ArticleBMC bioinformatics2007
Statistical significance of cis-regulatory modules.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
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- Implication of a new function of human tDNAs in chromatin organization.Scientific reports · 2020Article
- Peroxisome proliferator-activated receptor gamma controls prostate cancer cell growth through AR-dependent and independent mechanisms.The Prostate · 2020Article
- Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements.Nature communications · 2019Article
- Machine learning polymer models of three-dimensional chromatin organization in human lymphoblastoid cells.Methods (San Diego, Calif.) · 2019Article
- Spatial chromatin architecture alteration by structural variations in human genomes at the population scale.Genome biology · 2019Article
- Discovery of Allele-Specific Protein-RNA Interactions in Human Transcriptomes.American journal of human genetics · 2019Article
- Rbf Activates the Myogenic Transcriptional Program to Promote Skeletal Muscle Differentiation.Cell reports · 2019Article
- Polymer Simulations of Heteromorphic Chromatin Predict the 3D Folding of Complex Genomic Loci.Molecular cell · 2018Article
- Fast sequence analysis based on diamond sampling.PloS one · 2018Article
- Vertical sleeve gastrectomy reverses diet-induced gene-regulatory changes impacting lipid metabolism.Scientific reports · 2017Article
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Authors and funding
3 authors.
Funding
Abstract
backgroundIt 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.
resultsWe 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.
conclusionThe 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.
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