Literature DB >> 30590437

KinVis: a visualization tool to detect cryptic relatedness in genetic datasets.

Ehsan Ullah1, Michaël Aupetit1, Arun Das1, Abhishek Patil1, Noora Al Muftah2, Reda Rawi1,3, Mohamad Saad1, Halima Bensmail1.   

Abstract

MOTIVATION: It is important to characterize individual relatedness in terms of familial relationships and underlying population structure in genome-wide association studies for correct downstream analysis. The characterization of individual relatedness becomes vital if the cohort is to be used as reference panel in other studies for association tests and for identifying ethnic diversities. In this paper, we propose a kinship visualization tool to detect cryptic relatedness between subjects. We utilize multi-dimensional scaling, bar charts, heat maps and node-link visualizations to enable analysis of relatedness information.
AVAILABILITY AND IMPLEMENTATION: Available online as well as can be downloaded at http://shiny-vis.qcri.org/public/kinvis/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Mesh:

Year:  2019        PMID: 30590437      PMCID: PMC6931347          DOI: 10.1093/bioinformatics/bty1028

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  11 in total

1.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

2.  PLINK: a tool set for whole-genome association and population-based linkage analyses.

Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
Journal:  Am J Hum Genet       Date:  2007-07-25       Impact factor: 11.025

3.  Variance component model to account for sample structure in genome-wide association studies.

Authors:  Hyun Min Kang; Jae Hoon Sul; Susan K Service; Noah A Zaitlen; Sit-Yee Kong; Nelson B Freimer; Chiara Sabatti; Eleazar Eskin
Journal:  Nat Genet       Date:  2010-03-07       Impact factor: 38.330

4.  Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia.

Authors:  Kevin J Galinsky; Gaurav Bhatia; Po-Ru Loh; Stoyan Georgiev; Sayan Mukherjee; Nick J Patterson; Alkes L Price
Journal:  Am J Hum Genet       Date:  2016-02-25       Impact factor: 11.025

5.  Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness.

Authors:  Matthew P Conomos; Michael B Miller; Timothy A Thornton
Journal:  Genet Epidemiol       Date:  2015-03-23       Impact factor: 2.135

6.  Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure.

Authors:  Tulaya Limpiti; Apichart Intarapanich; Anunchai Assawamakin; Philip J Shaw; Pongsakorn Wangkumhang; Jittima Piriyapongsa; Chumpol Ngamphiw; Sissades Tongsima
Journal:  BMC Bioinformatics       Date:  2011-06-23       Impact factor: 3.169

7.  A global reference for human genetic variation.

Authors:  Adam Auton; Lisa D Brooks; Richard M Durbin; Erik P Garrison; Hyun Min Kang; Jan O Korbel; Jonathan L Marchini; Shane McCarthy; Gil A McVean; Gonçalo R Abecasis
Journal:  Nature       Date:  2015-10-01       Impact factor: 49.962

8.  PCA-based population structure inference with generic clustering algorithms.

Authors:  Chih Lee; Ali Abdool; Chun-Hsi Huang
Journal:  BMC Bioinformatics       Date:  2009-01-30       Impact factor: 3.169

9.  SHIPS: Spectral Hierarchical clustering for the Inference of Population Structure in genetic studies.

Authors:  Matthieu Bouaziz; Caroline Paccard; Mickael Guedj; Christophe Ambroise
Journal:  PLoS One       Date:  2012-10-12       Impact factor: 3.240

Review 10.  Inferring ancestry from population genomic data and its applications.

Authors:  Badri Padhukasahasram
Journal:  Front Genet       Date:  2014-07-03       Impact factor: 4.599

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