Literature DB >> 22021386

"SNP Snappy": a strategy for fast genome-wide association studies fitting a full mixed model.

Karin Meyer1, Bruce Tier.   

Abstract

A strategy to reduce computational demands of genome-wide association studies fitting a mixed model is presented. Improvements are achieved by utilizing a large proportion of calculations that remain constant across the multiple analyses for individual markers involved, with estimates obtained without inverting large matrices.

Mesh：

Year:  2011        PMID： 22021386      PMCID： PMC3249377          DOI： 10.1534/genetics.111.134841

Source DB:  PubMed          Journal:  Genetics        ISSN： 0016-6731            Impact factor:   4.562


  6 in total

1.  WOMBAT: a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML).

Authors:  Karin Meyer
Journal:  J Zhejiang Univ Sci B       Date:  2007-11       Impact factor: 3.066

2.  Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis.

Authors:  Yurii S Aulchenko; Dirk-Jan de Koning; Chris Haley
Journal:  Genetics       Date:  2007-07-29       Impact factor: 4.562

3.  Estimated gene frequencies of GeneSTAR markers and their size of effects on meat tenderness, marbling, and feed efficiency in temperate and tropical beef cattle breeds across a range of production systems.

Authors:  D J Johnston; H-U Graser
Journal:  J Anim Sci       Date:  2010-02-12       Impact factor: 3.159

4.  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

Review 5.  New approaches to population stratification in genome-wide association studies.

Authors:  Alkes L Price; Noah A Zaitlen; David Reich; Nick Patterson
Journal:  Nat Rev Genet       Date:  2010-07       Impact factor: 53.242

6.  Mixed linear model approach adapted for genome-wide association studies.

Authors:  Zhiwu Zhang; Elhan Ersoz; Chao-Qiang Lai; Rory J Todhunter; Hemant K Tiwari; Michael A Gore; Peter J Bradbury; Jianming Yu; Donna K Arnett; Jose M Ordovas; Edward S Buckler
Journal:  Nat Genet       Date:  2010-03-07       Impact factor: 38.330
  6 in total
  21 in total

1.  Fast computation for genome-wide association studies using boosted one-step statistics.

Authors:  Arend Voorman; Ken Rice; Thomas Lumley
Journal:  Bioinformatics       Date:  2012-05-15       Impact factor: 6.937

Review 2.  Fine-mapping QTLs in advanced intercross lines and other outbred populations.

Authors:  Natalia M Gonzales; Abraham A Palmer
Journal:  Mamm Genome       Date:  2014-06-07       Impact factor: 2.957

3.  GW-SEM: A Statistical Package to Conduct Genome-Wide Structural Equation Modeling.

Authors:  Brad Verhulst; Hermine H Maes; Michael C Neale
Journal:  Behav Genet       Date:  2017-03-15       Impact factor: 2.805

4.  Generalized estimating equations for genome-wide association studies using longitudinal phenotype data.

Authors:  Colleen M Sitlani; Kenneth M Rice; Thomas Lumley; Barbara McKnight; L Adrienne Cupples; Christy L Avery; Raymond Noordam; Bruno H C Stricker; Eric A Whitsel; Bruce M Psaty
Journal:  Stat Med       Date:  2014-10-09       Impact factor: 2.373

5.  A Multivariate Genome-Wide Association Study of Wing Shape in Drosophila melanogaster.

Authors:  William Pitchers; Jessica Nye; Eladio J Márquez; Alycia Kowalski; Ian Dworkin; David Houle
Journal:  Genetics       Date:  2019-02-21       Impact factor: 4.562

6.  Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens.

Authors:  Huiyu Wang; Ignacy Misztal; Ignacio Aguilar; Andres Legarra; Rohan L Fernando; Zulma Vitezica; Ron Okimoto; Terry Wing; Rachel Hawken; William M Muir
Journal:  Front Genet       Date:  2014-05-20       Impact factor: 4.599

7.  Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits.

Authors:  I M MacLeod; P J Bowman; C J Vander Jagt; M Haile-Mariam; K E Kemper; A J Chamberlain; C Schrooten; B J Hayes; M E Goddard
Journal:  BMC Genomics       Date:  2016-02-27       Impact factor: 3.969

8.  An investigation of the effects of BMPR1B, BMP15, and GDF9 genes on litter size in Ramlıç and Dağlıç sheep.

Authors:  Koray Çelikeloğlu; Mustafa Tekerli; Metin Erdoğan; Serdar Koçak; Özlem Hacan; Zehra Bozkurt
Journal:  Arch Anim Breed       Date:  2021-06-03

9.  Practical considerations regarding the use of genotype and pedigree data to model relatedness in the context of genome-wide association studies.

Authors:  Riyan Cheng; Clarissa C Parker; Mark Abney; Abraham A Palmer
Journal:  G3 (Bethesda)       Date:  2013-10-03       Impact factor: 3.154

10.  Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle.

Authors:  Aline Camporez Crispim; Matthew John Kelly; Simone Eliza Facioni Guimarães; Fabyano Fonseca e Silva; Marina Rufino Salinas Fortes; Raphael Rocha Wenceslau; Stephen Moore
Journal:  PLoS One       Date:  2015-10-07       Impact factor: 3.240
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