SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci

Citation:

Slowikowski K, Hu X, Raychaudhuri S. SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci [Internet]. Bioinformatics 2014;30(17):2496-7.

Date Published:

2014 Sep 01

Abstract:

UNLABELLED: We created a fast, robust and general C+ + implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol. AVAILABILITY AND IMPLEMENTATION: http://broadinstitute.org/mpg/snpsea. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Last updated on 04/29/2020