Abraham A, Labella AL, Benton ML, Rokas A, Capra JA. GSEL: a fast, flexible python package for detecting signatures of diverse evolutionary forces on genomic regions.
Bioinformatics 2023;
39:btad037. [PMID:
36655767 PMCID:
PMC9879724 DOI:
10.1093/bioinformatics/btad037]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 11/17/2022] [Accepted: 01/18/2023] [Indexed: 01/20/2023] Open
Abstract
SUMMARY
GSEL is a computational framework for calculating the enrichment of signatures of diverse evolutionary forces in a set of genomic regions. GSEL can flexibly integrate any sequence-based evolutionary metric and analyze sets of human genomic regions identified by genome-wide assays (e.g. GWAS, eQTL, *-seq). The core of GSEL's approach is the generation of empirical null distributions tailored to the allele frequency and linkage disequilibrium structure of the regions of interest. We illustrate the application of GSEL to variants identified from a GWAS of body mass index, a highly polygenic trait.
AVAILABILITY AND IMPLEMENTATION
GSEL is implemented as a fast, flexible and user-friendly python package. It is available with demonstration data at https://github.com/abraham-abin13/gsel_vec.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
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