Prioritising positively selected variants in whole-genome sequencing data using FineMAV.

ABSTRACT:

Background

In population genomics, polymorphisms that are highly differentiated between geographically separated populations are often suggestive of Darwinian positive selection. Genomic scans have highlighted several such regions in African and non-African populations, but only a handful of these have functional data that clearly associates candidate variations driving the selection process. Fine-Mapping of Adaptive Variation (FineMAV) was developed to address this in a high-throughput manner using population based whole-genome sequences generated by the 1000 Genomes Project. It pinpoints positively selected genetic variants in sequencing data by prioritizing high frequency, population-specific and functional derived alleles.

Results

We developed a stand-alone software that

SUBMITTER: Wahyudi F 

PROVIDER: S-EPMC8684245 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature