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2011 | OriginalPaper | Chapter

13. eQTL Mapping for Functional Classes of Saccharomyces cerevisiae Genes with Multivariate Sparse Partial Least Squares Regression

Authors : Dongjun Chung, Sündüz Keleş

Published in: Handbook of Statistical Bioinformatics

Publisher: Springer Berlin Heidelberg

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Abstract

The availability of high-throughput genotyping technologies and microarray assays has enabled investigation of genetic variations that influence levels of gene expression. Expression Quantitative Trait Loci (eQTL) mapping methods have been successfully used to identify the genetic basis of gene expression which in turn led to identification of candidate genes and construction of regulatory networks. One challenging statistical aspect of eQTL mapping is the existence of thousands of traits. We have recently proposed a multivariate sparse partial least squares framework for mapping multiple quantitative traits and identifying genetic variations that affect the expression of a group of genes. In this book chapter, we provide a comprehensive illustration of this methodology with a Saccharomyces cerevisiae linkage study. Data from this study involves segregants from a cross between two Saccharomyces cerevisiae strains. Our application focuses on elucidating genomic markers that affect expression of functional yeast gene classes. We illustrate identification of eQTL regions affecting whole functional classes of genes as well as eQTL regions influencing individual genes.

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Metadata
Title
eQTL Mapping for Functional Classes of Saccharomyces cerevisiae Genes with Multivariate Sparse Partial Least Squares Regression
Authors
Dongjun Chung
Sündüz Keleş
Copyright Year
2011
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-16345-6_13

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