An integrated web-based resource for mapping functional networks of long or circular forms of non-coding RNAs
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coexp
coexpc
deg
degc
demo_file
figs
msigdb
README.html
README.md
circos_zoom.r
circrna_local_run_cor.sh
circrna_local_run_deg.sh
coexp_pairs_annotation.r
correlation.r
deseq2.r
deseq2_annotation.r
gene_enrichment.r
heatmap.R
lncrna_local_run_cor.sh
lncrna_local_run_deg.sh
lncrna_local_run_deg_tcga.sh
randomization.R
scatterplot.r
triple_network_circRNA_RBP_2step.R
triple_network_circRNA_sponge_2step.R
triple_network_lncRNA_RBP_2step.R
triple_network_lncRNA_sponge_2step.R
universal_function.R

README.md

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
wget http://app.cgu.edu.tw/circlnc/tcga/tcga.zip # 1.6GB
unzip db.zip  
unzip tcga.zip  

3. Perform the differential expression analysis

Preperation of gene matrix file


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. App folders

  3. Run the app by clicking Run App. 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. App folders

  3. Run the app by clicking Run App. Run App