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Assessing the impact of missing genotype data in rare variant association analysis
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 1012450
Author(s) Mägi, Reedik; Kumar, Ashish; Morris, Andrew P.
Author(s) at UniBasel Kumar, Ashish
Year 2011
Title Assessing the impact of missing genotype data in rare variant association analysis
Journal BMC Proceedings
Volume 5 Suppl 9
Number Suppl. 9
Pages / Article-Number S107
Abstract Human genome resequencing technologies are becoming ever more affordable and provide a valuable source of data about rare genetic variants in the human genome. Such rare variation may play an important role in explaining the missing heritability of complex human traits. We implement an existing method for analyzing rare variants by testing for association with the mutational load across genes. In this study, we make use of simulated data from the Genetic Analysis Workshop 17 to assess the power of this approach to detect association with simulated quantitative and dichotomous phenotypes and to evaluate the impact of missing genotypes on the power of the analysis. According to our results, the mutational load based rare variant analysis method is relatively robust to call-rate and is adequately powered for genome-wide association analysis.
Publisher BioMed Central
ISSN/ISBN 1753-6561
edoc-URL http://edoc.unibas.ch/46988/
Full Text on edoc No
Digital Object Identifier DOI 10.1186/1753-6561-5-S9-S107
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/22373025
ISI-Number MEDLINE:22373025
Document type (ISI) Journal Article
 
   

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