Tool suite :: Network :: Co-expression network

Co-expression network analysis provides some clues for understanding the biological meaning extracted from the expression modules. In order to identify the functional association of co-expressed genes, we developed a co-expression network for cotton from microarray data.

Users can submit a probe set ID to get its co-expressed genes or transcripts, and then the co-expressed information related to the submitted probe set will be visualized and shown.


Please input one probe ID:


[Example]


To construct the co-expression network, the gene expression data set (279 samples) was downloaded from the Gene Expression Omnibus (GEO) database, with accession number GPL8672. We preprocessed the CEL source files by gcRMA (Guanine Cytosine Robust Multi-Array Analysis) algorithm with default parameters in the R Bioconductor package.

Furthermore, PCCs between probe sets were calculated and filtered (PCC <= -0.7 or PCC>=0.7) to construct a gene co-expression network. There were 1 419 237 and 1 127 237 co-expressed pairs between 20 480 probe sets respectively regarded as positively and negatively correlated.