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Quality control for genome-wide association studies

  • Cedric Gondro
  • , Seung Hwan Lee
  • , Hak Kyo Lee
  • , Laercio R. Porto-Neto
  • University of New England
  • United States Food and Drug Administration
  • Hankyong National University
  • University of Queensland

Research output: Contribution to conferenceChapterpeer-review

Abstract

This chapter overviews the quality control (QC) issues for SNP-based genotyping methods used in genome-wide association studies. The main metrics for evaluating the quality of the genotypes are discussed followed by a worked out example of QC pipeline starting with raw data and finishing with a fully filtered dataset ready for downstream analysis. The emphasis is on automation of data storage, filtering, and manipulation to ensure data integrity throughput the process and on how to extract a global summary from these high dimensional datasets to allow better-informed downstream analytical decisions. All examples will be run using the R statistical programming language followed by a practical example using a fully automated QC pipeline for the Illumina platform.

Original languageEnglish
Title of host publicationGenome-Wide Association Studies and Genomic Prediction
PublisherHumana Press Inc.
Pages129-147
Number of pages19
ISBN (Print)9781627034463
DOIs
StatePublished - 2013

Publication series

NameMethods in Molecular Biology
Volume1019
ISSN (Print)1064-3745

Keywords

  • Genome-wide association studies
  • Illumina
  • Quality control
  • R statistics

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