Literature DB >> 23756889

Quality control for genome-wide association studies.

Cedric Gondro1, Seung Hwan Lee, Hak Kyo Lee, Laercio R Porto-Neto.   

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.

Mesh:

Year:  2013        PMID: 23756889     DOI: 10.1007/978-1-62703-447-0_5

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  3 in total

1.  Genetics and brain morphology.

Authors:  Lachlan T Strike; Baptiste Couvy-Duchesne; Narelle K Hansell; Gabriel Cuellar-Partida; Sarah E Medland; Margaret J Wright
Journal:  Neuropsychol Rev       Date:  2015-03-14       Impact factor: 7.444

2.  hsphase: an R package for pedigree reconstruction, detection of recombination events, phasing and imputation of half-sib family groups.

Authors:  Mohammad H Ferdosi; Brian P Kinghorn; Julius H J van der Werf; Seung Hwan Lee; Cedric Gondro
Journal:  BMC Bioinformatics       Date:  2014-06-07       Impact factor: 3.169

3.  Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure.

Authors:  Laura Balagué-Dobón; Alejandro Cáceres; Juan R González
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

  3 in total

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