Robust identification of transcriptional regulatory networks using a gibbs sampler on outlier sum statistic

Jinghua Gu, Jianhua Xuan, Rebecca B. Riggins, Li Chen, Yue Wang, Robert Clarke

Research output: Contribution to journalArticle

Abstract

Motivation: Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive 'noise' in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context.Results: In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer.

Original languageEnglish (US)
Article numberbts296
Pages (from-to)1990-1997
Number of pages8
JournalBioinformatics
Volume28
Issue number15
DOIs
StatePublished - Aug 2012
Externally publishedYes

Fingerprint

Gibbs Sampler
Gene Regulatory Networks
Regulatory Networks
Outlier
Statistic
Genes
Cells
Statistics
Sampling
Transcription factors
Microarrays
Gene
Breast Cancer
Yeast
Target
Tumors
Signal to noise ratio
Estrogens
Transcription Factors
Topology

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

Robust identification of transcriptional regulatory networks using a gibbs sampler on outlier sum statistic. / Gu, Jinghua; Xuan, Jianhua; Riggins, Rebecca B.; Chen, Li; Wang, Yue; Clarke, Robert.

In: Bioinformatics, Vol. 28, No. 15, bts296, 08.2012, p. 1990-1997.

Research output: Contribution to journalArticle

Gu, Jinghua ; Xuan, Jianhua ; Riggins, Rebecca B. ; Chen, Li ; Wang, Yue ; Clarke, Robert. / Robust identification of transcriptional regulatory networks using a gibbs sampler on outlier sum statistic. In: Bioinformatics. 2012 ; Vol. 28, No. 15. pp. 1990-1997.
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