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Mining gene networks with application to GAW15 Problem 1

The Genetic Analysis Workshop 15 (GAW15) Problem 1 contained baseline expression levels of 8793 genes in immortalized B cells from 194 individuals in 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees. Previous analysis of the data showed linkage and association and evidence of sub...

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Detalles Bibliográficos
Autores principales: Zhao, Jing Hua, Luan, Jian'an, Baksh, M Fazil, Tan, Qihua
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367510/
https://www.ncbi.nlm.nih.gov/pubmed/18466552
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author Zhao, Jing Hua
Luan, Jian'an
Baksh, M Fazil
Tan, Qihua
author_facet Zhao, Jing Hua
Luan, Jian'an
Baksh, M Fazil
Tan, Qihua
author_sort Zhao, Jing Hua
collection PubMed
description The Genetic Analysis Workshop 15 (GAW15) Problem 1 contained baseline expression levels of 8793 genes in immortalized B cells from 194 individuals in 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees. Previous analysis of the data showed linkage and association and evidence of substantial individual variations. In particular, correlation was examined on expression levels of 31 genes and 25 target genes corresponding to two master regulatory regions. In this analysis, we apply Bayesian network analysis to gain further insight into these findings. We identify strong dependences and therefore provide additional insight into the underlying relationships between the genes involved. More generally, the approach is expected to be applicable for integrated analysis of genes on biological pathways.
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spelling pubmed-23675102008-05-06 Mining gene networks with application to GAW15 Problem 1 Zhao, Jing Hua Luan, Jian'an Baksh, M Fazil Tan, Qihua BMC Proc Proceedings The Genetic Analysis Workshop 15 (GAW15) Problem 1 contained baseline expression levels of 8793 genes in immortalized B cells from 194 individuals in 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees. Previous analysis of the data showed linkage and association and evidence of substantial individual variations. In particular, correlation was examined on expression levels of 31 genes and 25 target genes corresponding to two master regulatory regions. In this analysis, we apply Bayesian network analysis to gain further insight into these findings. We identify strong dependences and therefore provide additional insight into the underlying relationships between the genes involved. More generally, the approach is expected to be applicable for integrated analysis of genes on biological pathways. BioMed Central 2007-12-18 /pmc/articles/PMC2367510/ /pubmed/18466552 Text en Copyright © 2007 Zhao 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
Zhao, Jing Hua
Luan, Jian'an
Baksh, M Fazil
Tan, Qihua
Mining gene networks with application to GAW15 Problem 1
title Mining gene networks with application to GAW15 Problem 1
title_full Mining gene networks with application to GAW15 Problem 1
title_fullStr Mining gene networks with application to GAW15 Problem 1
title_full_unstemmed Mining gene networks with application to GAW15 Problem 1
title_short Mining gene networks with application to GAW15 Problem 1
title_sort mining gene networks with application to gaw15 problem 1
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367510/
https://www.ncbi.nlm.nih.gov/pubmed/18466552
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