Statistical significance of cis-regulatory modules

Schones, D. E., Smith, A. D., Zhang, M. Q. (January 2007) Statistical significance of cis-regulatory modules. Bmc Bioinformatics, 8. p. 16. ISSN 1471-2105

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URL: https://www.ncbi.nlm.nih.gov/pubmed/17241466
DOI: 10.1186/1471-2105-8-19

Abstract

Background: It is becoming increasingly important for researchers to be able to scan through large genomic regions for transcription factor binding sites or clusters of binding sites forming cis-regulatory modules. Correspondingly, there has been a push to develop algorithms for the rapid detection and assessment of cis-regulatory modules. While various algorithms for this purpose have been introduced, most are not well suited for rapid, genome scale scanning. Results: We introduce methods designed for the detection and statistical evaluation of cis-regulatory modules, modeled as either clusters of individual binding sites or as combinations of sites with constrained organization. In order to determine the statistical significance of module sites, we first need a method to determine the statistical significance of single transcription factor binding site matches. We introduce a straightforward method of estimating the statistical significance of single site matches using a database of known promoters to produce data structures that can be used to estimate p-values for binding site matches. We next introduce a technique to calculate the statistical significance of the arrangement of binding sites within a module using a max-gap model. If the module scanned for has defined organizational parameters, the probability of the module is corrected to account for organizational constraints. The statistical significance of single site matches and the architecture of sites within the module can be combined to provide an overall estimation of statistical significance of cis-regulatory module sites. Conclusion: The methods introduced in this paper allow for the detection and statistical evaluation of single transcription factor binding sites and cis-regulatory modules. The features described are implemented in the Search Tool for Occurrences of Regulatory Motifs (STORM) and MODSTORM software.

Item Type: Paper
Uncontrolled Keywords: DE-NOVO DISCOVERY GENE-EXPRESSION DROSOPHILA-PSEUDOOBSCURA NUCLEOTIDE-SEQUENCES BINDING-SITES IDENTIFICATION CLUSTERS PREDICTION GENOME MELANOGASTER
Subjects: organism description > animal > insect > Drosophila
bioinformatics > computational biology
bioinformatics > genomics and proteomics > computers > computer software
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > transcription factor
CSHL Authors:
Communities: CSHL labs > Zhang lab
Depositing User: CSHL Librarian
Date: January 2007
Date Deposited: 03 Nov 2011 16:16
Last Modified: 09 Apr 2018 20:18
PMCID: PMC1796902
Related URLs:
URI: http://repository.cshl.edu/id/eprint/23132

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