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Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists

BACKGROUND: In DNA microarray gene expression profiling studies, a fundamental task is to extract statistically significant genes that meet certain research hypothesis. Currently, Venn diagram is a frequently used method for identifying overlapping genes that meet the investigator's research hy...

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Detalles Bibliográficos
Autores principales: Deng, Xutao, Xu, Jun, Wang, Charles
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2423437/
https://www.ncbi.nlm.nih.gov/pubmed/18541049
http://dx.doi.org/10.1186/1471-2105-9-S6-S14
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author Deng, Xutao
Xu, Jun
Wang, Charles
author_facet Deng, Xutao
Xu, Jun
Wang, Charles
author_sort Deng, Xutao
collection PubMed
description BACKGROUND: In DNA microarray gene expression profiling studies, a fundamental task is to extract statistically significant genes that meet certain research hypothesis. Currently, Venn diagram is a frequently used method for identifying overlapping genes that meet the investigator's research hypotheses. However this simple operation of intersecting multiple gene lists, known as the Intersection-Union Tests (IUTs), is performed without knowing the incurred changes in Type 1 error rate and can lead to loss of discovery power. RESULTS: We developed an IUT adjustment procedure, called Relaxed IUT (RIUT), which is proved to be less conservative and more powerful for intersecting independent tests than the traditional Venn diagram approach. The advantage of the RIUT procedure over traditional IUT is demonstrated by empirical Monte-Carlo simulation and two real toxicogenomic gene expression case studies. Notably, the enhanced power of RIUT enables it to identify overlapping gene sets leading to identification of certain known related pathways which were not detected using the traditional IUT method. CONCLUSION: We showed that traditional IUT via a Venn diagram is generally conservative, which may lead to loss discovery power in DNA microarray studies. RIUT is proved to be a more powerful alternative for performing IUTs in identifying overlapping genes from multiple gene lists derived from microarray gene expression profiling.
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spelling pubmed-24234372008-06-11 Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists Deng, Xutao Xu, Jun Wang, Charles BMC Bioinformatics Research BACKGROUND: In DNA microarray gene expression profiling studies, a fundamental task is to extract statistically significant genes that meet certain research hypothesis. Currently, Venn diagram is a frequently used method for identifying overlapping genes that meet the investigator's research hypotheses. However this simple operation of intersecting multiple gene lists, known as the Intersection-Union Tests (IUTs), is performed without knowing the incurred changes in Type 1 error rate and can lead to loss of discovery power. RESULTS: We developed an IUT adjustment procedure, called Relaxed IUT (RIUT), which is proved to be less conservative and more powerful for intersecting independent tests than the traditional Venn diagram approach. The advantage of the RIUT procedure over traditional IUT is demonstrated by empirical Monte-Carlo simulation and two real toxicogenomic gene expression case studies. Notably, the enhanced power of RIUT enables it to identify overlapping gene sets leading to identification of certain known related pathways which were not detected using the traditional IUT method. CONCLUSION: We showed that traditional IUT via a Venn diagram is generally conservative, which may lead to loss discovery power in DNA microarray studies. RIUT is proved to be a more powerful alternative for performing IUTs in identifying overlapping genes from multiple gene lists derived from microarray gene expression profiling. BioMed Central 2008-05-28 /pmc/articles/PMC2423437/ /pubmed/18541049 http://dx.doi.org/10.1186/1471-2105-9-S6-S14 Text en Copyright © 2008 Deng 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 Research
Deng, Xutao
Xu, Jun
Wang, Charles
Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
title Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
title_full Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
title_fullStr Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
title_full_unstemmed Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
title_short Improving the power for detecting overlapping genes from multiple DNA microarray-derived gene lists
title_sort improving the power for detecting overlapping genes from multiple dna microarray-derived gene lists
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2423437/
https://www.ncbi.nlm.nih.gov/pubmed/18541049
http://dx.doi.org/10.1186/1471-2105-9-S6-S14
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