TESS3: fast inference of spatial population structure and genome scans for selection. (17th October 2015)

• Record Type: Journal Article
• Authors: Caye, Kevin; Deist, Timo M.; Martins, Helena; Michel, Olivier; François, Olivier
• Is Part Of: Molecular ecology resources. Volume 16:Number 2(2016:Mar.)
• Page Start: 540
• Page End: 548
• Publication Date: 2015-10-17
• Subjects: control of false discoveries -- genome scans for selection -- geographic variation -- inference of population structure; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.12471
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract: Geography and landscape are important determinants of genetic variation in natural populations, and several ancestry estimation methods have been proposed to investigate population structure using genetic and geographic data simultaneously. Those approaches are often based on computer‐intensive stochastic simulations and do not scale with the dimensions of the data sets generated by high‐throughput sequencing technologies. There is a growing demand for faster algorithms able to analyse genomewide patterns of population genetic variation in their geographic context. In this study, we presentTESS3, a major update of the spatial ancestry estimation programTESS . By combining matrix factorization and spatial statistical methods, TESS3 provides estimates of ancestry coefficients with accuracy comparable toTESS and with run‐times much faster than the Bayesian version. In addition, theTESS3 program can be used to perform genome scans for selection, and separate adaptive from nonadaptive genetic variation using ancestral allele frequency differentiation tests. The main features ofTESS3 are illustrated using simulated data and analysing genomic data from European lines of the plant species Arabidopsis thaliana .