Journal
BRIEFINGS IN BIOINFORMATICS
Volume 16, Issue 1, Pages 39-44Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbt066
Keywords
GWAS; genome-wide analysis; linear regression; continuous traits; combinatorial traits; metabolomics
Funding
- University of Tartu (grant 'Center of Translational Genomics')
- Estonian Goverment [SF0180142s08]
- European Commission through the European Regional Development Fund in the frame of grant 'Centre of Excellence in Genomics'
- Estonian Research Infrastructure's Roadmap
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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.
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