Literature DB >> 30010715

A comprehensive survey of models for dissecting local ancestry deconvolution in human genome.

Ephifania Geza1,2, Jacquiline Mugo1, Nicola J Mulder2, Ambroise Wonkam3, Emile R Chimusa3, Gaston K Mazandu1,2,3.   

Abstract

Over the past decade, studies of admixed populations have increasingly gained interest in both medical and population genetics. These studies have so far shed light on the patterns of genetic variation throughout modern human evolution and have improved our understanding of the demographics and adaptive processes of human populations. To date, there exist about 20 methods or tools to deconvolve local ancestry. These methods have merits and drawbacks in estimating local ancestry in multiway admixed populations. In this article, we survey existing ancestry deconvolution methods, with special emphasis on multiway admixture, and compare these methods based on simulation results reported by different studies, computational approaches used, including mathematical and statistical models, and biological challenges related to each method. This should orient users on the choice of an appropriate method or tool for given population admixture characteristics and update researchers on current advances, challenges and opportunities behind existing ancestry deconvolution methods.
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  admixture; ancestry informative markers; hidden Markov models; linkage disequilibrium; local ancestry

Mesh:

Year:  2019        PMID: 30010715      PMCID: PMC7373186          DOI: 10.1093/bib/bby044

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  48 in total

1.  Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data.

Authors:  Na Li; Matthew Stephens
Journal:  Genetics       Date:  2003-12       Impact factor: 4.562

2.  Design and analysis of admixture mapping studies.

Authors:  C J Hoggart; M D Shriver; R A Kittles; D G Clayton; P M McKeigue
Journal:  Am J Hum Genet       Date:  2004-04-14       Impact factor: 11.025

3.  Robust estimation of local genetic ancestry in admixed populations using a nonparametric Bayesian approach.

Authors:  Kyung-Ah Sohn; Zoubin Ghahramani; Eric P Xing
Journal:  Genetics       Date:  2012-05-29       Impact factor: 4.562

4.  Estimating local ancestry in admixed populations.

Authors:  Sriram Sankararaman; Srinath Sridhar; Gad Kimmel; Eran Halperin
Journal:  Am J Hum Genet       Date:  2008-02       Impact factor: 11.025

5.  Recent genetic selection in the ancestral admixture of Puerto Ricans.

Authors:  Hua Tang; Shweta Choudhry; Rui Mei; Martin Morgan; William Rodriguez-Cintron; Esteban González Burchard; Neil J Risch
Journal:  Am J Hum Genet       Date:  2007-08-01       Impact factor: 11.025

Review 6.  Analyses of genetic ancestry enable key insights for molecular ecology.

Authors:  Zachariah Gompert; C Alex Buerkle
Journal:  Mol Ecol       Date:  2013-09-19       Impact factor: 6.185

7.  Accurate local-ancestry inference in exome-sequenced admixed individuals via off-target sequence reads.

Authors:  Youna Hu; Cristen Willer; Xiaowei Zhan; Hyun Min Kang; Gonçalo R Abecasis
Journal:  Am J Hum Genet       Date:  2013-11-07       Impact factor: 11.025

8.  Ancestry and pharmacogenomics of relapse in acute lymphoblastic leukemia.

Authors:  Jun J Yang; Cheng Cheng; Meenakshi Devidas; Xueyuan Cao; Yiping Fan; Dario Campana; Wenjian Yang; Geoff Neale; Nancy J Cox; Paul Scheet; Michael J Borowitz; Naomi J Winick; Paul L Martin; Cheryl L Willman; W Paul Bowman; Bruce M Camitta; Andrew Carroll; Gregory H Reaman; William L Carroll; Mignon Loh; Stephen P Hunger; Ching-Hon Pui; William E Evans; Mary V Relling
Journal:  Nat Genet       Date:  2011-02-06       Impact factor: 38.330

9.  Strong association of socioeconomic status with genetic ancestry in Latinos: implications for admixture studies of type 2 diabetes.

Authors:  J C Florez; A L Price; D Campbell; L Riba; M V Parra; F Yu; C Duque; R Saxena; N Gallego; M Tello-Ruiz; L Franco; M Rodríguez-Torres; A Villegas; G Bedoya; C A Aguilar-Salinas; M T Tusié-Luna; A Ruiz-Linares; D Reich
Journal:  Diabetologia       Date:  2009-06-13       Impact factor: 10.122

10.  Leveraging local ancestry to detect gene-gene interactions in genome-wide data.

Authors:  Hugues Aschard; Alexander Gusev; Robert Brown; Bogdan Pasaniuc
Journal:  BMC Genet       Date:  2015-10-24       Impact factor: 2.797

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  8 in total

Review 1.  Systematic Review on Local Ancestor Inference From a Mathematical and Algorithmic Perspective.

Authors:  Jie Wu; Yangxiu Liu; Yiqiang Zhao
Journal:  Front Genet       Date:  2021-05-24       Impact factor: 4.599

2.  GeMo: a web-based platform for the visualization and curation of genome ancestry mosaics.

Authors:  Marilyne Summo; Aurore Comte; Guillaume Martin; Pierrick Perelle; Eric M Weitz; Gaëtan Droc; Mathieu Rouard
Journal:  Database (Oxford)       Date:  2022-07-14       Impact factor: 4.462

3.  Fine Scale Genomic Signals of Admixture and Alien Introgression among Asian Rice Landraces.

Authors:  João D Santos; Dmytro Chebotarov; Kenneth L McNally; Jérôme Bartholomé; Gaëtan Droc; Claire Billot; Jean Christophe Glaszmann
Journal:  Genome Biol Evol       Date:  2019-05-01       Impact factor: 3.416

4.  Comparing local ancestry inference models in populations of two- and three-way admixture.

Authors:  Ryan Schubert; Angela Andaleon; Heather E Wheeler
Journal:  PeerJ       Date:  2020-10-02       Impact factor: 2.984

5.  A Chromosome-Painting-Based Pipeline to Infer Local Ancestry under Limited Source Availability.

Authors:  Ludovica Molinaro; Davide Marnetto; Mayukh Mondal; Linda Ongaro; Burak Yelmen; Daniel John Lawson; Francesco Montinaro; Luca Pagani
Journal:  Genome Biol Evol       Date:  2021-04-05       Impact factor: 3.416

6.  Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power.

Authors:  Caroline M Nievergelt; Mark J Daly; Benjamin M Neale; Elizabeth G Atkinson; Adam X Maihofer; Masahiro Kanai; Alicia R Martin; Konrad J Karczewski; Marcos L Santoro; Jacob C Ulirsch; Yoichiro Kamatani; Yukinori Okada; Hilary K Finucane; Karestan C Koenen
Journal:  Nat Genet       Date:  2021-01-18       Impact factor: 38.330

7.  Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes.

Authors:  Aurélien Cottin; Benjamin Penaud; Jean-Christophe Glaszmann; Nabila Yahiaoui; Mathieu Gautier
Journal:  G3 (Bethesda)       Date:  2020-02-06       Impact factor: 3.154

8.  Local ancestry inference provides insight into Tilapia breeding programmes.

Authors:  Alex Avallone; Kerry L Bartie; Sarah-Louise C Selly; Khanam Taslima; Antonio Campos Mendoza; Michaël Bekaert
Journal:  Sci Rep       Date:  2020-10-29       Impact factor: 4.379

  8 in total

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