Integrative analysis of methylation and gene expression data in TCGA

Yihua Liu; Peng Qiu

doi:10.1109/GENSIPS.2012.6507712

Integrative analysis of methylation and gene expression data in TCGA

Yihua Liu, Peng Qiu

Bioinformatics & Computational Biology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

An integrative analysis of methylation and gene expression is performed using TCGA data for 997 samples from multiple cancer types. We use conditional mutual information to examine each gene separately, identify 798 genes whose expression are repressed by their methylation, and derive gene-specific thresholds to dichotomize their methylation data. For each methylation controlled gene, we evaluate its conditional correlation with other genes, and infer which other genes are its regulators or targets. The resulting set of regulator genes is much larger than that of target genes, and the set of regulator genes is highly enriched by transcription factors.

Original language	English (US)
Title of host publication	Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Pages	1-4
Number of pages	4
DOIs	https://doi.org/10.1109/GENSIPS.2012.6507712
State	Published - 2012
Event	2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 - Washington, DC, United States Duration: Dec 2 2012 → Dec 4 2012

Publication series

Name	Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)	2150-3001
ISSN (Electronic)	2150-301X

Other

Other	2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Country/Territory	United States
City	Washington, DC
Period	12/2/12 → 12/4/12

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology (miscellaneous)
Computational Theory and Mathematics
Signal Processing
Biomedical Engineering

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10.1109/GENSIPS.2012.6507712

Cite this

Integrative analysis of methylation and gene expression data in TCGA. / Liu, Yihua; Qiu, Peng.
Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012. 2012. p. 1-4 6507712 (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Liu, Y & Qiu, P 2012, Integrative analysis of methylation and gene expression data in TCGA. in Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012., 6507712, Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics, pp. 1-4, 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012, Washington, DC, United States, 12/2/12. https://doi.org/10.1109/GENSIPS.2012.6507712

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title = "Integrative analysis of methylation and gene expression data in TCGA",

abstract = "An integrative analysis of methylation and gene expression is performed using TCGA data for 997 samples from multiple cancer types. We use conditional mutual information to examine each gene separately, identify 798 genes whose expression are repressed by their methylation, and derive gene-specific thresholds to dichotomize their methylation data. For each methylation controlled gene, we evaluate its conditional correlation with other genes, and infer which other genes are its regulators or targets. The resulting set of regulator genes is much larger than that of target genes, and the set of regulator genes is highly enriched by transcription factors.",

author = "Yihua Liu and Peng Qiu",

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AB - An integrative analysis of methylation and gene expression is performed using TCGA data for 997 samples from multiple cancer types. We use conditional mutual information to examine each gene separately, identify 798 genes whose expression are repressed by their methylation, and derive gene-specific thresholds to dichotomize their methylation data. For each methylation controlled gene, we evaluate its conditional correlation with other genes, and infer which other genes are its regulators or targets. The resulting set of regulator genes is much larger than that of target genes, and the set of regulator genes is highly enriched by transcription factors.

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Integrative analysis of methylation and gene expression data in TCGA

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