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A review of statistical methods for expression quantitative trait loci mapping

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Abstract

With high-throughput technologies now widely available, investigators can easily measure thousands of phenotypes for quantitative trait loci (QTL) mapping. Microarray measurements are particularly amenable to QTL mapping, as evidenced by a number of recent studies demonstrating utility across a broad range of biological endeavors. The early success stories have impelled a rapid increase in both the number and complexity of expression QTL (eQTL) experiments. Consequently, there is a need to consider the statistical principles involved in the design and analysis of these experiments and the methods currently being used. In this article we review these principles and methods and discuss the open questions most likely to yield significant progress toward increasing the amount of meaningful information obtained from eQTL mapping experiments.

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Acknowledgments

The authors thank Alan Attie, Meng Chen, Michael Newton, and Brian Yandell for useful discussions and two anonymous reviewers for comments that improved the manuscript. They also thank Stephanie Ciatti for extra help at home.

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Authors and Affiliations

  1. Department of Biostatistics and Medical Informatics, University of Wisconsin, 1300 University Avenue (6729 MSC), Madison, Wisconsin, 53706, USA

    Christina Kendziorski

  2. Department of Statistics, University of Wisconsin, 1300 University Avenue (1245 MSC), Madison, Wisconsin, 53706, USA

    Ping Wang

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  1. Christina Kendziorski
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  2. Ping Wang
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Correspondence to Christina Kendziorski.

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Kendziorski, C., Wang, P. A review of statistical methods for expression quantitative trait loci mapping. Mamm Genome 17, 509–517 (2006). https://doi.org/10.1007/s00335-005-0189-6

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  • DOI: https://doi.org/10.1007/s00335-005-0189-6

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