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Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping
In the fast-developing field of expression quantitative traits loci (eQTL) studies, much interest has been concentrated on detecting genomic regions containing transcriptional regulators that influence multiple expression phenotypes (trans-hubs). In this paper, we develop statistical methods for eQT...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367467/ https://www.ncbi.nlm.nih.gov/pubmed/18466502 |
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author | Peng, Jie Wang, Pei Tang, Hua |
author_facet | Peng, Jie Wang, Pei Tang, Hua |
author_sort | Peng, Jie |
collection | PubMed |
description | In the fast-developing field of expression quantitative traits loci (eQTL) studies, much interest has been concentrated on detecting genomic regions containing transcriptional regulators that influence multiple expression phenotypes (trans-hubs). In this paper, we develop statistical methods for eQTL mapping and propose a new procedure for investigating candidate trans-hubs. We use data from the Genetic Analysis Workshop 15 to illustrate our methods. After correlations among expressions were accounted for, the previously detected trans-hubs are no longer significant. Our results suggest that conclusions regarding regulation hot spots should be treated with great caution. |
format | Text |
id | pubmed-2367467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-23674672008-05-06 Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping Peng, Jie Wang, Pei Tang, Hua BMC Proc Proceedings In the fast-developing field of expression quantitative traits loci (eQTL) studies, much interest has been concentrated on detecting genomic regions containing transcriptional regulators that influence multiple expression phenotypes (trans-hubs). In this paper, we develop statistical methods for eQTL mapping and propose a new procedure for investigating candidate trans-hubs. We use data from the Genetic Analysis Workshop 15 to illustrate our methods. After correlations among expressions were accounted for, the previously detected trans-hubs are no longer significant. Our results suggest that conclusions regarding regulation hot spots should be treated with great caution. BioMed Central 2007-12-18 /pmc/articles/PMC2367467/ /pubmed/18466502 Text en Copyright © 2007 Peng et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Peng, Jie Wang, Pei Tang, Hua Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping |
title | Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping |
title_full | Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping |
title_fullStr | Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping |
title_full_unstemmed | Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping |
title_short | Controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping |
title_sort | controlling for false positive findings of trans-hubs in expression quantitative trait loci mapping |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367467/ https://www.ncbi.nlm.nih.gov/pubmed/18466502 |
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