Pathway Analysis for SNP microarray data

Pathway Analysis (PA) is a powerful method for data analysis in genomics, most often applied to gene expression analysis, but little used to analyze variants such as Single Nucleotide Polymorphisms (SNPs). PA could allow the interpretation of variants concerning the biological processes in which the affected genes and proteins are involved. Currently, the available PA software tools are not able to automatically perform pathway analysis using SNPs data. PA software tools cannot deal natively with SNPs data, hence several software tools have to be used to put SNPs data in the proper format for the analysis. To overcome these limitations, we present SNP Microarray Pathway Analysis (MPA), a software tool able to discriminate relevant genes from SNP microarrays to use in PA analysis. MPA automatically identifies relevant SNPs using the well known Fisher's test, with which to perform PA. Pathway analysis in MPA is obtained employing the Hypergeometric function. As a result, MPA provides to the user the list of enriched pathways from the identified SNPs. MPA software tool along with the user guide and datasets, are available for download at https://gitlab.com/giuseppeagapito/mpa under the GPL v3.0 license.