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 |
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Contributor(s): | Gondro, Cedric (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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