Strategies for processing and quality control of Illumina genotyping arrays.

Zhao S, Jing W, Samuels DC, Sheng Q, Shyr Y, Guo Y
Brief Bioinform. 2018 19 (5): 765-775

PMID: 28334151 · PMCID: PMC6171493 · DOI:10.1093/bib/bbx012

Illumina genotyping arrays have powered thousands of large-scale genome-wide association studies over the past decade. Yet, because of the tremendous volume and complicated genetic assumptions of Illumina genotyping data, processing and quality control (QC) of these data remain a challenge. Thorough QC ensures the accurate identification of single-nucleotide polymorphisms and is required for the correct interpretation of genetic association results. By processing genotyping data on > 100 000 subjects from >10 major Illumina genotyping arrays, we have accumulated extensive experience in handling some of the most peculiar scenarios related to the processing and QC of Illumina genotyping data. Here, we describe strategies for processing Illumina genotyping data from the raw data to an analysis ready format, and we elaborate on the necessary QC procedures required at each processing step. High-quality Illumina genotyping data sets can be obtained by following our detailed QC strategies.

MeSH Terms (17)

Algorithms Cluster Analysis Computational Biology Continental Population Groups Female Gene Frequency Genome-Wide Association Study Genotype Genotyping Techniques High-Throughput Nucleotide Sequencing Humans Male Models, Genetic Oligonucleotide Array Sequence Analysis Polymorphism, Single Nucleotide Quality Control Software

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