Use of circlncRNAnet in local mode

This instruction will guide the users to use the circlncRNAnet in local mode. To set up a local run mode, the following three items are required:

1. Linux environment.
2. R, v3.3.2 is recommended.
3. RStudio.

Then, follow the instructions below for installation and data analyses:

1. Installation of prerequisites

# download circlncRNAnet
git clone https://github.com/smw1414/circlncRNAnet.git
cd  circlncRNAnet

# make all scripts executable  
chmod +x *.[Rr]
chmod +x *.sh

# installation of reguired pakcages for R
R
install.packages(c("shiny","shinyjs","ggplot2","plotly","data.table","DT","visNetwork","googleVis","magrittr","factoextra","plyr","circlize","getopt"))
source("https://bioconductor.org/biocLite.R")
biocLite(c("DESeq2","BiocParallel","org.Hs.eg.db","clusterProfiler"))
q("no")

2. Download the db files

wget http://app.cgu.edu.tw/circlnc/db/db.zip # 1GB
# or https://drive.google.com/file/d/1GZTwYKFbeyejiuGdzmt48hMxkDCeucX6/view?usp=sharing
wget http://app.cgu.edu.tw/circlnc/tcga/tcga.zip # 1.6GB
# or https://drive.google.com/file/d/17fEiOTrJb1L-9LrQG8pDxel5rh_Ep-ce/view?usp=sharing
unzip db.zip  
unzip tcga.zip  

3. Perform the differential expression analysis

Preperation of gene matrix file

• Please refer http://app.cgu.edu.tw/circlnc/circlnc_tutorial/_book/data-input.html#preparation-of-input-files

Perform the differential expression analysis

1. Open RStudio and create a new R project under the folder of circlncRNAnet.
2. Run the following commands for either lncRNA or circRNA differential expression analyses.

# lncRNA  
system("./lncrna_local_run_deg.sh <gene reads count table> <demographic table>")

# circRNA 
system("./circrna_local_run_deg.sh <gene reads count table> <demographic table> <circRNA reads count table>")

# TCGA data 
# Please refer the table below for the available TCGA datasets
system("./lncrna_local_run_deg_tcga.sh <cancer code>")
system("./lncrna_local_run_deg_tcga.sh TCGA-LUAD")

# example of demo datset  
# lncRNA 
system("./lncrna_local_run_deg.sh demo_file/TCGA_COADREAD_GENCODEV25_raw_read_count.txt demo_file/TCGA_COADREAD_GENCODEV25_condition.txt")

# circRNA  
system("./circrna_local_run_deg.sh demo_file/encode_example_Gene_raw_read_count_casted.txt demo_file/encode_example_circRNA_condition.txt demo_file/encode_example_circRNA_raw_read_count_casted.txt ") 

TCGA datasets
TCGA-BLCA	TCGA-ESCA	TCGA-LIHC	TCGA-PRAD
TCGA-BRCA	TCGA-HNSC	TCGA-LUAD	TCGA-READ
TCGA-CESC	TCGA-KICH	TCGA-LUSC	TCGA-STAD
TCGA-CHOL	TCGA-KIRC	TCGA-PAAD	TCGA-THCA
TCGA-COAD	TCGA-KIRP	TCGA-PCPG	TCGA-UCEC

4. Visualization of differential expresion results/table

1. Open the file browser in the right bottom panel.

2. Open the app.R under the deg folder for lncRNA or the degc folder for circRNA analysis.

3. Run the app by clicking Run App.

• Users can browse and select the gene of interest now.
• The Calcaulate co-expression button was designed for the PHP and the Shiny enviroment. Thus, the button is non-functional in this enviroment. To calculate the co-expressed genes, please follow the next step.

5. Perform co-expression analysis

# lncRNA
system("./lncrna_local_run_cor.sh <lncRNAs>")  

# circRNA
system("./circrna_local_run_cor.sh <circRNAs>")

# <lncRNAs/circRNAs> could be one or more genes, seperated by comma.

# example of demo datset
# lncRNA 
system("./lncrna_local_run_cor.sh CCAT1,PVT1")

# circRNA  
system("./circrna_local_run_cor.sh chr11_35204640_35201082_fwd,chr10_97437191_97438703_rev,chr9_128515639_128508876_fwd") 

6. Visualization of co-expression analysis results

1. Open the file browser in the right bottom panel.

2. Open the app.R under the coexp folder for lncRNA or the coexpc folder for circRNA analysis.

3. Run the app by clicking Run App.