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 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.
authors.affiliation: The Centre for Genetic Analysis and Applications, University of New England, Armidale, NSW, Australia.
authors.forename: Cedric
authors.initials: C
authors.lastname: Gondro
authors.forename: Seung Hwan
authors.initials: SH
authors.lastname: Lee
authors.forename: Hak Kyo
authors.initials: HK
authors.lastname: Lee
authors.forename: Laercio R
authors.initials: LR
authors.lastname: Porto-Neto
mesh_terms: D000465:Algorithms; D000818:Animals; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D016247:Information Storage and Retrieval; D020641:Polymorphism, Single Nucleotide; D011381:Programming Languages; D011786:Quality Control