Cargando…
Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected
For genome-wide association studies in family-based designs, we propose a powerful two-stage testing strategy that can be applied in situations in which parent-offspring trio data are available and all offspring are affected with the trait or disease under study. In the first step of the testing str...
Autores principales: | , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2008
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2529406/ https://www.ncbi.nlm.nih.gov/pubmed/18802462 http://dx.doi.org/10.1371/journal.pgen.1000197 |
_version_ | 1782158927533703168 |
---|---|
author | Murphy, Amy Weiss, Scott T. Lange, Christoph |
author_facet | Murphy, Amy Weiss, Scott T. Lange, Christoph |
author_sort | Murphy, Amy |
collection | PubMed |
description | For genome-wide association studies in family-based designs, we propose a powerful two-stage testing strategy that can be applied in situations in which parent-offspring trio data are available and all offspring are affected with the trait or disease under study. In the first step of the testing strategy, we construct estimators of genetic effect size in the completely ascertained sample of affected offspring and their parents that are statistically independent of the family-based association/transmission disequilibrium tests (FBATs/TDTs) that are calculated in the second step of the testing strategy. For each marker, the genetic effect is estimated (without requiring an estimate of the SNP allele frequency) and the conditional power of the corresponding FBAT/TDT is computed. Based on the power estimates, a weighted Bonferroni procedure assigns an individually adjusted significance level to each SNP. In the second stage, the SNPs are tested with the FBAT/TDT statistic at the individually adjusted significance levels. Using simulation studies for scenarios with up to 1,000,000 SNPs, varying allele frequencies and genetic effect sizes, the power of the strategy is compared with standard methodology (e.g., FBATs/TDTs with Bonferroni correction). In all considered situations, the proposed testing strategy demonstrates substantial power increases over the standard approach, even when the true genetic model is unknown and must be selected based on the conditional power estimates. The practical relevance of our methodology is illustrated by an application to a genome-wide association study for childhood asthma, in which we detect two markers meeting genome-wide significance that would not have been detected using standard methodology. |
format | Text |
id | pubmed-2529406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25294062008-09-19 Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected Murphy, Amy Weiss, Scott T. Lange, Christoph PLoS Genet Research Article For genome-wide association studies in family-based designs, we propose a powerful two-stage testing strategy that can be applied in situations in which parent-offspring trio data are available and all offspring are affected with the trait or disease under study. In the first step of the testing strategy, we construct estimators of genetic effect size in the completely ascertained sample of affected offspring and their parents that are statistically independent of the family-based association/transmission disequilibrium tests (FBATs/TDTs) that are calculated in the second step of the testing strategy. For each marker, the genetic effect is estimated (without requiring an estimate of the SNP allele frequency) and the conditional power of the corresponding FBAT/TDT is computed. Based on the power estimates, a weighted Bonferroni procedure assigns an individually adjusted significance level to each SNP. In the second stage, the SNPs are tested with the FBAT/TDT statistic at the individually adjusted significance levels. Using simulation studies for scenarios with up to 1,000,000 SNPs, varying allele frequencies and genetic effect sizes, the power of the strategy is compared with standard methodology (e.g., FBATs/TDTs with Bonferroni correction). In all considered situations, the proposed testing strategy demonstrates substantial power increases over the standard approach, even when the true genetic model is unknown and must be selected based on the conditional power estimates. The practical relevance of our methodology is illustrated by an application to a genome-wide association study for childhood asthma, in which we detect two markers meeting genome-wide significance that would not have been detected using standard methodology. Public Library of Science 2008-09-19 /pmc/articles/PMC2529406/ /pubmed/18802462 http://dx.doi.org/10.1371/journal.pgen.1000197 Text en Murphy et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Murphy, Amy Weiss, Scott T. Lange, Christoph Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected |
title | Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected |
title_full | Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected |
title_fullStr | Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected |
title_full_unstemmed | Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected |
title_short | Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected |
title_sort | screening and replication using the same data set: testing strategies for family-based studies in which all probands are affected |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2529406/ https://www.ncbi.nlm.nih.gov/pubmed/18802462 http://dx.doi.org/10.1371/journal.pgen.1000197 |
work_keys_str_mv | AT murphyamy screeningandreplicationusingthesamedatasettestingstrategiesforfamilybasedstudiesinwhichallprobandsareaffected AT weissscottt screeningandreplicationusingthesamedatasettestingstrategiesforfamilybasedstudiesinwhichallprobandsareaffected AT langechristoph screeningandreplicationusingthesamedatasettestingstrategiesforfamilybasedstudiesinwhichallprobandsareaffected |