| GEL: a novel genotype calling algorithm using empirical likelihood. | |
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MedLine Citation:
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PMID: 16809396 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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MOTIVATION: Preliminary results on the data produced using the Affymetrix large-scale genotyping platforms show that it is necessary to construct improved genotype calling algorithms. There is evidence that some of the existing algorithms lead to an increased error rate in heterozygous genotypes, and a disproportionately large rate of heterozygotes with missing genotypes. Non-random errors and missing data can lead to an increase in the number of false discoveries in genetic association studies. Therefore, the factors that need to be evaluated in assessing the performance of an algorithm are the missing data (call) and error rates, but also the heterozygous proportions in missing data and errors. RESULTS: We introduce a novel genotype calling algorithm (GEL) for the Affymetrix GeneChip arrays. The algorithm uses likelihood calculations that are based on distributions inferred from the observed data. A key ingredient in accurate genotype calling is weighting the information that comes from each probe quartet according to the quality/reliability of the data in the quartet, and prior information on the performance of the quartet. AVAILABILITY: The GEL software is implemented in R and is available by request from the corresponding author at nicolae@galton.uchicago.edu. |
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Authors:
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Dan L Nicolae; Xiaolin Wu; Kazuaki Miyake; Nancy J Cox |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't Date: 2006-06-29 |
Journal Detail:
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Title: Bioinformatics (Oxford, England) Volume: 22 ISSN: 1367-4811 ISO Abbreviation: Bioinformatics Publication Date: 2006 Aug |
Date Detail:
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Created Date: 2006-08-10 Completed Date: 2006-09-28 Revised Date: 2009-11-04 |
Medline Journal Info:
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Nlm Unique ID: 9808944 Medline TA: Bioinformatics Country: England |
Other Details:
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Languages: eng Pagination: 1942-7 Citation Subset: IM |
Affiliation:
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Department of Statistics, The University of Chicago. nicolae@galton.uchicago.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Computational Biology / methods* Genotype* Likelihood Functions Oligonucleotide Array Sequence Analysis Programming Languages Reproducibility of Results Software |
| Grant Support | |
ID/Acronym/Agency:
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DK-20595/DK/NIDDK NIH HHS; DK-47486/DK/NIDDK NIH HHS; DK-55889/DK/NIDDK NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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