publication . Article . 2009

Look who is calling: a comparison of genotype calling algorithms.

Maren Vens; Arne Schillert; Inke R König; Andreas Ziegler;
Open Access
  • Published: 01 Dec 2009 Journal: BMC Proceedings, volume 3, page S59 (issn: 1753-6561, Copyright policy)
  • Publisher: Springer Nature
Abstract
<p>Abstract</p> <p>In genome-wide association studies, high-level statistical analyses rely on the validity of the called genotypes, and different genotype calling algorithms (GCAs) have been proposed. We compared the GCAs Bayesian robust linear modeling using Mahalanobis distance (BRLMM), Chiamo++, and JAPL using the autosomal single-nucleotide polymorphisms (SNPs) from the 500 k Affymetrix Array Set data of the Framingham Heart Study as provided for the Genetic Analysis Workshop 16, Problem 2, and prepared standard quality control (sQC) for each algorithm. Using JAPL, most individuals were retained for the analysis. The lowest number of SNPs that successfully ...
Subjects
free text keywords: General Biochemistry, Genetics and Molecular Biology, General Medicine, Minor allele frequency, Genetic association, Linear model, Bayesian probability, Mahalanobis distance, Genotype, Concordance, Medicine, business.industry, business, Algorithm, Single-nucleotide polymorphism, Proceedings, R, Science, Q
Related Organizations
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)
,
NIH| Genetic Analysis of Common Diseases: An Evaluation
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM031575-22
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

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