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Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies
Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, stud...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053820/ https://www.ncbi.nlm.nih.gov/pubmed/24708878 http://dx.doi.org/10.1186/gb-2014-15-4-r61 |
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author | J Joo, Jong Wha Sul, Jae Hoon Han, Buhm Ye, Chun Eskin, Eleazar |
author_facet | J Joo, Jong Wha Sul, Jae Hoon Han, Buhm Ye, Chun Eskin, Eleazar |
author_sort | J Joo, Jong Wha |
collection | PubMed |
description | Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. |
format | Online Article Text |
id | pubmed-4053820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40538202014-06-12 Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies J Joo, Jong Wha Sul, Jae Hoon Han, Buhm Ye, Chun Eskin, Eleazar Genome Biol Method Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. BioMed Central 2014 2014-04-07 /pmc/articles/PMC4053820/ /pubmed/24708878 http://dx.doi.org/10.1186/gb-2014-15-4-r61 Text en Copyright © 2014 Joo 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 | Method J Joo, Jong Wha Sul, Jae Hoon Han, Buhm Ye, Chun Eskin, Eleazar Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies |
title | Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies |
title_full | Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies |
title_fullStr | Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies |
title_full_unstemmed | Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies |
title_short | Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies |
title_sort | effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053820/ https://www.ncbi.nlm.nih.gov/pubmed/24708878 http://dx.doi.org/10.1186/gb-2014-15-4-r61 |
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