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| Content Provider | PubMed Central |
|---|---|
| Author | Bailey, Julia N. |
| Copyright Year | 2005 |
| Abstract | The purpose of these analyses was to determine if incorporating or adjusting for covariates in genetic analyses helped or hindered in genetic analyses, specifically heritability and linkage analyses. To study this question, two types of covariate models were used in the simulated Genetic Analysis Workshop 14 dataset in which the true gene locations are known. All four populations of one replicate were combined for the analyses. The first model included typical covariates of sex and cohort (population) and the second included the typical covariates and also those related endophenotypes that are thought to be associated with the trait (phenotypes A, B, C, D, E, F, G, H, I, J, K, and L). A final best fit model produced in the heritability analyses was used for linkage. Linkage for disease genes D1, D3, and D4 were localized using models with and without the covariates. The use of inclusion of covariates did not appear to have any consistent advantage or disadvantage for the different phenotypes in regards to gene localization or false positive rate. |
| Related Links | http://dx.doi.org/10.1186/1471-2156-6-S1-S49 |
| Starting Page | 49 |
| File Format | |
| ISSN | 14712156 |
| e-ISSN | 14712156 |
| Journal | BMC Genetics |
| Issue Number | Suppl 1 |
| Volume Number | 6 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2005-12-30 |
| Access Restriction | Open |
| Rights Holder | BioMed Central |
| Subject Keyword | Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Genetics Genetics (clinical) |
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