Statistical Methods in Integrative Genomics

Author:

Richardson Sylvia1,Tseng George C.2,Sun Wei34

Affiliation:

1. MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge CB2 0SR, United Kingdom;

2. Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania 15261;

3. Department of Biostatistics, Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599;

4. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 27516

Abstract

Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then we review statistical methods of integrative genomics with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions.

Publisher

Annual Reviews

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

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