A new approach to identify functional modules using random matrix theory

Mengxia Zhu, Qishi Wu, Yunfeng Yang, Jizhong Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The advance in high-throughput genomic technologies including microarrays has generated a tremendous amount of gene expression data for the entire genome. Deciphering transcriptional networks that convey information on members of gene clusters and cluster interactions is a crucial analysis task in the post-sequence era. Most of the existing analysis methods for large-scale genome-wide gene expression profiles involve several steps that often require human intervention. We propose a random matrix theory-based approach to analyze the cross correlations of gene expression data in an entirely automatic and objective manner to eliminate the ambiguities and subjectivity inherent to human decisions. The correlations calculated from experimental measurements typically contain both "genuine" and "random" components. In the proposed approach, we remove the "random" component by testing the statistics of the eigenvalues of the correlation matrix against a "null hypothesis" - a truly random correlation matrix obtained from mutually uncorrelated expression data series. Our investigation on the components of deviating eigenvectors using varimax orthogonal rotation reveals distinct functional modules. We apply the proposed approach to the publicly available yeast cycle expression data and produce a transcriptional network that consists of interacting functional modules. The experimental results nicely conform to those obtained in previously published literatures.

Original languageEnglish
Title of host publicationProceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06
Pages117-123
Number of pages7
DOIs
StatePublished - 1 Dec 2006
Event3rd Computational Intelligence in Bioinformatics and Computational Biology Symposium, CIBCB - Toronto, ON, Canada
Duration: 28 Sep 200629 Sep 2006

Publication series

NameProceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06

Other

Other3rd Computational Intelligence in Bioinformatics and Computational Biology Symposium, CIBCB
CountryCanada
CityToronto, ON
Period28/09/0629/09/06

Fingerprint

Random Matrix Theory
Gene expression
Genes
Correlation Matrix
Gene Expression Data
Module
Genome
Gene Expression Profile
Microarrays
Cross-correlation
Random Matrices
Null hypothesis
Microarray
Eigenvalues and eigenfunctions
Yeast
Eigenvector
High Throughput
Genomics
Eliminate
Throughput

Keywords

  • Eigenvalue
  • Eigenvector
  • Microarray
  • Pearson correlation
  • Random Matrix
  • Varimax orthogonal rotation

Cite this

Zhu, M., Wu, Q., Yang, Y., & Zhou, J. (2006). A new approach to identify functional modules using random matrix theory. In Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06 (pp. 117-123). [4133162] (Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06). https://doi.org/10.1109/CIBCB.2006.330980
Zhu, Mengxia ; Wu, Qishi ; Yang, Yunfeng ; Zhou, Jizhong. / A new approach to identify functional modules using random matrix theory. Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06. 2006. pp. 117-123 (Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06).
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Zhu, M, Wu, Q, Yang, Y & Zhou, J 2006, A new approach to identify functional modules using random matrix theory. in Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06., 4133162, Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06, pp. 117-123, 3rd Computational Intelligence in Bioinformatics and Computational Biology Symposium, CIBCB, Toronto, ON, Canada, 28/09/06. https://doi.org/10.1109/CIBCB.2006.330980

A new approach to identify functional modules using random matrix theory. / Zhu, Mengxia; Wu, Qishi; Yang, Yunfeng; Zhou, Jizhong.

Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06. 2006. p. 117-123 4133162 (Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Zhu M, Wu Q, Yang Y, Zhou J. A new approach to identify functional modules using random matrix theory. In Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06. 2006. p. 117-123. 4133162. (Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06). https://doi.org/10.1109/CIBCB.2006.330980