A guide to genome-wide association analysis and post-analytic interrogation

Statistics in Medicine
Eric ReedAndrea S Foulkes

Abstract

This tutorial is a learning resource that outlines the basic process and provides specific software tools for implementing a complete genome-wide association analysis. Approaches to post-analytic visualization and interrogation of potentially novel findings are also presented. Applications are illustrated using the free and open-source R statistical computing and graphics software environment, Bioconductor software for bioinformatics and the UCSC Genome Browser. Complete genome-wide association data on 1401 individuals across 861,473 typed single nucleotide polymorphisms from the PennCATH study of coronary artery disease are used for illustration. All data and code, as well as additional instructional resources, are publicly available through the Open Resources in Statistical Genomics project: http://www.stat-gen.org.

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Citations

May 26, 2017·Statistics in Medicine·Jing QianAndrea S Foulkes
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Methods Mentioned

BETA
genotyping
PCA
chip
Acetylation
ChipSeq

Software Mentioned

Unix
Windows
MACH
UCSC Genome Browser
ENCODE
SnpMatrix
MACH2qtl
doParallel
snpStats
Tools Table Browser

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