Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/14593
Title: Quality Control for Genome-Wide Association Studies
Contributor(s): Gondro, Cedric  (author)orcid ; Lee, S H (author); Lee, H K (author); Porto-Neto, Laercio R (author)
Publication Date: 2013
DOI: 10.1007/978-1-62703-447-0_5
Handle Link: https://hdl.handle.net/1959.11/14593
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 throughout 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.
Publication Type: Book Chapter
Source of Publication: Genome-Wide Association Studies and Genomic Prediction, p. 129-147
Publisher: Humana Press
Place of Publication: New York, United States of America
ISBN: 9781627034463
9781627034470
Fields of Research (FoR) 2008: 060412 Quantitative Genetics (incl Disease and Trait Mapping Genetics)
Fields of Research (FoR) 2020: 310506 Gene mapping
Socio-Economic Objective (SEO) 2008: 970106 Expanding Knowledge in the Biological Sciences
Socio-Economic Objective (SEO) 2020: 280102 Expanding knowledge in the biological sciences
HERDC Category Description: B1 Chapter in a Scholarly Book
Publisher/associated links: http://trove.nla.gov.au/version/198468706
Series Name: Methods in Molecular Biology
Series Number : 1019
Editor: Editor(s): Cedric Gondro, Julius van der Werf, Ben Hayes
Appears in Collections:Book Chapter

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