GsGator: An integrated web platform for cross-species gene set analysis

Hyunjung Kang, Ikjung Choi, Sooyoung Cho, Daeun Ryu, Sanghyuk Lee, Wankyu Kim

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Background: Gene set analysis (GSA) is useful in deducing biological significance of gene lists using a priori defined gene sets such as gene ontology (GO) or pathways. Phenotypic annotation is sparse for human genes, but is far more abundant for other model organisms such as mouse, fly, and worm. Often, GSA needs to be done highly interactively by combining or modifying gene lists or inspecting gene-gene interactions in a molecular network.Description: We developed gsGator, a web-based platform for functional interpretation of gene sets with useful features such as cross-species GSA, simultaneous analysis of multiple gene sets, and a fully integrated network viewer for visualizing both GSA results and molecular networks. An extensive set of gene annotation information is amassed including GO & pathways, genomic annotations, protein-protein interaction, transcription factor-target (TF-target), miRNA targeting, and phenotype information for various model organisms. By combining the functionalities of Set Creator, Set Operator and Network Navigator, user can perform highly flexible and interactive GSA by creating a new gene list by any combination of existing gene sets (intersection, union and difference) or expanding genes interactively along the molecular networks such as protein-protein interaction and TF-target. We also demonstrate the utility of our interactive and cross-species GSA implemented in gsGator by several usage examples for interpreting genome-wide association study (GWAS) results. gsGator is freely available at Interactive and cross-species GSA in gsGator greatly extends the scope and utility of GSA, leading to novel insights via conserved functional gene modules across different species.

Original languageEnglish
Article number13
JournalBMC Bioinformatics
Issue number1
StatePublished - 14 Jan 2014

Bibliographical note

Funding Information:
Funding: National Research Foundation of Korea (NRF) grants funded by MEST of KOREA (2011–0014992, 2013M3A9B6046519, 2012M3A9C5048707, 2012M3A9D1054744); GIST Systems Biology Infrastructure Establishment Grant (2012–3) through Ewha Research Center for Systems Biology (ERCSB); Ewha Womans University Research Grant of 2013.


  • Cross-species GSA
  • Gene function
  • Gene set analysis
  • Interactive GSA
  • Omics


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