RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations

被引：27

作者：

Haller, Toomas ^{[1
,2
]}

Kals, Mart ^{[2
]}

Esko, Tonu ^{[3
,4
]}

Maegi, Reedik ^{[2
]}

Fischer, Krista ^{[2
,5
,6
]}

机构：

[1] MIT, Cambridge, MA 02139 USA

[2] EGCUT, Tartu, Estonia

[3] EGCUT, GWAS Related Projects, Tartu, Estonia

[4] Broad Inst Harvard & MIT, GWAS Related Projects, Cambridge, MA USA

[5] Univ Tartu, Fac Med, EE-51010 Tartu, Estonia

[6] MRC Biostat Unit, Cambridge, England

来源：

BRIEFINGS IN BIOINFORMATICS | 2015年 / 16卷 / 01期

关键词：

GWAS; genome-wide analysis; linear regression; continuous traits; combinatorial traits; metabolomics; GENOME-WIDE ASSOCIATION; GENOTYPES;

D O I：

10.1093/bib/bbt066

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Genome-wide association studies are becoming computationally more demanding with the growing amounts of data. Combinatorial traits can increase the data dimensions beyond the computational capabilities of the current tools. We addressed this issue by creating an application for quick association analysis that is ten to hundreds of times faster than the leading fast methods. Our tool (RegScan) is designed for performing basic linear regression analysis with continuous traits maximally fast on large data sets. RegScan specifically targets association analysis of combinatorial traits in metabolomics. It can both generate and analyze the combinatorial traits efficiently. RegScan is capable of analyzing any number of traits together without the need to specify each trait individually. The main goal of the article is to show that RegScan can be the preferred analytical tool when large amounts of data need to be analyzed quickly using the allele frequency test. Availability: Precompiled RegScan (all major platforms), source code, user guide and examples are freely available at www. biobank. ee/regscan.

引用

页码：39 / 44

页数：6

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