Local ancestry prediction with PyLAE

被引:0
|
作者
Moshkov, Nikita [1 ,2 ,3 ,4 ]
Smetanin, Aleksandr [5 ]
Tatarinova, Tatiana, V [6 ,7 ,8 ,9 ]
机构
[1] Univ Szeged, Doctoral Sch Interdisciplinary Med, Szeged, Hungary
[2] Biol Res Ctr, Synthet & Syst Biol Unit, Szeged, Hungary
[3] Atlas Biomed Grp Ltd, London, England
[4] HSE Univ, Fac Comp Sci, Lab AI Computat Biol, Moscow, Russia
[5] ITMO Univ, St Petersburg, Russia
[6] Univ La Verne, Dept Biol, La Verne, CA 91750 USA
[7] Siberian Fed Univ, Krasnoyarsk, Russia
[8] Inst Gen Genet, Moscow, Russia
[9] Inst Informat Transmiss Problems, Moscow, Russia
来源
PEERJ | 2021年 / 9卷
关键词
Local ancestry; HMM; Global ancestry; Bio-origin; Selection signals; 1000; Genomes; AFRICAN; NUCLEOTIDE;
D O I
10.7717/peerj.12502
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
We developed PyLAE, a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimating many parameters, it can process thousands of genomes within a day. PyLAE can run on phased or unphased genomic data. We have shown how PyLAE can be applied to the identification of differentially enriched pathways between populations. The local ancestry approach results in higher enrichment scores compared to whole-genome approaches. We benchmarked PyLAE using the 1000 Genomes dataset, comparing the aggregated predictions with the global admixture results and the current gold standard program RFMix. Computational efficiency, minimal requirements for data pre-processing, straightforward presentation of results, and ease of installation make PyLAE a valuable tool to study admixed populations.
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页数:24
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