@inbook{2a3253562f754aa581009dab2358a936,
title = "Quality Control for Genome-Wide Association Studies",
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.",
keywords = "Quantitative Genetics (incl Disease and Trait Mapping Genetics)",
author = "Cedric Gondro and Lee, \{S H\} and Lee, \{H K\} and Porto-Neto, \{Laercio R\}",
year = "2013",
doi = "10.1007/978-1-62703-447-0\_5",
language = "English",
isbn = "9781627034463",
series = "Methods in Molecular Biology",
publisher = "Humana Press",
number = "1019",
pages = "129--147",
editor = "Cedric Gondro and \{van der Werf\}, Julius and Ben Hayes",
booktitle = "Genome-Wide Association Studies and Genomic Prediction",
edition = "1",
}