on the gene expression). Super.FELT(R) uses feature selection for all omics data. | +| DIPK | Published Model | Multi-Drug Model | [Deep neural network Integrating Prior Knowledge](https://doi.org/10.1093/bib/bbae153) from Li et al. Uses gene interaction relationships (encoded by a graph auto-encoder), gene expression profiles (encoded by a denoising auto-encoder), and molecular topologies (encoded by MolGNet). Those features are integrated using multi-head attention layers. | + +### Available Datasets + +The following datasets are available and can be supplied via `--dataset_name`: + +| Dataset Name | Number of drugs | Number of Cell Lines | Description | +| ------------ | --------------- | -------------------- | -------------------------------------------------------------------------------------------------------------------- | +| GDSC1 | 345 | 987 | The Genomics of Drug Sensitivity in Cancer (GDSC) dataset version 1. | +| GDSC2 | 192 | 809 | The Genomics of Drug Sensitivity in Cancer (GDSC) dataset version 2. | +| CCLE | 18 | 471 | The Cancer Cell Line Encyclopedia (CCLE) dataset. The response data will soon be replaced with the data from CTRPv2. | + +Our pipeline also supports cross-study prediction, i.e., training on one dataset and testing on another (or multiple +others) to assess the generalization of the model. This dataset name can be supplied via `--cross_study_datasets`. + +### Available Randomization Tests + +We have several randomization modes and types available. + +The modes are supplied via `--randomization_mode` and the types via `--randomization_type`.: + +- **SVCC: Single View Constant for Cell Lines:** A single cell line view (e.g., gene expression) is held unperturbed + while the others are randomized. +- **SVCD: Single View Constant for Drugs:** A single drug view (e.g., drug fingerprints) is held unperturbed while the + others are randomized. +- **SVRC: Single View Random for Cell Lines:** A single cell line view (e.g., gene expression) is randomized while the + others are held unperturbed. +- **SVRD: Single View Random for Drugs:** A single drug view (e.g., drug fingerprints) is randomized while the others + are held unperturbed. + +Currently, we support two ways of randomizing the data. The default is permututation. + +- **Permutation**: Permutes the features over the instances, keeping the distribution of the features the same but + dissolving the relationship to the target. +- **Invariant**: The randomization is done in a way that a key characteristic of the feature is preserved. In case + of matrices, this is the mean and standard deviation of the feature view for this instance, for networks it is the + degree distribution. + +### Robustness Tests + +The robustness test is a test where the model is trained with varying seeds. This is done multiple times to see how +stable the model is. Via `--n_trials_robustness`, you can specify the number of trials for the robustness tests. + ### Updating the pipeline When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline: From f0f9417be3d6da54828aa5ba907cc76b90bd99d8 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 22 Nov 2024 17:54:52 +0100 Subject: [PATCH 19/31] Proper output documentation, removed unnecessary statements in the module files --- conf/modules.config | 49 +-- docs/output.md | 313 ++++++++++++++++-- docs/usage.md | 2 +- modules/local/collect_results/main.nf | 6 - modules/local/cv_split/main.nf | 4 - modules/local/draw_corr_comp/main.nf | 5 - .../local/draw_critical_difference/main.nf | 5 - modules/local/draw_heatmap/main.nf | 5 - modules/local/draw_regression/main.nf | 5 - modules/local/draw_violin/main.nf | 5 - modules/local/evaluate_final/main.nf | 6 - modules/local/evaluate_find_max/main.nf | 4 - modules/local/hpam_split/main.nf | 4 - modules/local/load_response/main.nf | 6 +- modules/local/make_model_channel/main.nf | 6 +- modules/local/params_check/main.nf | 6 - modules/local/predict_full/main.nf | 4 - modules/local/randomization_split/main.nf | 4 - modules/local/randomization_test/main.nf | 4 - modules/local/robustness_test/main.nf | 4 - modules/local/save_tables/main.nf | 5 - modules/local/write_html/main.nf | 5 - modules/local/write_index/main.nf | 6 - 23 files changed, 319 insertions(+), 144 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index 13057f3..5dba3ba 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -52,29 +52,38 @@ process { withName: 'HPAM_SPLIT' { publishDir = [ - path: { params.save_datasets ? "${params.path_data}/${params.run_id}/hpams" : params.path_data }, + path: params.outdir, mode: params.publish_dir_mode, - saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } + saveAs: { filename -> null } ] } withName: 'TRAIN_AND_PREDICT_CV' { publishDir = [ - path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, + path: params.outdir, mode: params.publish_dir_mode, - saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } + saveAs: { filename -> null } ] ext.use_gpu = { [ 'SimpleNeuralNetwork', 'MultiOmicsNeuralNetwork', 'MOLIR', - 'SuperFELTR' + 'SuperFELTR', + 'DIPK' ].contains( model_name.split( '\\.' )[0] ) } } + withName: 'EVALUATE_FIND_MAX' { + publishDir = [ + path: params.outdir, + mode: params.publish_dir_mode, + saveAs: { filename -> null } + ] + } + withName: 'PREDICT_FULL' { ext.use_gpu = { [ 'SimpleNeuralNetwork', @@ -85,12 +94,21 @@ process { } } + withName: 'RANDOMIZATION_SPLIT' { + publishDir = [ + path: params.outdir, + mode: params.publish_dir_mode, + saveAs: { filename -> null } + ] + } + withName: 'RANDOMIZATION_TEST' { ext.use_gpu = { [ 'SimpleNeuralNetwork', 'MultiOmicsNeuralNetwork', 'MOLIR', - 'SuperFELTR' + 'SuperFELTR', + 'DIPK' ].contains( model_name.split( '\\.' )[0] ) } } @@ -100,27 +118,12 @@ process { 'SimpleNeuralNetwork', 'MultiOmicsNeuralNetwork', 'MOLIR', - 'SuperFELTR' + 'SuperFELTR', + 'DIPK' ].contains( model_name.split( '\\.' )[0] ) } } - withName: 'EVALUATE_FIND_MAX' { - publishDir = [ - path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, - mode: params.publish_dir_mode, - saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } - ] - } - - withName: 'RANDOMIZATION_SPLIT' { - publishDir = [ - path: { params.save_datasets ? "${params.path_data}/${params.run_id}/datasets" : params.path_data }, - mode: params.publish_dir_mode, - saveAs: { filename -> (filename != 'versions.yml' && params.save_datasets) ? filename : null } - ] - } - withName: 'EVALUATE_FINAL' { publishDir = [ path: params.outdir, diff --git a/docs/output.md b/docs/output.md index f086882..b0c6b9e 100644 --- a/docs/output.md +++ b/docs/output.md @@ -2,45 +2,312 @@ ## Introduction -This document describes the output produced by the pipeline. Most of the plots are taken from the MultiQC report, which summarises results at the end of the pipeline. +This document describes the output produced by the pipeline. -The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory. - - +The directories listed below will be created in the results directory after the pipeline has finished. +All paths are relative to the top-level results directory. ## Pipeline overview The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data using the following steps: -1. [Load response](#load-response) The response data is loaded -2. All models are trained and evaluated in a cross-validation setting -3. For each CV split, the best hyperparameters are determined using a grid search per model -4. The model is trained on the full training set (train & validation) with the best - hyperparameters to predict the test set -5. If randomization tests are enabled, the model is trained on the full training set with the best - hyperparameters to predict the randomized test set -6. If robustness tests are enabled, the model is trained N times on the full training set with the - best hyperparameters -7. Plots are created summarizing the results -8. [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution +1. [Parameter check](#parameter-check): Several parameters are validated to ensure that the pipeline can run + successfully. +2. `RUN_CV` subworkflow: Finds the optimal hyperparameters for each model in a cross-validation setting. + - [Load response](#load-response): The response data is loaded. + - [CV split](#cv-split): The response data is split into cross-validation folds. + - [Make model channel](#make-model-channel): From the input baseline and model names, channels are created. This + step is necessary because for the Single-Drug Models, one model has to be created per drug. + - [HPAM split](#hyperparameter-split): One YAML file is created per model and hyperparameter combination to be + tested. + - [Train and predict CV](#train-and-predict-cv): All models are trained and evaluated in a cross-validation setting. + - [Evaluate and find max](#evaluate-and-find-max): For each CV split, the best hyperparameters are determined + using a grid search per model +3. `MODEL_TESTING` subworkflow: The best hyperparameters are used to train the models on the full training set + and predict the test set. Optionally, randomization and robustness testes are performed. + - [Predict full](#predict-full): The model is trained on the full training set (train & validation) with the best + hyperparameters to predict the test set. + - [Randomization split](#randomization-split): Makes a channel per randomization to be tested. + - [Randomization test](#randomization-test): If randomization tests are enabled, the model is trained on the full + training set with the best hyperparameters to predict the randomized test set. + - [Robustness test](#robustness-test): If robustness tests are enabled, the model is trained N times on the full + training set with the best hyperparameters + - [Consolidate results](#consolidate-results): The results of the model testing are consolidated into a single + table for each model. + - [Evaluate final](#evaluate-final): The performance of the models is calculated on the test set results. + - [Collect results](#collect-results): The results of the evaluation metrics per model are collected into four + overview tables. +4. `VISUALIZATION` subworkflow: Plots are created summarizing the results. + - [Critical difference plot](#critical-difference): A critical difference plot is created to compare the performance + of the models. + - [Violin plot](#violin-plot): A violin plot is created to compare the performance of the models over the CV folds. + - [Heatmap](#heatmap): A heatmap is created to compare the average performance of the models over the CV folds. + - [Correlation comparison](#correlation-comparison): Renders a plot in which the per-drug/per-cell line + correlations between y_true and y_predicted are compared between different models. + - [Regression plots](#regression-plots): Plots in which the y_true and y_predicted values are compared between + different models. + - [Save tables](#save-tables): Saves the performance metrics of the models in a table. + - [Write html](#write-html): Writes the plots to an HTML file per setting (LPO/LCO/LDO). + - [Write index](#write-index): Writes an index.html file that links to all the HTML files. +5. [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution + +### Parameter check + +The process `PARAMS_CHECK` performs the following checks: + +- `--models` / `--baselines`: Check if the model and baseline names are valid (for valid names, see the [usage](usage.md) page). +- `--test_mode`: Check whether the test mode is LPO, LCO, LDO or a combination of these. +- `--dataset_name`: Check if the dataset name is valid, i.e., GDSC1, GDSC2, or CCLE. +- `--cross_study_datasets`: If supplied, check if the datasets are valid, i.e., GDSC1, GDSC2, or CCLE or a + combination of these. +- `--n_cv_splits`: Check if the number of cross-validation splits is a positive integer > 1. +- `--randomization_mode`: If supplied, checks if the randomization is SVCC, SVCD, SVRC, SVRD, or a combination of these. +- `--randomization_type`: If supplied, checks if the randomization type is valid, i.e., permutation or invariant. +- `--n_trials_robustness`: Checks if the number of trials for robustness tests is >= 0. +- `--optim_metric`: Checks if the optimization metric is either MSE, RMSE, MAE, R^2, Pearson, Spearman, Kendall, or + Partial_Correlation. +- `--response_transformation`: If supplied, checks whether the response transformation is either standard, + minmax, or robust. + +It emits the path to the data but mostly so that the other processes wait for `PARAMS_CHECK` to finish before starting. -### Load response +### Subworkflow `RUN_CV` + +#### Load response The response data is loaded into the pipeline. This step is necessary to provide the pipeline with the response data that will be used to train and evaluate the models. -### Train and evaluate models +
        +Optional output files if --save_datasets is set + +- `response_dataset.pkl`: The response data is saved as a pickle file. +- `cross_study_*.pkl`: The response data for the cross-study datasets is saved as a pickle file. + +
        + +#### CV split + +The response data is split into as many cross-validation folds as specified over the `--n_cv_splits` parameter. +The data is split into training, validation, and test sets for each fold. For models using early stopping, the early +stopping dataset is split from the validation set. This ensures that all models are trained and evaluated on the +same dataset. + +
        +Optional output file if --save_datasets is set + +- `split*.pkl`: The response data belonging to each fold is saved as a pickle file. + +
        + +#### Make model channel + +From the input baseline and model names, channels are created. This step is necessary because for the +Single-Drug Models, one model has to be created per drug. The model name then becomes the name of the model and the +drug, separated by a dot, e.g., `MOLIR.Drug1`. All of these models should be able to be trained in parallel +which is why they should be individual elements in the channel. + +#### Hyperparameter split + +One YAML file is created per model and hyperparameter combination to be tested. This ensures that all hyperparameter +can be tested in parallel. + +#### Train and predict CV + +A model is trained in the specified test mode, on the specific cross-validation split with the specified +hyperparameter combination. + +As soon as the GPU support is available, the training and prediction will be done on the GPU for the models +SimpleNeuralNetwork, MultiOmicsNeuralNetwork, MOLIR, SuperFELTR, and DIPK. + +#### Evaluate and find max + +Over all hyperparameter combinations, the best hyperparameters for a specific cross-validation split are determined. +The best hyperparameters are determined based on the optimization metric specified via `--optim_metric`. + +### Subworkflow `MODEL_TESTING` + +### Predict full + +The model is trained on the full training set (train & validation) per split with the best hyperparameters to predict +the test set of the CV split. If specified via `--cross_study_datasets`, the cross-study datasets are also +predicted. + +
        +Output files + +- `**predictions*.csv`: CSV file with the predicted response values for the test set. +- `**cross_study/cross_study*.csv`: CSV file with the predicted response values for the cross-study datasets. +- `**best_hpams*.json`: JSON file with the best hyperparameters for the model. + +
        + +#### Randomization split + +Takes the `--randomization_mode` as input and creates a channel for each randomization to be tested. This ensures that +all randomizations can be tested in parallel. + +#### Randomization test + +Trains the model on the randomized training + validation set with the best hyperparameters to predict the +unperturbed test set of the specified CV split. How the data is randomized is determined by the +`--randomization_type`. + +As soon as GPU support is available, the training and prediction will be done on the GPU for +the models SimpleNeuralNetwork, MultiOmicsNeuralNetwork, MOLIR, SuperFELTR, and DIPK. + +
        +Output files + +- `**randomization*.csv`: CSV file with the predicted response values for the randomization test. + +
        + +#### Robustness test + +Trains the model `--n_trials_robustness` times on the full training set with the best hyperparameters to predict the test set of the +specific CV split. + +As soon as GPU support is available, the training and prediction will be done on the GPU for the models +SimpleNeuralNetwork, MultiOmicsNeuralNetwork, MOLIR, SuperFELTR, and DIPK. + +
        +Output files + +- `**robustness*.csv`: CSV file with the predicted response values for the robustness test. + +
        + +#### Consolidate results + +For Single-Drug Models, the results of the model testing are consolidated such that their results look like the +results of the Multi-Drug Models. + +
        +Output files + +- `**predictions*.csv`: CSV file with the consolidated predicted response values for the test set. +- `**cross_study/cross_study*.csv`: CSV file with the consolidated predicted response values for the cross-study + datasets. +- `**randomization*.csv`: CSV file with the consolidated predicted response values for the randomization test. +- `**robustness*.csv`: CSV file with the consolidated predicted response values for the robustness test. + +
        + +#### Evaluate final + +Calculates various performance metrics on the given test set results, including RMSE, MSE, MAE, R^2, Pearson +Correlation, Spearman Correlation, Kendall Correlation, and Partial Correlation. + +#### Collect results -All models are trained and evaluated in a cross-validation setting. The models are trained on the training set and evaluated on the validation set. The performance of the models is evaluated using various metrics such as accuracy, precision, recall, F1-score, and ROC-AUC. +Collapses the results from above into four overview tables: `evaluation_results.csv`, `evaluation_results_per_drug. +csv`, `evaluation_results_per_cell_line.csv`, and `true_vs_pred.csv`. -### Determine best hyperparameters +
        +Output files + +- `evaluation_results.csv`: Overall performance metrics. One value per model per CV fold and setting (LPO/LCO/LDO, + full predictions, randomizations, robustness, cross-study predictions). +- `evaluation_results_per_drug.csv`: Performance metrics calculated per drug. +- `evaluation_results_per_cell_line.csv`: Performance metrics calculated per cell line. +- `true_vs_pred.csv`: true vs predicted values for each model. + +
        + +### Subworkflow `VISUALIZATION` + +#### Critical difference + +The critical difference plot measures whether a model is significantly better than another model measured over its +average rank over all CV folds. + +
        +Output files + +- `critical_difference*.svg`: SVG file with the critical difference plot. + +
        + +#### Violin plot + +The violin shows the distribution of the performance metrics over the CV folds. This plot is rendered overall for +all real predictions and once per algorithm to compare the real predictions against, e.g., the randomization results. + +
        +Output files + +- `violin*.html`: HTML file with the violin plot. + +
        + +#### Heatmap + +The heatmap shows the average performance of the models over the CV folds. This plot is rendered overall for all +real predictions and once per algorithm to compare the real predictions against, e.g., the randomization results. + +
        +Output files + +- `heatmap*.html`: HTML file with the violin plot. + +
        + +#### Correlation comparison + +Renders a plot in which the per-drug/per-cell line correlations between y_true and y_predicted are compared between +different models. + +
        +Output files -### Train model on full training set +- `corr_comp_scatter*.html`: HTML file with the violin plot. -### Randomization tests +
        -### Robustness tests +#### Regression plots -### Create plots +Plots in which the y_true and y_predicted values are compared between different models. + +
        +Output files + +- `regression_lines*.html`: HTML file with the violin plot. + +
        + +#### Save tables + +Saves the performance metrics of the models in an html table. + +
        +Output files + +- `table*.html`: HTML file with the violin plot. + +
        + +#### Write html + +Creates a summary HTML file per setting (LPO/LCO/LDO) that contains all the plots and tables. + +
        +Output files + +- `{LPO,LCO,LPO}.html`: HTML file with the violin plot. + +
        + +#### Write index + +Writes an index.html file that links to all the HTML files. + +
        +Output files + +- `index.html`: HTML file with the violin plot. +- `*.png`: Some png files for the logo, etc. + +
        ### Pipeline information diff --git a/docs/usage.md b/docs/usage.md index 53dc9a8..6d84a78 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -33,7 +33,7 @@ Furthermore, we offer a variety of more advanced **baseline models** and some ** your model against. Similarly, we provide commonly used datasets to evaluate your model on (GDSC1, GDSC2, CCLE, CTRPv2). You can also provide your **own dataset or your own model by contributing to our PyPI package [drevalpy](https://github.com/daisybio/drevalpy.git)** Before contributing, you can pull our respective repositories. -More information will be supplied soon. +More information can be found in the [drevalpy readthedocs](https://drevalpy.readthedocs.io/en/latest/). We first identify the best hyperparameters for all models and baselines in a cross-validation setting. Then, we train the models on the whole training set and evaluate them on the test set. Furthermore, we offer randomization diff --git a/modules/local/collect_results/main.nf b/modules/local/collect_results/main.nf index 86e3d88..e426caf 100644 --- a/modules/local/collect_results/main.nf +++ b/modules/local/collect_results/main.nf @@ -1,13 +1,7 @@ process COLLECT_RESULTS { - //tag "${test_mode}_${model_name}_${pred_file}" label 'process_single' publishDir "${params.outdir}/${params.run_id}", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: path(outfiles) diff --git a/modules/local/cv_split/main.nf b/modules/local/cv_split/main.nf index cc58dec..74b36d9 100644 --- a/modules/local/cv_split/main.nf +++ b/modules/local/cv_split/main.nf @@ -2,10 +2,6 @@ process CV_SPLIT { tag "$test_mode" label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple val(test_mode), path(response) val n_cv_splits diff --git a/modules/local/draw_corr_comp/main.nf b/modules/local/draw_corr_comp/main.nf index 2361525..c0487f8 100644 --- a/modules/local/draw_corr_comp/main.nf +++ b/modules/local/draw_corr_comp/main.nf @@ -3,11 +3,6 @@ process DRAW_CORR_COMP { label 'process_single' publishDir "${params.outdir}/${params.run_id}/corr_comp_scatter", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: tuple val(name), path(eval_results_per_group) diff --git a/modules/local/draw_critical_difference/main.nf b/modules/local/draw_critical_difference/main.nf index f8945aa..e06c486 100644 --- a/modules/local/draw_critical_difference/main.nf +++ b/modules/local/draw_critical_difference/main.nf @@ -3,11 +3,6 @@ process DRAW_CRITICAL_DIFFERENCE { label 'process_single' publishDir "${params.outdir}/${params.run_id}/critical_difference_plots", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: tuple val(lpo_lco_ldo), path(eval_results) diff --git a/modules/local/draw_heatmap/main.nf b/modules/local/draw_heatmap/main.nf index a5cde8f..673562c 100644 --- a/modules/local/draw_heatmap/main.nf +++ b/modules/local/draw_heatmap/main.nf @@ -3,11 +3,6 @@ process DRAW_HEATMAP { label 'process_single' publishDir "${params.outdir}/${params.run_id}/heatmaps", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: val(name) path(eval_results) diff --git a/modules/local/draw_regression/main.nf b/modules/local/draw_regression/main.nf index 83ccb61..d75e683 100644 --- a/modules/local/draw_regression/main.nf +++ b/modules/local/draw_regression/main.nf @@ -3,11 +3,6 @@ process DRAW_REGRESSION { label 'process_single' publishDir "${params.outdir}/${params.run_id}/regression_plots", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: tuple val(name), val(model), path(true_vs_pred) diff --git a/modules/local/draw_violin/main.nf b/modules/local/draw_violin/main.nf index 2c5aa00..e9c71a3 100644 --- a/modules/local/draw_violin/main.nf +++ b/modules/local/draw_violin/main.nf @@ -3,11 +3,6 @@ process DRAW_VIOLIN { label 'process_single' publishDir "${params.outdir}/${params.run_id}/violin_plots", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: val(name) path(eval_results) diff --git a/modules/local/evaluate_final/main.nf b/modules/local/evaluate_final/main.nf index b439ea0..aa252f8 100644 --- a/modules/local/evaluate_final/main.nf +++ b/modules/local/evaluate_final/main.nf @@ -1,12 +1,6 @@ process EVALUATE_FINAL { tag "${test_mode}_${model_name}_${pred_file}" label 'process_single' - //publishDir "${params.outdir}/${params.run_id}" - - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple val(test_mode), val(model_name), path(pred_file) diff --git a/modules/local/evaluate_find_max/main.nf b/modules/local/evaluate_find_max/main.nf index 34acca5..c2637a3 100644 --- a/modules/local/evaluate_find_max/main.nf +++ b/modules/local/evaluate_find_max/main.nf @@ -2,10 +2,6 @@ process EVALUATE_FIND_MAX { tag "${test_mode}_${model_name}_${split_id}" label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple val(model_name), val(test_mode), val(split_id), path(hpam_yamls), path(pred_datas) val metric diff --git a/modules/local/hpam_split/main.nf b/modules/local/hpam_split/main.nf index 70dc028..78d0002 100644 --- a/modules/local/hpam_split/main.nf +++ b/modules/local/hpam_split/main.nf @@ -2,10 +2,6 @@ process HPAM_SPLIT { tag "$model_name" label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: val model_name diff --git a/modules/local/load_response/main.nf b/modules/local/load_response/main.nf index 69790b9..6063252 100644 --- a/modules/local/load_response/main.nf +++ b/modules/local/load_response/main.nf @@ -1,12 +1,8 @@ process LOAD_RESPONSE { tag "${dataset_name} (cross: ${cross_study_datasets})" - //label 'process_single' + label 'process_single' publishDir "${path_data}", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: val dataset_name path path_data diff --git a/modules/local/make_model_channel/main.nf b/modules/local/make_model_channel/main.nf index aa8cf87..a9373aa 100644 --- a/modules/local/make_model_channel/main.nf +++ b/modules/local/make_model_channel/main.nf @@ -1,11 +1,7 @@ process MAKE_MODEL_CHANNEL { tag "Make model channel" - //label 'process_single' + label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple val(models), path(response_data) val(name) diff --git a/modules/local/params_check/main.nf b/modules/local/params_check/main.nf index ecc6e63..7970b4d 100755 --- a/modules/local/params_check/main.nf +++ b/modules/local/params_check/main.nf @@ -1,12 +1,6 @@ process PARAMS_CHECK { - //tag "$samplesheet" label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: val run_id val models diff --git a/modules/local/predict_full/main.nf b/modules/local/predict_full/main.nf index 9d9b513..965fd11 100644 --- a/modules/local/predict_full/main.nf +++ b/modules/local/predict_full/main.nf @@ -4,10 +4,6 @@ process PREDICT_FULL { label 'process_gpu' publishDir "${params.outdir}/${params.run_id}/${test_mode}", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple path(cross_study_datasets), val(model_name), val(test_mode), val(split_id), path(split_dataset), path(hpam_combi) val(response_transformation) diff --git a/modules/local/randomization_split/main.nf b/modules/local/randomization_split/main.nf index a71c426..2a8ec1d 100644 --- a/modules/local/randomization_split/main.nf +++ b/modules/local/randomization_split/main.nf @@ -2,10 +2,6 @@ process RANDOMIZATION_SPLIT { tag "${model_name}_${randomization_mode}" label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple val(model_name), val(randomization_mode) diff --git a/modules/local/randomization_test/main.nf b/modules/local/randomization_test/main.nf index 7632fba..c9041ff 100644 --- a/modules/local/randomization_test/main.nf +++ b/modules/local/randomization_test/main.nf @@ -4,10 +4,6 @@ process RANDOMIZATION_TEST { label 'process_gpu' publishDir "${params.outdir}/${params.run_id}/${test_mode}", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple val(model_name), val(test_mode), val(split_id), path(split_dataset), path(best_hpams), path(randomization_views) path(path_data) diff --git a/modules/local/robustness_test/main.nf b/modules/local/robustness_test/main.nf index 7d40573..4f54593 100644 --- a/modules/local/robustness_test/main.nf +++ b/modules/local/robustness_test/main.nf @@ -4,10 +4,6 @@ process ROBUSTNESS_TEST { label 'process_gpu' publishDir "${params.outdir}/${params.run_id}/${test_mode}", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" input: tuple val(model_name), val(test_mode), val(split_id), path(split_dataset), path(best_hpams), val(robustness_iteration) path(path_data) diff --git a/modules/local/save_tables/main.nf b/modules/local/save_tables/main.nf index a42eef5..eec8ef4 100644 --- a/modules/local/save_tables/main.nf +++ b/modules/local/save_tables/main.nf @@ -3,11 +3,6 @@ process SAVE_TABLES { label 'process_single' publishDir "${params.outdir}/${params.run_id}/html_tables", mode: 'copy' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: tuple val(lpo_lco_ldo), path(eval_results) diff --git a/modules/local/write_html/main.nf b/modules/local/write_html/main.nf index 06076f2..c9e703d 100644 --- a/modules/local/write_html/main.nf +++ b/modules/local/write_html/main.nf @@ -2,11 +2,6 @@ process WRITE_HTML { tag "${test_mode}" label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: val(run_id) tuple val(test_mode), path(files) diff --git a/modules/local/write_index/main.nf b/modules/local/write_index/main.nf index 88b2d76..a5551e8 100644 --- a/modules/local/write_index/main.nf +++ b/modules/local/write_index/main.nf @@ -1,12 +1,6 @@ process WRITE_INDEX { - //tag "index" label 'process_single' - //conda "conda-forge::python=3.8.3" - //container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - // 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - // 'biocontainers/python:3.8.3' }" - input: val(run_id) val(test_modes) From 9839312de41c84de66dfc8a8d2121ed0d291d3b0 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 22 Nov 2024 18:01:30 +0100 Subject: [PATCH 20/31] change log for the pull request --- CHANGELOG.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 16ceb7c..0e50810 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -9,8 +9,16 @@ Initial release of nf-core/drugresponseeval, created with the [nf-core](https:// ### `Added` +- Updated to the new template +- Added tests that run with docker, singularity, apptainer, and conda +- Added the docker container and the conda env.yml in the nextflow.config. We just need one container for all + processes as this pipeline automates the PyPI package drevalpy. +- Added usage and output documentation. + ### `Fixed` +- Fixed linting issues + ### `Dependencies` ### `Deprecated` From e01cbdcfe1555bd7c0dd4ebdee7f69518a141c28 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Fri, 22 Nov 2024 18:17:52 +0100 Subject: [PATCH 21/31] added citations for implemented and adapted drug response prediction models --- CITATIONS.md | 24 ++++++++++++++++++++---- docs/usage.md | 2 +- 2 files changed, 21 insertions(+), 5 deletions(-) diff --git a/CITATIONS.md b/CITATIONS.md index 8dd7848..95debcc 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -1,5 +1,9 @@ # nf-core/drugresponseeval: Citations +## [DrugResponseEval](https://github.com/nf-core/drugresponseeval/) + +> Bernett, J, Iversen, P, Picciani, M, Wilhelm, M, Baum, K, List, M. Will be published soon. + ## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/) > Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031. @@ -10,13 +14,25 @@ ## Pipeline tools -- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) +- [DrEvalPy](https://github.com/daisybio/drevalpy) + + > Bernett, J, Iversen, P, Picciani, M, Wilhelm, M, Baum, K, List, M. Will be published soon. + +- [SRMF](https://doi.org/10.1186/s12885-017-3500-5) + + > Wang L, Li X, Zhang L, Gao Q. Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization. BMC cancer. 2017 Dec;17:1-2. + +- [MOLI](https://doi.org/10.1093/bioinformatics/btz318) + + > Sharifi-Noghabi H, Zolotareva O, Collins CC, Ester M. MOLI: multi-omics late integration with deep neural networks for drug response prediction. Bioinformatics. 2019 Jul;35(14):i501-9. + +- [SuperFELT](https://doi.org/10.1186/s12859-021-04146-z) -> Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. + > Park S, Soh J, Lee H. Super. FELT: supervised feature extraction learning using triplet loss for drug response prediction with multi-omics data. BMC bioinformatics. 2021 May 25;22(1):269. -- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/) +- [DIPK](https://doi.org/10.1093/bib/bbae153) -> Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924. + > Li P, Jiang Z, Liu T, Liu X, Qiao H, Yao X. Improving drug response prediction via integrating gene relationships with deep learning. Briefings in Bioinformatics. 2024 May;25(3):bbae153. ## Software packaging/containerisation tools diff --git a/docs/usage.md b/docs/usage.md index 6d84a78..556df55 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -127,7 +127,7 @@ The following models are available: | MultiOmicsNeuralNetwork | Baseline Method | Multi-Drug Model | Fits a simple feedforward neural network (implemented with [Pytorch Lightning](https://lightning.ai/docs/pytorch/stable/)) on gene expression, methylation, mutation, copy number variation data, and drug fingerprints (concatenated input) with 3 layers of varying dimensions and Dropout layers. The dimensionality of the methylation data is reduced with a PCA to the first 100 components before it is fed to the model. | | SRMF | Published Model | Multi-Drug Model | [Similarity Regularization Matrix Factorization](https://doi.org/10.1186/s12885-017-3500-5) model by Wang et al. on gene expression data and drug fingerprints. Re-implemented Matlab code into Python. The basic idea is represent each drug and each cell line by their respective similarities to all other drugs/cell lines. Those similarities are mapped into a shared latent low-dimensional space from which responses are predicted. | | MOLIR | Published Model | Single-Drug Model | Regression extension of [MOLI: multi-omics late integration deep neural network.](https://doi.org/10.1093/bioinformatics/btz318) by Sharifi-Noghabi et al. Takes somatic mutation, copy number variation and gene expression data as input. MOLI reduces the dimensionality of each omics type with a hidden layer, concatenates them into one representation and optimizes this representation via a combined cost function consisting of a triplet loss and a binary cross-entropy loss. We implemented a regression adaption with MSE loss and an adapted triplet loss for regression. | -| SuperFELTR | Published Model | Single-Drug Model | Regression extension of [SuperFELT: supervised feature extraction learning using triplet loss for drug response](https:://doi.org/10.1186/s12859-021-04146-z) by Park et al. Very similar to MOLI(R). In MOLI(R), encoders and the classifier were trained jointly. Super.FELT(R) trains them independently. MOLI(R) was trained without feature selection (except for the Variance Threshold on the gene expression). Super.FELT(R) uses feature selection for all omics data. | +| SuperFELTR | Published Model | Single-Drug Model | Regression extension of [SuperFELT: supervised feature extraction learning using triplet loss for drug response](https://doi.org/10.1186/s12859-021-04146-z) by Park et al. Very similar to MOLI(R). In MOLI(R), encoders and the classifier were trained jointly. Super.FELT(R) trains them independently. MOLI(R) was trained without feature selection (except for the Variance Threshold on the gene expression). Super.FELT(R) uses feature selection for all omics data. | | DIPK | Published Model | Multi-Drug Model | [Deep neural network Integrating Prior Knowledge](https://doi.org/10.1093/bib/bbae153) from Li et al. Uses gene interaction relationships (encoded by a graph auto-encoder), gene expression profiles (encoded by a denoising auto-encoder), and molecular topologies (encoded by MolGNet). Those features are integrated using multi-head attention layers. | ### Available Datasets From 268ba9597728d4afb55f40b1705a95e9ac97b241 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 09:32:34 +0100 Subject: [PATCH 22/31] trying to fix version comment --- .../workflows/template_version_comment.yml | 21 +++++++++++-------- 1 file changed, 12 insertions(+), 9 deletions(-) diff --git a/.github/workflows/template_version_comment.yml b/.github/workflows/template_version_comment.yml index 9dea41f..e8aafe4 100644 --- a/.github/workflows/template_version_comment.yml +++ b/.github/workflows/template_version_comment.yml @@ -10,9 +10,11 @@ jobs: steps: - name: Check out pipeline code uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4 + with: + ref: ${{ github.event.pull_request.head.sha }} - name: Read template version from .nf-core.yml - uses: pietrobolcato/action-read-yaml@1.0.0 + uses: nichmor/minimal-read-yaml@v0.0.2 id: read_yml with: config: ${{ github.workspace }}/.nf-core.yml @@ -24,20 +26,21 @@ jobs: - name: Check nf-core outdated id: nf_core_outdated - run: pip list --outdated | grep nf-core + run: echo "OUTPUT=$(pip list --outdated | grep nf-core)" >> ${GITHUB_ENV} - name: Post nf-core template version comment uses: mshick/add-pr-comment@b8f338c590a895d50bcbfa6c5859251edc8952fc # v2 if: | - ${{ steps.nf_core_outdated.outputs.stdout }} =~ 'nf-core' + contains(env.OUTPUT, 'nf-core') with: repo-token: ${{ secrets.NF_CORE_BOT_AUTH_TOKEN }} allow-repeats: false message: | - ## :warning: Newer version of the nf-core template is available. - - Your pipeline is using an old version of the nf-core template: ${{ steps.read_yml.outputs['nf_core_version'] }}. - Please update your pipeline to the latest version. - - For more documentation on how to update your pipeline, please see the [nf-core documentation](https://github.com/nf-core/tools?tab=readme-ov-file#sync-a-pipeline-with-the-template) and [Synchronisation documentation](https://nf-co.re/docs/contributing/sync). + > [!WARNING] + > Newer version of the nf-core template is available. + > + > Your pipeline is using an old version of the nf-core template: ${{ steps.read_yml.outputs['nf_core_version'] }}. + > Please update your pipeline to the latest version. + > + > For more documentation on how to update your pipeline, please see the [nf-core documentation](https://github.com/nf-core/tools?tab=readme-ov-file#sync-a-pipeline-with-the-template) and [Synchronisation documentation](https://nf-co.re/docs/contributing/sync). # From aafd92a31573e39e9eef16102ea57010f62bc7ed Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 09:42:13 +0100 Subject: [PATCH 23/31] trying to fix ci.yml --- .github/workflows/ci.yml | 94 ++++++++++++++++++++++++++++++++-------- 1 file changed, 77 insertions(+), 17 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 6f061ea..3759130 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -11,6 +11,12 @@ on: env: NXF_ANSI_LOG: false + NFT_VER: "0.9.1" + NFT_WORKDIR: "~" + NFT_DIFF: "pdiff" + NFT_DIFF_ARGS: "--line-numbers --width 120 --expand-tabs=2" + NXF_SINGULARITY_CACHEDIR: ${{ github.workspace }}/.singularity + NXF_SINGULARITY_LIBRARYDIR: ${{ github.workspace }}/.singularity concurrency: group: "${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}" @@ -18,42 +24,96 @@ concurrency: jobs: test: - name: Run pipeline with test data + name: "Run pipeline with test data (${{ matrix.NXF_VER }} | ${{ matrix.test_name }} | ${{ matrix.profile }})" # Only run on push if this is the nf-core dev branch (merged PRs) if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/drugresponseeval') }}" runs-on: ubuntu-latest strategy: + fail-fast: false matrix: NXF_VER: - "24.04.2" - "latest-everything" + shard: [1, 2, 3, 4, 5] + filter: [pipeline, workflow] + profile: + - "docker" + - "singularity" + test_name: + - "test" + isMaster: + - ${{ github.base_ref == 'master' }} + # Exclude conda and singularity on dev + exclude: + - isMaster: false + profile: "conda" + - isMaster: false + profile: "singularity" steps: - name: Check out pipeline code uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4 + with: + fetch-depth: 0 - - name: Install Nextflow + - name: Set up Nextflow uses: nf-core/setup-nextflow@v2 with: version: "${{ matrix.NXF_VER }}" - - name: Disk space cleanup - uses: jlumbroso/free-disk-space@54081f138730dfa15788a46383842cd2f914a1be # v1.3.1 + - name: Install pdiff to see diff between nf-test snapshots + run: | + python -m pip install --upgrade pip + pip install pdiff + + - uses: nf-core/setup-nf-test@v1 + with: + version: ${{ env.NFT_VER }} + + - name: Set up Apptainer + if: matrix.profile == 'singularity' + uses: eWaterCycle/setup-apptainer@main + + - name: Set up Singularity + if: matrix.profile == 'singularity' + run: | + mkdir -p $NXF_SINGULARITY_CACHEDIR + mkdir -p $NXF_SINGULARITY_LIBRARYDIR + + - name: Set up Miniconda + if: matrix.profile == 'conda' + uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3 + with: + miniconda-version: "latest" + auto-update-conda: true + conda-solver: libmamba + channels: conda-forge,bioconda - - name: Run pipeline with test data (docker) - # TODO nf-core: You can customise CI pipeline run tests as required - # For example: adding multiple test runs with different parameters - # Remember that you can parallelise this by using strategy.matrix + - name: Set up Conda + if: matrix.profile == 'conda' run: | - nextflow run ${GITHUB_WORKSPACE} -profile test,docker --outdir ./results + echo $(realpath $CONDA)/condabin >> $GITHUB_PATH + echo $(realpath python) >> $GITHUB_PATH - - name: Run pipeline with test data (singularity) - # TODO nf-core: You can customise CI pipeline run tests as required + - name: Clean up Disk space + uses: jlumbroso/free-disk-space@54081f138730dfa15788a46383842cd2f914a1be # v1.3.1 + + - name: Run Tests (Shard ${{ matrix.shard }}/${{ strategy.job-total }}) run: | - nextflow run ${GITHUB_WORKSPACE} -profile test,singularity --outdir ./results - if: "${{ github.base_ref == 'master' }}" + nf-test test \ + --ci \ + --shard ${{ matrix.shard }}/${{ strategy.job-total }} \ + --changed-since HEAD^ \ + --profile "+${{ matrix.profile }}" \ + --filter ${{ matrix.filter }} - - name: Run pipeline with test data (conda) - # TODO nf-core: You can customise CI pipeline run tests as required + - name: Output log on failure + if: failure() run: | - nextflow run ${GITHUB_WORKSPACE} -profile test,conda --outdir ./results - if: "${{ github.base_ref == 'master' }}" + sudo apt install bat > /dev/null + batcat --decorations=always --color=always ${{ github.workspace }}/.nf-test/tests/*/meta/nextflow.log + + - name: Publish Test Report + uses: mikepenz/action-junit-report@v3 + if: always() # always run even if the previous step fails + with: + report_paths: test.xml From 95cde66ad4ae49554a3721d7c67c0f9663bd229e Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 09:47:32 +0100 Subject: [PATCH 24/31] trying to fix ci.yml --- .github/workflows/ci.yml | 112 +++++++++++++++++++++++---------------- 1 file changed, 67 insertions(+), 45 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 3759130..14e96ef 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -1,32 +1,50 @@ name: nf-core CI # This workflow runs the pipeline with the minimal test dataset to check that it completes without any syntax errors on: - push: - branches: - - dev pull_request: release: types: [published] workflow_dispatch: env: - NXF_ANSI_LOG: false - NFT_VER: "0.9.1" - NFT_WORKDIR: "~" NFT_DIFF: "pdiff" NFT_DIFF_ARGS: "--line-numbers --width 120 --expand-tabs=2" + NFT_VER: "0.9.0" + NFT_WORKDIR: "~" + NXF_ANSI_LOG: false NXF_SINGULARITY_CACHEDIR: ${{ github.workspace }}/.singularity NXF_SINGULARITY_LIBRARYDIR: ${{ github.workspace }}/.singularity concurrency: group: "${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}" cancel-in-progress: true - jobs: + nf-test-changes: + name: Check for changes + runs-on: ubuntu-latest + outputs: + nf_test_files: ${{ steps.list.outputs.components }} + steps: + - uses: actions/checkout@v4 + with: + fetch-depth: 0 + + - name: List nf-test files + id: list + uses: adamrtalbot/detect-nf-test-changes@v0.0.2 + with: + head: ${{ github.sha }} + base: origin/${{ github.base_ref }} + include: .github/include.yaml + + - name: print list of nf-test files + run: | + echo ${{ steps.list.outputs.components }} + test: - name: "Run pipeline with test data (${{ matrix.NXF_VER }} | ${{ matrix.test_name }} | ${{ matrix.profile }})" - # Only run on push if this is the nf-core dev branch (merged PRs) - if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/drugresponseeval') }}" + name: "Run tests (${{ matrix.nf_test_files }} ${{ matrix.profile }} NF-${{ matrix.NXF_VER }})" + needs: [nf-test-changes] + if: needs.nf-test-changes.outputs.nf_test_files != '[]' runs-on: ubuntu-latest strategy: fail-fast: false @@ -34,41 +52,27 @@ jobs: NXF_VER: - "24.04.2" - "latest-everything" - shard: [1, 2, 3, 4, 5] - filter: [pipeline, workflow] + nf_test_files: ["${{ fromJson(needs.nf-test-changes.outputs.nf_test_files) }}"] profile: - "docker" - "singularity" - test_name: - - "test" isMaster: - ${{ github.base_ref == 'master' }} # Exclude conda and singularity on dev exclude: - - isMaster: false - profile: "conda" - isMaster: false profile: "singularity" + - NXF_VER: "latest-everything" + profile: "singularity" steps: - name: Check out pipeline code uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4 - with: - fetch-depth: 0 - name: Set up Nextflow uses: nf-core/setup-nextflow@v2 with: version: "${{ matrix.NXF_VER }}" - - name: Install pdiff to see diff between nf-test snapshots - run: | - python -m pip install --upgrade pip - pip install pdiff - - - uses: nf-core/setup-nf-test@v1 - with: - version: ${{ env.NFT_VER }} - - name: Set up Apptainer if: matrix.profile == 'singularity' uses: eWaterCycle/setup-apptainer@main @@ -79,32 +83,32 @@ jobs: mkdir -p $NXF_SINGULARITY_CACHEDIR mkdir -p $NXF_SINGULARITY_LIBRARYDIR - - name: Set up Miniconda - if: matrix.profile == 'conda' - uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3 + - name: Install nf-test + uses: nf-core/setup-nf-test@v1 with: - miniconda-version: "latest" - auto-update-conda: true - conda-solver: libmamba - channels: conda-forge,bioconda + version: ${{ env.NFT_VER }} - - name: Set up Conda - if: matrix.profile == 'conda' + - uses: actions/setup-python@v4 + with: + python-version: "3.10" + architecture: "x64" + + - name: Install pdiff to see diff between nf-test snapshots run: | - echo $(realpath $CONDA)/condabin >> $GITHUB_PATH - echo $(realpath python) >> $GITHUB_PATH + python -m pip install --upgrade pip + pip install pdiff - name: Clean up Disk space uses: jlumbroso/free-disk-space@54081f138730dfa15788a46383842cd2f914a1be # v1.3.1 - - name: Run Tests (Shard ${{ matrix.shard }}/${{ strategy.job-total }}) + - name: Run nf-test run: | - nf-test test \ - --ci \ - --shard ${{ matrix.shard }}/${{ strategy.job-total }} \ - --changed-since HEAD^ \ - --profile "+${{ matrix.profile }}" \ - --filter ${{ matrix.filter }} + nf-test test --verbose ${{ matrix.nf_test_files }} --profile "+${{ matrix.profile }}" --junitxml=test.xml --tap=test.tap + + - uses: pcolby/tap-summary@v1 + with: + path: >- + test.tap - name: Output log on failure if: failure() @@ -117,3 +121,21 @@ jobs: if: always() # always run even if the previous step fails with: report_paths: test.xml + + confirm-pass: + runs-on: ubuntu-latest + needs: [test] + if: always() + steps: + - name: All tests ok + if: ${{ !contains(needs.*.result, 'failure') }} + run: exit 0 + - name: One or more tests failed + if: ${{ contains(needs.*.result, 'failure') }} + run: exit 1 + + - name: debug-print + if: always() + run: | + echo "toJSON(needs) = ${{ toJSON(needs) }}" + echo "toJSON(needs.*.result) = ${{ toJSON(needs.*.result) }}" From 4af82b0ecbc2dfd4db331d8f89da302836e4c4fd Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 09:51:54 +0100 Subject: [PATCH 25/31] rolling back ci.yml --- .github/workflows/ci.yml | 126 +++++++-------------------------------- 1 file changed, 22 insertions(+), 104 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 14e96ef..6f061ea 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -1,141 +1,59 @@ name: nf-core CI # This workflow runs the pipeline with the minimal test dataset to check that it completes without any syntax errors on: + push: + branches: + - dev pull_request: release: types: [published] workflow_dispatch: env: - NFT_DIFF: "pdiff" - NFT_DIFF_ARGS: "--line-numbers --width 120 --expand-tabs=2" - NFT_VER: "0.9.0" - NFT_WORKDIR: "~" NXF_ANSI_LOG: false - NXF_SINGULARITY_CACHEDIR: ${{ github.workspace }}/.singularity - NXF_SINGULARITY_LIBRARYDIR: ${{ github.workspace }}/.singularity concurrency: group: "${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}" cancel-in-progress: true -jobs: - nf-test-changes: - name: Check for changes - runs-on: ubuntu-latest - outputs: - nf_test_files: ${{ steps.list.outputs.components }} - steps: - - uses: actions/checkout@v4 - with: - fetch-depth: 0 - - - name: List nf-test files - id: list - uses: adamrtalbot/detect-nf-test-changes@v0.0.2 - with: - head: ${{ github.sha }} - base: origin/${{ github.base_ref }} - include: .github/include.yaml - - - name: print list of nf-test files - run: | - echo ${{ steps.list.outputs.components }} +jobs: test: - name: "Run tests (${{ matrix.nf_test_files }} ${{ matrix.profile }} NF-${{ matrix.NXF_VER }})" - needs: [nf-test-changes] - if: needs.nf-test-changes.outputs.nf_test_files != '[]' + name: Run pipeline with test data + # Only run on push if this is the nf-core dev branch (merged PRs) + if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/drugresponseeval') }}" runs-on: ubuntu-latest strategy: - fail-fast: false matrix: NXF_VER: - "24.04.2" - "latest-everything" - nf_test_files: ["${{ fromJson(needs.nf-test-changes.outputs.nf_test_files) }}"] - profile: - - "docker" - - "singularity" - isMaster: - - ${{ github.base_ref == 'master' }} - # Exclude conda and singularity on dev - exclude: - - isMaster: false - profile: "singularity" - - NXF_VER: "latest-everything" - profile: "singularity" steps: - name: Check out pipeline code uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4 - - name: Set up Nextflow + - name: Install Nextflow uses: nf-core/setup-nextflow@v2 with: version: "${{ matrix.NXF_VER }}" - - name: Set up Apptainer - if: matrix.profile == 'singularity' - uses: eWaterCycle/setup-apptainer@main - - - name: Set up Singularity - if: matrix.profile == 'singularity' - run: | - mkdir -p $NXF_SINGULARITY_CACHEDIR - mkdir -p $NXF_SINGULARITY_LIBRARYDIR - - - name: Install nf-test - uses: nf-core/setup-nf-test@v1 - with: - version: ${{ env.NFT_VER }} - - - uses: actions/setup-python@v4 - with: - python-version: "3.10" - architecture: "x64" - - - name: Install pdiff to see diff between nf-test snapshots - run: | - python -m pip install --upgrade pip - pip install pdiff - - - name: Clean up Disk space + - name: Disk space cleanup uses: jlumbroso/free-disk-space@54081f138730dfa15788a46383842cd2f914a1be # v1.3.1 - - name: Run nf-test + - name: Run pipeline with test data (docker) + # TODO nf-core: You can customise CI pipeline run tests as required + # For example: adding multiple test runs with different parameters + # Remember that you can parallelise this by using strategy.matrix run: | - nf-test test --verbose ${{ matrix.nf_test_files }} --profile "+${{ matrix.profile }}" --junitxml=test.xml --tap=test.tap - - - uses: pcolby/tap-summary@v1 - with: - path: >- - test.tap + nextflow run ${GITHUB_WORKSPACE} -profile test,docker --outdir ./results - - name: Output log on failure - if: failure() + - name: Run pipeline with test data (singularity) + # TODO nf-core: You can customise CI pipeline run tests as required run: | - sudo apt install bat > /dev/null - batcat --decorations=always --color=always ${{ github.workspace }}/.nf-test/tests/*/meta/nextflow.log - - - name: Publish Test Report - uses: mikepenz/action-junit-report@v3 - if: always() # always run even if the previous step fails - with: - report_paths: test.xml - - confirm-pass: - runs-on: ubuntu-latest - needs: [test] - if: always() - steps: - - name: All tests ok - if: ${{ !contains(needs.*.result, 'failure') }} - run: exit 0 - - name: One or more tests failed - if: ${{ contains(needs.*.result, 'failure') }} - run: exit 1 + nextflow run ${GITHUB_WORKSPACE} -profile test,singularity --outdir ./results + if: "${{ github.base_ref == 'master' }}" - - name: debug-print - if: always() + - name: Run pipeline with test data (conda) + # TODO nf-core: You can customise CI pipeline run tests as required run: | - echo "toJSON(needs) = ${{ toJSON(needs) }}" - echo "toJSON(needs.*.result) = ${{ toJSON(needs.*.result) }}" + nextflow run ${GITHUB_WORKSPACE} -profile test,conda --outdir ./results + if: "${{ github.base_ref == 'master' }}" From 29c8d0d407c24c48a22173677da2dc3d1ccd0cef Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 09:59:15 +0100 Subject: [PATCH 26/31] does this template_version_comment.yml update now? --- .github/workflows/template_version_comment.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/template_version_comment.yml b/.github/workflows/template_version_comment.yml index e8aafe4..ad95636 100644 --- a/.github/workflows/template_version_comment.yml +++ b/.github/workflows/template_version_comment.yml @@ -2,7 +2,8 @@ name: nf-core template version comment # This workflow is triggered on PRs to check if the pipeline template version matches the latest nf-core version. # It posts a comment to the PR, even if it comes from a fork. -on: pull_request_target +on: + pull_request: jobs: template_version: From 238ea4665979e119e49289809507708e928de2ee Mon Sep 17 00:00:00 2001 From: Judith Bernett <38618495+JudithBernett@users.noreply.github.com> Date: Mon, 25 Nov 2024 10:39:39 +0100 Subject: [PATCH 27/31] Remove unnecessary statements in .nf-core.yml MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Matthias Hörtenhuber --- .nf-core.yml | 2 -- 1 file changed, 2 deletions(-) diff --git a/.nf-core.yml b/.nf-core.yml index a06ac73..bad883f 100644 --- a/.nf-core.yml +++ b/.nf-core.yml @@ -10,8 +10,6 @@ lint: files_unchanged: - .github/CONTRIBUTING.md - assets/sendmail_template.txt - - .github/CONTRIBUTING.md - - assets/sendmail_template.txt multiqc_config: false nf_core_version: 3.0.2 org_path: null From 87db9b1312e651a1b90941761a81edd2149cd2ee Mon Sep 17 00:00:00 2001 From: Judith Bernett <38618495+JudithBernett@users.noreply.github.com> Date: Mon, 25 Nov 2024 10:40:30 +0100 Subject: [PATCH 28/31] remove unnecessary statements in .nf-core.yml MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Matthias Hörtenhuber --- .nf-core.yml | 3 --- 1 file changed, 3 deletions(-) diff --git a/.nf-core.yml b/.nf-core.yml index bad883f..741acee 100644 --- a/.nf-core.yml +++ b/.nf-core.yml @@ -4,9 +4,6 @@ lint: - conf/igenomes.config - conf/igenomes_ignored.config - assets/multiqc_config.yml - - conf/igenomes.config - - conf/igenomes_ignored.config - - assets/multiqc_config.yml files_unchanged: - .github/CONTRIBUTING.md - assets/sendmail_template.txt From 1857efa8c12558d1fc8ebf2595f8121d65816690 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 10:47:38 +0100 Subject: [PATCH 29/31] sorted the cited implemented tools alphabetically, renamed the pipeline picture and added more alt-text --- CITATIONS.md | 16 ++++++++-------- README.md | 2 +- ...=> drugresponseeval_pipeline_simplified.png} | Bin 3 files changed, 9 insertions(+), 9 deletions(-) rename assets/{DrEval_pipeline_simplified.png => drugresponseeval_pipeline_simplified.png} (100%) diff --git a/CITATIONS.md b/CITATIONS.md index 95debcc..53b3aca 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -14,25 +14,25 @@ ## Pipeline tools -- [DrEvalPy](https://github.com/daisybio/drevalpy) +- [DrEvalPy](https://github.com/daisybio/drevalpy): The pipeline mostly automates the individual steps of the DrEvalPy PyPI package. > Bernett, J, Iversen, P, Picciani, M, Wilhelm, M, Baum, K, List, M. Will be published soon. -- [SRMF](https://doi.org/10.1186/s12885-017-3500-5) +- [DIPK](https://doi.org/10.1093/bib/bbae153): Implemented model in the pipeline. - > Wang L, Li X, Zhang L, Gao Q. Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization. BMC cancer. 2017 Dec;17:1-2. + > Li P, Jiang Z, Liu T, Liu X, Qiao H, Yao X. Improving drug response prediction via integrating gene relationships with deep learning. Briefings in Bioinformatics. 2024 May;25(3):bbae153. -- [MOLI](https://doi.org/10.1093/bioinformatics/btz318) +- [MOLI](https://doi.org/10.1093/bioinformatics/btz318): Implemented model in the pipeline. > Sharifi-Noghabi H, Zolotareva O, Collins CC, Ester M. MOLI: multi-omics late integration with deep neural networks for drug response prediction. Bioinformatics. 2019 Jul;35(14):i501-9. -- [SuperFELT](https://doi.org/10.1186/s12859-021-04146-z) +- [SRMF](https://doi.org/10.1186/s12885-017-3500-5): Implemented model in the pipeline. - > Park S, Soh J, Lee H. Super. FELT: supervised feature extraction learning using triplet loss for drug response prediction with multi-omics data. BMC bioinformatics. 2021 May 25;22(1):269. + > Wang L, Li X, Zhang L, Gao Q. Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization. BMC cancer. 2017 Dec;17:1-2. -- [DIPK](https://doi.org/10.1093/bib/bbae153) +- [SuperFELT](https://doi.org/10.1186/s12859-021-04146-z): Implemented model in the pipeline. - > Li P, Jiang Z, Liu T, Liu X, Qiao H, Yao X. Improving drug response prediction via integrating gene relationships with deep learning. Briefings in Bioinformatics. 2024 May;25(3):bbae153. + > Park S, Soh J, Lee H. Super. FELT: supervised feature extraction learning using triplet loss for drug response prediction with multi-omics data. BMC bioinformatics. 2021 May 25;22(1):269. ## Software packaging/containerisation tools diff --git a/README.md b/README.md index c230cd7..e5b9e0f 100644 --- a/README.md +++ b/README.md @@ -34,7 +34,7 @@ tuning is fair and consistent. With its flexible model interface, DrEval support ranging from statistical models to complex neural networks. By contributing your model to the DrEval catalog, you can increase your work's exposure, reusability, and transferability. -# ![DrEval_pipeline](assets/DrEval_pipeline_simplified.png) +# ![Pipeline diagram showing the major steps of nf-core/drugresponseeval](assets/drugresponseeval_pipeline_simplified.png) 1. The response data is loaded 2. All models are trained and evaluated in a cross-validation setting diff --git a/assets/DrEval_pipeline_simplified.png b/assets/drugresponseeval_pipeline_simplified.png similarity index 100% rename from assets/DrEval_pipeline_simplified.png rename to assets/drugresponseeval_pipeline_simplified.png From 304a6956b30fbfc0aed29a605c40696ac37c0d60 Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 11:07:27 +0100 Subject: [PATCH 30/31] ignoring input parameter --- .nf-core.yml | 2 ++ nextflow_schema.json | 12 ------------ 2 files changed, 2 insertions(+), 12 deletions(-) diff --git a/.nf-core.yml b/.nf-core.yml index 741acee..7bc803a 100644 --- a/.nf-core.yml +++ b/.nf-core.yml @@ -8,6 +8,8 @@ lint: - .github/CONTRIBUTING.md - assets/sendmail_template.txt multiqc_config: false + nextflow_config: + - params.input nf_core_version: 3.0.2 org_path: null repository_type: pipeline diff --git a/nextflow_schema.json b/nextflow_schema.json index 7804e2b..7d57ead 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -53,18 +53,6 @@ "fa_icon": "fas fa-envelope", "help_text": "Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file (`~/.nextflow/config`) then you don't need to specify this on the command line for every run.", "pattern": "^([a-zA-Z0-9_\\-\\.]+)@([a-zA-Z0-9_\\-\\.]+)\\.([a-zA-Z]{2,5})$" - }, - "input": { - "type": "string", - "format": "file-path", - "exists": true, - "schema": "assets/schema_input.json", - "mimetype": "text/csv", - "pattern": "^\\S+\\.csv$", - "description": "Unnecessary parameter for the pipeline, added to satisfy linting.", - "help_text": "Unnecessary parameter for the pipeline, added to satisfy linting.", - "fa_icon": "fas fa-file-csv", - "hidden": true } } }, From 004555c404b25557a588cb03a600bb769704c8aa Mon Sep 17 00:00:00 2001 From: Judith Bernett Date: Mon, 25 Nov 2024 11:18:34 +0100 Subject: [PATCH 31/31] forgot to remove input from nextflow.config --- nextflow.config | 1 - 1 file changed, 1 deletion(-) diff --git a/nextflow.config b/nextflow.config index 1b47b13..36e18bc 100644 --- a/nextflow.config +++ b/nextflow.config @@ -29,7 +29,6 @@ params { save_datasets = false // Boilerplate options - input = null outdir = 'results' publish_dir_mode = 'copy' email = null