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

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 ana...

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Main Authors:	Haller, Toomas, Kals, Mart, Esko, Tõnu, Mägi, Reedik, Fischer, Krista
Format:	Online
Language:	English
Published:	Oxford University Press 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4293375/

id	pubmed-4293375
recordtype	oai_dc
spelling	pubmed-42933752015-02-03 RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations Haller, Toomas Kals, Mart Esko, Tõnu Mägi, Reedik Fischer, Krista Papers 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. Oxford University Press 2015-01 2013-09-05 /pmc/articles/PMC4293375/ /pubmed/24008273 http://dx.doi.org/10.1093/bib/bbt066 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Haller, Toomas Kals, Mart Esko, Tõnu Mägi, Reedik Fischer, Krista
spellingShingle	Haller, Toomas Kals, Mart Esko, Tõnu Mägi, Reedik Fischer, Krista RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations
author_facet	Haller, Toomas Kals, Mart Esko, Tõnu Mägi, Reedik Fischer, Krista
author_sort	Haller, Toomas
title	RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations
title_short	RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations
title_full	RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations
title_fullStr	RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations
title_full_unstemmed	RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations
title_sort	regscan: a gwas tool for quick estimation of allele effects on continuous traits and their combinations
description	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.
publisher	Oxford University Press
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4293375/
_version_	1613176355069886464

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

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