Methods in statistical genomics In the context of genome-wide association studies

By Phillip Cooley

The objective of this book is to describe procedures for analyzing genome-wide association studies (GWAS). Some of the material is unpublished and contains commentary and unpublished research; other chapters (Chapters 4 through 7) have been published in other journals. Each previously published chapter investigates a different genomics model, but all focus on identifying the strengths and limitations of various statistical procedures that have been applied to different GWAS scenarios.


Cooley, P. (Ed.) (2016). Methods in statistical genomics: In the context of genome-wide association studies. (RTI Press Publication No. BK-0016-1608). Research Triangle Park, NC: RTI Press.

© 2019 RTI International. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.


Phillip CooleyPhilip C. Cooley, MS, Senior Fellow in bioinformatics and high-performance computing, is a principal scientist with more than 50 years of experience developing computer models for the study of environmental health and infectious and chronic disease. Cooley has designed and implemented a series of influenza transmission models for the study and management of pandemic flu. He has also designed a model to study the double burden of malnutrition in Indonesia. His current research includes an assessment of statistical methods for biomarker explorations in the context of genome-wide-analysis studies.

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