ICOSSY: An online tool for context-specific subnetwork discovery from gene expression data

Ashis Saha, Minji Jeon, Aik Choon Tan, Jaewoo Kang

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference.

Original languageEnglish
Article numbere0131656
JournalPloS one
Issue number7
Publication statusPublished - 2015 Jul 6

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF-2014R1A2A1A10051238, 2014M3C9A3063543).

Publisher Copyright:
© 2015 Saha et al.

ASJC Scopus subject areas

  • General Biochemistry,Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • General


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