GCEN++: A C++ tool for Gene Co-Expression Networks

Introduction
GCEN++ is a C++ tool for gene co-expression networks analysis and function annotation.

Download
GCEN++ is freely available under the GPLv3 license at http://gcen.biochen.com. It is implemented in C++ and supported on Mac OS X, Linux and MS Windows.
Linux: GCEN++_Linux_0.2.0.zip
Windows: GCEN++_Windows_0.2.0.zip
Mac OS will soon be supported!

Usage
data_stat
data_stat -i input_file
-i --input <input file> (default: ./test/gene_expr.tsv)
-h --help print help information
Input file format: table separate, first column are genename, the others are gene expression value
data_norm
data_norm -i input_file -o output_file
-i --input <input file> (default: ./test/gene_expr.tsv)
-o --output <output file> (default: ./test/gene_expr_norm.tsv)
-m --method <upqt or median or deseq> normalization method (default: upqt)
-h --help print help information
Input file format: table separate, first column are genename, the others are gene expression value
Output file format: The file structure is the same as input file
data_filter
data_filter -i input_file -o output_file
-i --input <input file> (default: ./test/gene_expr.tsv)
-o --output <output file> (default: ./test/gene_expr_filter.tsv)
-m --mean <number> mean cutoff (default: 0.0)
-s --std <number> standard deviation cutoff (default: 0.0)
-h --help print help information
Input file format: table separate, first column are genename, the others are gene expression value
Output file format: The file structure is the same as input file
network_build
network_build -i input_file -o output_file
-i --input <input file> (default: ./test/gene_expr.tsv)
-o --output <output file> (default: ./test/gene_co_expr.network)
-m --method <pearson or spearman> correlation coefficient method (default: spearman)
-l --log <log2 or log10> make a log transformation (default: not transform)
-t --thread <number> cpu cores (default: 2)
-p --pval <number> p value cutoff (default: 0.001)
-c --cor <number> correlation coefficient cutoff (default: 0.1)
-s --signed <y or n> singed network (default: n)
-f --fdr <y or n> calculate FDR (default: n)
-h --help print help information
Input file format: table separate, first column are genename, the others are gene expression value
Output file format: table separate, four or five columns are geneA, geneB, correlation coefficent, P value, FDR

Example
./data_stat -i ./test/gene_expr.tsv
./data_filter -i ./test/gene_expr.tsv -o ./test/gene_expr_filter.tsv -m 0.001 -s 0.001
./data_norm -i ./test/gene_expr_filter.tsv -o ./test/gene_expr_filter_norm.tsv -m upqt
./network_build -i ./test/gene_expr_filter_norm.tsv -o ./test/gene_co_expr.network -m spearman -t 16 -f y -s y

Todo
Implementation of "module identify" and "GO/KEGG function annotation".

Contact
Wen Chen, Ph.D. Candidate, chenwen@biochen.com