Linked Life Data

20018042

Source:http://linkedlifedata.com/resource/pubmed/id/20018042

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-12-18
pubmed:abstractText
ABSTRACT : Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-control dataset to compare the performance of four of these imputation methods: IMPUTE, MACH, PLINK, and fastPHASE. We compared the methods' imputation error rates and performance of association tests using the imputed data, in the context of imputing completely untyped markers as well as imputing missing genotypes to combine two datasets genotyped at different sets of markers. As expected, all methods performed better for single-nucleotide polymorphisms (SNPs) in high linkage disequilibrium with genotyped SNPs. However, MACH and IMPUTE generated lower imputation error rates than fastPHASE and PLINK. Association tests based on allele "dosage" from MACH and tests based on the posterior probabilities from IMPUTE provided results closest to those based on complete data. However, in both situations, none of the imputation-based tests provide the same level of evidence of association as the complete data at SNPs strongly associated with disease.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-14557050, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-15208781, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-16175503, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-16380915, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-16532393, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-16986160, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-17572673, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-17676998, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-17701901, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-18958166, http://linkedlifedata.com/resource/pubmed/commentcorrection/20018042-19089453
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:issn
1753-6561
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
3 Suppl 7
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S5
pubmed:year
2009
pubmed:articleTitle
Assessment of genotype imputation methods.
pubmed:affiliation
Department of Health Sciences Research, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905 USA. biernacka.joanna@mayo.edu.
pubmed:publicationType
Journal Article