nav-left cat-right

Group Meeting 21/12/20

Speaker: ZHANG Chunyuan

Time: 13:00 – 14:00, Dec 21, 2020
Venue: Room 315, SIBS Main Building

Topic: work progress

Speaker: MA Sen
Time: 14:00 – 15:00, Dec 21, 2020
Venue: Room 315, SIBS Main Building

Topic: 基于NGS数据对HLA分型及人群自然选择的研究(开题报告试讲)

Speaker: LIU Chang
Time: 15:00 – 16:00, Dec 21, 2020
Venue: Room 315, SIBS Main Building

Topic: Detecting Selection from Linked Sites Using an F-Model


Allele frequencies vary across populations and loci, even in the presence of migration. While most differences may be due to genetic drift, divergent selection will further increase differentiation at some loci. Identifying those is key in studying local adaptation, but remains statistically challenging. A particularly elegant way to describe allele frequency differences among populations connected by migration is the F-model, which measures differences in allele frequencies by population specific FST coefficients. This model readily accounts for multiple evolutionary forces by partitioning FST coefficients into locus- and population-specific components reflecting selection and drift, respectively. Here we present an extension of this model to linked loci by means of a hidden Markov model (HMM), which characterizes the effect of selection on linked markers through correlations in the locus specific component along the genome. Using extensive simulations, we show that the statistical power of our method is up to twofold higher than that of previous implementations that assume sites to be independent. We finally evidence selection in the human genome by applying our method to data from the Human Genome Diversity Project (HGDP).

This post is also available in: Chinese (Simplified)

Leave a Reply

You must be logged in to post a comment.