FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations.

Abstract:

:We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated "gold standard" positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.

journal_name

Genome Biol

journal_title

Genome biology

authors

Szpak M,Mezzavilla M,Ayub Q,Chen Y,Xue Y,Tyler-Smith C

doi

10.1186/s13059-017-1380-2

subject

Has Abstract

pub_date

2018-01-17 00:00:00

pages

5

issue

1

eissn

1474-7596

issn

1474-760X

pii

10.1186/s13059-017-1380-2

journal_volume

19

pub_type

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