gsasnp2 to run in linux online online with Winfy

We have hosted the application gsasnp2 to run in linux online in order to run this application in our online workstations with Wine or directly.

Quick description about gsasnp2 to run in linux online:

* 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 and outputs pathway genesets ‘enriched’ with genes associated with the given phenotype. It also provides both local and global protein interaction networks in the associated pathways.

* Article: SYoon, HCTNguyen, YJYoo, JKim, BBaik, SKim, JKim, SKim, DNam, "Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2", Nucleic Acids Research, Vol. 46(10), e60(2018).

* PubMed ID: 29562348

* DOI: 10.1093/nar/gky175

-> PLEASE MOVE OR MAKE A COPY OF 'DATA' FOLDER INTO YOUR INTENSIVE TEST FOLDER (I.E. LINUX, MAC OR WINDOWS SPECIFIED FOLDER) TO ALLOW THE PROGRAM TO FIND THE PREDESIGNED DATA.

* UPDATE NOTE:
-> Aug-7-2019: add an update for Ubuntu-19.04. You will need Boost library installed (sudo apt-get install libboost-all-dev)
-> Mar-7-2018: revise header terms in the output file

Features:

• 1/ 'DECENT 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.

User interface: Win32 (MS Windows), Command-line.
Programming Language: C++, PHP, JavaScript.

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