%0 Journal Article %1 zhao2017strategies %A Zhao, Shilin %A Jing, Wang %A Samuels, David C %A Sheng, Quanghu %A Shyr, Yu %A Guo, Yan %D 2017 %J Briefings in Bioinformatics %K genotype_arrays genotyping methods statistics %N 5 %P 765-775 %R 10.1093/bib/bbx012 %T Strategies for processing and quality control of Illumina genotyping arrays %U https://doi.org/10.1093/bib/bbx012 %V 19 %X 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.

@article{zhao2017strategies, abstract = {{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.}}, added-at = {2020-03-19T04:36:02.000+0100}, author = {Zhao, Shilin and Jing, Wang and Samuels, David C and Sheng, Quanghu and Shyr, Yu and Guo, Yan}, biburl = {https://www.bibsonomy.org/bibtex/225a394b34af0ed2e158e44bb9e1dbc52/peter.ralph}, doi = {10.1093/bib/bbx012}, eprint = {https://academic.oup.com/bib/article-pdf/19/5/765/25861231/bbx012.pdf}, interhash = {7de969d8f41bfded0102a862dbdbb001}, intrahash = {25a394b34af0ed2e158e44bb9e1dbc52}, issn = {1477-4054}, journal = {Briefings in Bioinformatics}, keywords = {genotype_arrays genotyping methods statistics}, month = {02}, number = 5, pages = {765-775}, timestamp = {2020-03-19T04:36:02.000+0100}, title = {Strategies for processing and quality control of {Illumina} genotyping arrays}, url = {https://doi.org/10.1093/bib/bbx012}, volume = 19, year = 2017 }