PMID- 31123038
OWN - NLM
STAT- MEDLINE
DCOM- 20200113
LR  - 20240229
IS  - 1943-2631 (Electronic)
IS  - 0016-6731 (Print)
IS  - 0016-6731 (Linking)
VI  - 212
IP  - 3
DP  - 2019 Jul
TI  - Fine-Scale Inference of Ancestry Segments Without Prior Knowledge of Admixing 
      Groups.
PG  - 869-889
LID - 10.1534/genetics.119.302139 [doi]
AB  - We present an algorithm for inferring ancestry segments and characterizing 
      admixture events, which involve an arbitrary number of genetically differentiated 
      groups coming together. This allows inference of the demographic history of the 
      species, properties of admixing groups, identification of signatures of natural 
      selection, and may aid disease gene mapping. The algorithm employs nested hidden 
      Markov models to obtain local ancestry estimation along the genome for each 
      admixed individual. In a range of simulations, the accuracy of these estimates 
      equals or exceeds leading existing methods. Moreover, and unlike these 
      approaches, we do not require any prior knowledge of the relationship between 
      subgroups of donor reference haplotypes and the unseen mixing ancestral 
      populations. Our approach infers these in terms of conditional "copying 
      probabilities." In application to the Human Genome Diversity Project, we 
      corroborate many previously inferred admixture events (e.g., an ancient admixture 
      event in the Kalash). We further identify novel events such as complex four-way 
      admixture in San-Khomani individuals, and show that Eastern European populations 
      possess [Formula: see text] ancestry from a group resembling modern-day central 
      Asians. We also identify evidence of recent natural selection favoring 
      sub-Saharan ancestry at the human leukocyte antigen (HLA) region, across North 
      African individuals. We make available an R and C++ software library, which we 
      term MOSAIC (which stands for MOSAIC Organizes Segments of Ancestry In 
      Chromosomes).
CI  - Copyright (c) 2019 Salter-Townshend and Myers.
FAU - Salter-Townshend, Michael
AU  - Salter-Townshend M
AUID- ORCID: 0000-0001-6232-9109
AD  - School of Mathematics and Statistics, University College Dublin, Ireland 
      michael.salter-townshend@ucd.ie.
FAU - Myers, Simon
AU  - Myers S
AUID- ORCID: 0000-0002-2585-9626
AD  - Dept. of Statistics, University of Oxford and Wellcome Trust Centre for Human 
      Genetics, Oxford, UK.
LA  - eng
GR  - 212284/Z/18/Z/WT_/Wellcome Trust/United Kingdom
GR  - 098387/Z/12/Z/WT_/Wellcome Trust/United Kingdom
GR  - WT_/Wellcome Trust/United Kingdom
GR  - 203141/Z/16/Z/WT_/Wellcome Trust/United Kingdom
GR  - R01 HG006399/HG/NHGRI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20190523
PL  - United States
TA  - Genetics
JT  - Genetics
JID - 0374636
RN  - 0 (HLA Antigens)
SB  - IM
MH  - Genetic Drift
MH  - Genetics, Population/methods
MH  - HLA Antigens/genetics
MH  - Haplotypes
MH  - Humans
MH  - Markov Chains
MH  - *Models, Genetic
MH  - *Pedigree
MH  - Population/*genetics
MH  - Software
PMC - PMC6614886
OTO - NOTNLM
OT  - admixture
OT  - demography
OT  - drift
OT  - population genetics
OT  - selection
EDAT- 2019/05/28 06:00
MHDA- 2020/01/14 06:00
PMCR- 2019/05/23
CRDT- 2019/05/25 06:00
PHST- 2019/03/21 00:00 [received]
PHST- 2019/05/18 00:00 [accepted]
PHST- 2019/05/28 06:00 [pubmed]
PHST- 2020/01/14 06:00 [medline]
PHST- 2019/05/25 06:00 [entrez]
PHST- 2019/05/23 00:00 [pmc-release]
AID - genetics.119.302139 [pii]
AID - 302139 [pii]
AID - 10.1534/genetics.119.302139 [doi]
PST - ppublish
SO  - Genetics. 2019 Jul;212(3):869-889. doi: 10.1534/genetics.119.302139. Epub 2019 
      May 23.