LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present
<p>Abstract</p> <p>Background</p> <p>In the field of statistical genetics, phenotype and genotype misclassification errors can substantially reduce power to detect association with genetic case/control studies. Misclassification also can bias population frequency parame...
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| Format: | Article |
| Language: | English |
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BMC
2006-04-01
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| Series: | BMC Genetics |
| Online Access: | http://www.biomedcentral.com/1471-2156/7/24 |
| _version_ | 1811234198385590272 |
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| author | Stone Millicent Haynes Chad Barral Sandra Gordon Derek |
| author_facet | Stone Millicent Haynes Chad Barral Sandra Gordon Derek |
| author_sort | Stone Millicent |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>In the field of statistical genetics, phenotype and genotype misclassification errors can substantially reduce power to detect association with genetic case/control studies. Misclassification also can bias population frequency parameters such as genotype, haplotype, or multi-locus genotype frequencies. These problems are of particular concern in case/control designs because, short of repeated sampling, there is no way to detect misclassification errors.</p> <p>We developed a double-sampling procedure for case/control genetic association using a likelihood ratio test framework. Different approaches have been proposed to deal with misclassification errors. We have chosen the likelihood framework because of the ease with which misclassification probabilities may be incorporated into in the statistical framework and hypothesis testing. The statistic is called the Likelihood Ratio Test allowing for errors (LRTae) and is freely available via software download.</p> <p>Results</p> <p>We applied our procedure to 10,000 replicates of simulated case/control data in which we introduced phenotype misclassification errors. The phenotype considered is Ankylosing Spondylitis (AS). The LRTae method power was always greater than LRTstd power for the significance levels considered (5%, 1%, 0.1%, 0.01%). Power gains for the LRTae method over the LRTstd method increased as the significance level became more stringent. Multi-locus genotype frequency estimates using LRTae method were more accurate than estimates using LRTstd method.</p> <p>Conclusion</p> <p>The LRTae method can be applied to single-locus genotypes, multi-locus genotypes, or multi-locus haplotypes in a case/control framework and can be more powerful to detect association in case/control studies when both genotype and/or phenotype errors are present. Furthermore, the LRTae method provides asymptotically unbiased estimates of case and control genotype frequencies, as well as estimates of phenotype and/or genotype misclassification rates.</p> |
| first_indexed | 2024-04-12T11:32:37Z |
| format | Article |
| id | doaj.art-ef7d3748c3f5446284eff83e00757d81 |
| institution | Directory Open Access Journal |
| issn | 1471-2156 |
| language | English |
| last_indexed | 2024-04-12T11:32:37Z |
| publishDate | 2006-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genetics |
| spelling | doaj.art-ef7d3748c3f5446284eff83e00757d812022-12-22T03:34:59ZengBMCBMC Genetics1471-21562006-04-01712410.1186/1471-2156-7-24LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are presentStone MillicentHaynes ChadBarral SandraGordon Derek<p>Abstract</p> <p>Background</p> <p>In the field of statistical genetics, phenotype and genotype misclassification errors can substantially reduce power to detect association with genetic case/control studies. Misclassification also can bias population frequency parameters such as genotype, haplotype, or multi-locus genotype frequencies. These problems are of particular concern in case/control designs because, short of repeated sampling, there is no way to detect misclassification errors.</p> <p>We developed a double-sampling procedure for case/control genetic association using a likelihood ratio test framework. Different approaches have been proposed to deal with misclassification errors. We have chosen the likelihood framework because of the ease with which misclassification probabilities may be incorporated into in the statistical framework and hypothesis testing. The statistic is called the Likelihood Ratio Test allowing for errors (LRTae) and is freely available via software download.</p> <p>Results</p> <p>We applied our procedure to 10,000 replicates of simulated case/control data in which we introduced phenotype misclassification errors. The phenotype considered is Ankylosing Spondylitis (AS). The LRTae method power was always greater than LRTstd power for the significance levels considered (5%, 1%, 0.1%, 0.01%). Power gains for the LRTae method over the LRTstd method increased as the significance level became more stringent. Multi-locus genotype frequency estimates using LRTae method were more accurate than estimates using LRTstd method.</p> <p>Conclusion</p> <p>The LRTae method can be applied to single-locus genotypes, multi-locus genotypes, or multi-locus haplotypes in a case/control framework and can be more powerful to detect association in case/control studies when both genotype and/or phenotype errors are present. Furthermore, the LRTae method provides asymptotically unbiased estimates of case and control genotype frequencies, as well as estimates of phenotype and/or genotype misclassification rates.</p>http://www.biomedcentral.com/1471-2156/7/24 |
| spellingShingle | Stone Millicent Haynes Chad Barral Sandra Gordon Derek LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present BMC Genetics |
| title | LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present |
| title_full | LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present |
| title_fullStr | LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present |
| title_full_unstemmed | LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present |
| title_short | LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present |
| title_sort | lrtae improving statistical power for genetic association with case control data when phenotype and or genotype misclassification errors are present |
| url | http://www.biomedcentral.com/1471-2156/7/24 |
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