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gsasnp2

Posted on by Robin Ding Leave a comment Bio-Informatics, Statistics

* USAGE NOTE:

-> Please move or make a copy of ‘data’ folder into your intensive test folder (i.e. Linux or Mac or Windows specified folder) to allow the program look for predesigned data.

* UPDATE NOTE:

->Aug-4-2017: minor bugs fixed: i/o bugs do not load input from GO and KEGG radio options

-> Apr-3-2017: MacOSX command-line version is added. It also provides the PPI net summarization.

-> Mar-31-2017: Linux and Windows command-line versions now provide the PPI net summary results (except the net visualization)

* GSA-SNP2 is a successor of GSA-SNP (Nam et al. 2010, NAR web server issue). GSA-SNP2 accepts human GWAS summary data (rs numbers, p-values) or gene-wise p-values (possibly obtained from VEGAS or GATES) and outputs pathway gene sets ‘enriched’ with genes associated with the given phenotype. It also provides both local and global protein interaction networks in the associated pathways.

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62 Reviews

  • Unlimited Calling, Faxing, Video Conferencing
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Website https://sites.google.com/view/gsasnp2
Tags
License GNU General Public License version 3.0 (GPLv3) MIT License
Platform Linux Windows
Features
  • 1/ 'Reasonable type I error control' achieved by the following two processes: A) Gene scores are ‘adjusted’ to the number of SNPs assigned to each gene using monotone cubic spline trend curve. B) Adjacent genes with high inter-gene correlations within each pathway were removed
  • 2/ 'High power' and 'fast computation' based on the random set model
  • 3/ 'No critical free parameter'
  • 4/ 'Protein interaction networks' among the member genes were visualized for the significant pathways. This function enables the user to prioritize the core sub-networks within and across the significant pathways. The STRING and HIPPIE networks are currently provided
  • 5/ 'Easy to use': It only requires GWAS summary data (or gene p-values) and takes only a minute or two to get results. Other powerful self-contained pathway tools require the SNP correlation input as well and take a much longer time. User can also upload their own pathway gene-sets and protein interaction networks.