Literature DB >> 23479353

JAWAMix5: an out-of-core HDF5-based java implementation of whole-genome association studies using mixed models.

Quan Long1, Qingrun Zhang, Bjarni J Vilhjalmsson, Petar Forai, Ümit Seren, Magnus Nordborg.   

Abstract

SUMMARY: We present JAWAMix5, an out-of-core open-source toolkit for association mapping using high-throughput sequence data. Taking advantage of its HDF5-based implementation, JAWAMix5 stores genotype data on disk and accesses them as though stored in main memory. Therefore, it offers a scalable and fast analysis without concerns about memory usage, whatever the size of the dataset. We have implemented eight functions for association studies, including standard methods (linear models, linear mixed models, rare variants test, analysis in nested association mapping design and local variance component analysis), as well as a novel Bayesian local variance component analysis. Application to real data demonstrates that JAWAMix5 is reasonably fast compared with traditional solutions that load the complete dataset into memory, and that the memory usage is efficient regardless of the dataset size. AVAILABILITY: The source code, a 'batteries-included' executable and user manual can be freely downloaded from http://code.google.com/p/jawamix5/.

Mesh:

Year:  2013        PMID: 23479353     DOI: 10.1093/bioinformatics/btt122

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


  5 in total

1.  lrgpr: interactive linear mixed model analysis of genome-wide association studies with composite hypothesis testing and regression diagnostics in R.

Authors:  Gabriel E Hoffman; Jason G Mezey; Eric E Schadt
Journal:  Bioinformatics       Date:  2014-07-16       Impact factor: 6.937

2.  Inter-tissue coexpression network analysis reveals DPP4 as an important gene in heart to blood communication.

Authors:  Quan Long; Carmen Argmann; Sander M Houten; Tao Huang; Siwu Peng; Yong Zhao; Zhidong Tu; Jun Zhu
Journal:  Genome Med       Date:  2016-02-09       Impact factor: 11.117

3.  AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.

Authors:  Qingrun Zhang; Quan Long; Jurg Ott
Journal:  PLoS Comput Biol       Date:  2014-06-05       Impact factor: 4.475

4.  Power analysis of transcriptome-wide association study: Implications for practical protocol choice.

Authors:  Chen Cao; Bowei Ding; Qing Li; Devin Kwok; Jingjing Wu; Quan Long
Journal:  PLoS Genet       Date:  2021-02-26       Impact factor: 5.917

5.  OCMA: Fast, Memory-Efficient Factorization of Prohibitively Large Relationship Matrices.

Authors:  Zhi Xiong; Qingrun Zhang; Alexander Platt; Wenyuan Liao; Xinghua Shi; Gustavo de Los Campos; Quan Long
Journal:  G3 (Bethesda)       Date:  2019-01-09       Impact factor: 3.154

  5 in total

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