Coexpression networks help overcome the limitations of sparsity in gene functional annotations, by providing a means to transfer knowledge from annotated genes to genes yet unannotated, based on the 'guilt-by association' assumptions. RECoN is designed to identify clusters of functionally genes that tightly coexpress in a compendium of abiotic-stress gene expression experiments in rice.

Use RECoN to
1) Upload the differential expression profile of genes in response to an abiotic-stress to find clusters that are most highly expressed/repressed in the experiment. Prepare the transcriptome file in a format like this. This file contains locus ids of all the genes in the first column and their differential expression values in the second column, with a tab space in between, and a header.

2) Search clusters linked to a specific biological process from the drop down menu.

3) Use a single gene as a guide to find other genes highly coexpressed with it.

Citation: Krishnan Arjun, Gupta Chirag, Ambavaram Madana M. R., Pereira Andy (2017). RECoN: Rice Environment Coexpression Network for Systems Level Analysis of Abiotic-Stress Response. Frontiers in Plant Science

 Cluster Enrichment Tool

[ upload a .txt file with all genes and their fold-change values ]

Qvalue threshold 0.1 0.05 0.01 0.001

 Search biological process

 Query a single gene

[start typing a Locus ID in MSU format(LOC_Os...) ]