PopHumanVar: an interactive application for the functional characterization and prioritization of adaptive genomic variants in humans
Author(s) -
Aina Colomer-Vilaplana,
Jesús Murga-Moreno,
Aleix Canalda-Baltrons,
Clara Inserte,
Daniel E. Soto,
Marta CoronadoZamora,
Antonio Barbadilla,
Sònia Casillas
Publication year - 2021
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkab925
Subject(s) - biology , computational biology , genomics , genome , selection (genetic algorithm) , 1000 genomes project , genetics , population , prioritization , single nucleotide polymorphism , computer science , gene , genotype , artificial intelligence , demography , management science , sociology , economics
Adaptive challenges that humans faced as they expanded across the globe left specific molecular footprints that can be decoded in our today's genomes. Different sets of metrics are used to identify genomic regions that have undergone selection. However, there are fewer methods capable of pinpointing the allele ultimately responsible for this selection. Here, we present PopHumanVar, an interactive online application that is designed to facilitate the exploration and thorough analysis of candidate genomic regions by integrating both functional and population genomics data currently available. PopHumanVar generates useful summary reports of prioritized variants that are putatively causal of recent selective sweeps. It compiles data and graphically represents different layers of information, including natural selection statistics, as well as functional annotations and genealogical estimations of variant age, for biallelic single nucleotide variants (SNVs) of the 1000 Genomes Project phase 3. Specifically, PopHumanVar amasses SNV-based information from GEVA, SnpEFF, GWAS Catalog, ClinVar, RegulomeDB and DisGeNET databases, as well as accurate estimations of iHS, nSL and iSAFE statistics. Notably, PopHumanVar can successfully identify known causal variants of frequently reported candidate selection regions, including EDAR in East-Asians, ACKR1 (DARC) in Africans and LCT/MCM6 in Europeans. PopHumanVar is open and freely available at https://pophumanvar.uab.cat.
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