Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics

Often, analysis for pharmacogenomic studies involving multiple drugs from the same class is completed by analyzing each drug individually for association with genomic variation. However, by completing the analysis of each drug individually, we may be losing valuable information. When studying multip...

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Main Authors:	Fridley, B L, Jenkins, G D, Batzler, A, Wang, L, Ji, Y, Li, F, Weinshilboum, R M
Format:	Online
Language:	English
Published:	Nature Publishing Group 2012
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3084322/

id	pubmed-3084322
recordtype	oai_dc
spelling	pubmed-30843222012-04-01 Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics Fridley, B L Jenkins, G D Batzler, A Wang, L Ji, Y Li, F Weinshilboum, R M Original Article Often, analysis for pharmacogenomic studies involving multiple drugs from the same class is completed by analyzing each drug individually for association with genomic variation. However, by completing the analysis of each drug individually, we may be losing valuable information. When studying multiple drugs from the same drug class, one may wish to determine genomic variation that explains the difference in response between individuals for the drug class, as opposed to each individual drug. Therefore, we have developed a multivariate model to assess whether genomic variation impacts a class of drugs. In addition to determine genomic effects that are similar for the drugs, we will also be able to determine genomic effects that differ between the drugs (that is, interaction). We will illustrate the utility of this multivariate model for cytotoxicity and genomic data collected on the Coriell Human Variation Panel for the class of anti-purine metabolites (6-mercaptopurine and 6-thioguanine). Nature Publishing Group 2012-04 2010-11-09 /pmc/articles/PMC3084322/ /pubmed/21060324 http://dx.doi.org/10.1038/tpj.2010.83 Text en Copyright © 2012 Macmillan Publishers Limited http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under the Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
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	Fridley, B L Jenkins, G D Batzler, A Wang, L Ji, Y Li, F Weinshilboum, R M
spellingShingle	Fridley, B L Jenkins, G D Batzler, A Wang, L Ji, Y Li, F Weinshilboum, R M Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics
author_facet	Fridley, B L Jenkins, G D Batzler, A Wang, L Ji, Y Li, F Weinshilboum, R M
author_sort	Fridley, B L
title	Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics
title_short	Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics
title_full	Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics
title_fullStr	Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics
title_full_unstemmed	Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics
title_sort	multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics
description	Often, analysis for pharmacogenomic studies involving multiple drugs from the same class is completed by analyzing each drug individually for association with genomic variation. However, by completing the analysis of each drug individually, we may be losing valuable information. When studying multiple drugs from the same drug class, one may wish to determine genomic variation that explains the difference in response between individuals for the drug class, as opposed to each individual drug. Therefore, we have developed a multivariate model to assess whether genomic variation impacts a class of drugs. In addition to determine genomic effects that are similar for the drugs, we will also be able to determine genomic effects that differ between the drugs (that is, interaction). We will illustrate the utility of this multivariate model for cytotoxicity and genomic data collected on the Coriell Human Variation Panel for the class of anti-purine metabolites (6-mercaptopurine and 6-thioguanine).
publisher	Nature Publishing Group
publishDate	2012
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3084322/
_version_	1611451018398138368

Multivariate models to detect genomic signatures for a class of drugs: application to thiopurines pharmacogenomics

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