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Journal of Zhejiang University (Agriculture and Life Sciences)  2014, Vol. 40 Issue (4): 379-386    DOI: 10.3785/j.issn.1008-9209.2014.04.212
Review     
Tools for quantitative trait locus mapping and genome-wide association study mapping: a review
Md. Mamun Monir1, Zhu Jun1,2,3*
(1. Department of Agronomy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China; 2. Department of Mathematics, Zhejiang University, Hangzhou 310058, China; 3. Research Center for Air Pollution and Health, Zhejiang University, Hangzhou 310058, China)
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Abstract  One of the key objectives in genomics studies is to understand genetic architecture of complex traits and diseases. Quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) mapping have been using to dissect genetic architecture of complex traits and diseases that assists in genetic breeding and drug discovery. In this paper, we reviewed QTL mapping and GWAS mapping methodologies and softwares for complex traits or diseases analysis. PLINK, TASSEL, SNPassoc, GenABEL and ProbABEL are most popular softwares providing many useful functions for GWAS mapping. PLINK is the highest popular opensource whole genome association analysis toolset, which implements a number of functions for SNP data analysis. TASSEL is another popular software, implements Q+K composite approach for association mapping. SNPassoc, GenABEL and ProbABEL are popular open source R packages using for association mapping. We have briefly described above popular softwares for GWAS mapping and have described implemented functions in QTXNetwork software for GWAS mapping of quantitative trait with markers (QTLs), SNPs (QTSs), transcripts (QTTs), proteins (QTPs), and metabolites (QTMs). We also describe some other popular softwares such as Windows QTL Cartographer, QTL Express, Map Manager QTX, R/qtl and QTLNetwork for QTL mapping.

Published: 20 July 2014
CLC:  Q 939.96  
Cite this article:

Md. Mamun Monir, Zhu Jun. Tools for quantitative trait locus mapping and genome-wide association study mapping: a review. Journal of Zhejiang University (Agriculture and Life Sciences), 2014, 40(4): 379-386.

URL:

http://www.zjujournals.com/agr/10.3785/j.issn.1008-9209.2014.04.212     OR     http://www.zjujournals.com/agr/Y2014/V40/I4/379


数量性状位点定位和全基因组关联分析的方法与软件综述(英文)

基因组学研究的主要目标是剖析复杂性状和疾病的遗传结构。数量性状位点(quantitative trait locus,QTL)定位和全基因组关联分析(genome-wide association study,GWAS)已经应用于遗传育种和药物研制,分析复杂性状和复杂疾病的遗传结构。本文回顾了分析复杂性状和复杂疾病的QTL定位和GWAS的作图方法和软件。PLINK,TASSEL,SNPassoc,GenABEL和ProbABEL是流行的软件,为GWAS提供了许多有用的功能。PLINK是目前最流行的开源全基因组关联分析的工具集,它聚合了用于分析SNP数据的许多功能。TASSEL是另一种流行的软件,整合了Q+K关联分析的诸多方法。SNPassoc、GenABEL和ProbABEL是应用于关联分析的开源代码R软件包。本文对上述提及的GWAS关联分析流行软件作了简要介绍,并介绍了新研制的QTXNetwork分析软件,它可分析QTL和GWAS定位数量性状SNP(QTS)、数量性状转录子(QTT)、数量性状蛋白子(QTP)和数量性状代谢子(QTM)。本文还介绍了一些常用的分析软件,例如Windows QTL Cartographer,QTL Express,Map Manager QTX,R/qtl和QTLNetwork。
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