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motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites

Summary: Functional annotation represents a key step toward the understanding and interpretation of germline and somatic variation as revealed by genome-wide association studies (GWAS) and The Cancer Genome Atlas (TCGA), respectively. GWAS have revealed numerous genetic risk variants residing in non...

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Autores principales: Coetzee, Simon G., Coetzee, Gerhard A., Hazelett, Dennis J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653394/
https://www.ncbi.nlm.nih.gov/pubmed/26272984
http://dx.doi.org/10.1093/bioinformatics/btv470
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author Coetzee, Simon G.
Coetzee, Gerhard A.
Hazelett, Dennis J.
author_facet Coetzee, Simon G.
Coetzee, Gerhard A.
Hazelett, Dennis J.
author_sort Coetzee, Simon G.
collection PubMed
description Summary: Functional annotation represents a key step toward the understanding and interpretation of germline and somatic variation as revealed by genome-wide association studies (GWAS) and The Cancer Genome Atlas (TCGA), respectively. GWAS have revealed numerous genetic risk variants residing in non-coding DNA associated with complex diseases. For sequences that lie within enhancers or promoters of transcription, it is not straightforward to assess the effects of variants on likely transcription factor binding sites. Consequently we introduce motifbreakR, which allows the biologist to judge whether the sequence surrounding a polymorphism or mutation is a good match, and how much information is gained or lost in one allele of the polymorphism or mutation relative to the other. MotifbreakR is flexible, giving a choice of algorithms for interrogation of genomes with motifs from many public sources that users can choose from. MotifbreakR can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within bioconductor. Availability and implementation: https://github.com/Simon-Coetzee/MotifBreakR, www.bioconductor.org. Contact: dennis.hazelett@cshs.org
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spelling pubmed-46533942015-11-20 motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites Coetzee, Simon G. Coetzee, Gerhard A. Hazelett, Dennis J. Bioinformatics Applications Notes Summary: Functional annotation represents a key step toward the understanding and interpretation of germline and somatic variation as revealed by genome-wide association studies (GWAS) and The Cancer Genome Atlas (TCGA), respectively. GWAS have revealed numerous genetic risk variants residing in non-coding DNA associated with complex diseases. For sequences that lie within enhancers or promoters of transcription, it is not straightforward to assess the effects of variants on likely transcription factor binding sites. Consequently we introduce motifbreakR, which allows the biologist to judge whether the sequence surrounding a polymorphism or mutation is a good match, and how much information is gained or lost in one allele of the polymorphism or mutation relative to the other. MotifbreakR is flexible, giving a choice of algorithms for interrogation of genomes with motifs from many public sources that users can choose from. MotifbreakR can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within bioconductor. Availability and implementation: https://github.com/Simon-Coetzee/MotifBreakR, www.bioconductor.org. Contact: dennis.hazelett@cshs.org Oxford University Press 2015-12-01 2015-08-12 /pmc/articles/PMC4653394/ /pubmed/26272984 http://dx.doi.org/10.1093/bioinformatics/btv470 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Coetzee, Simon G.
Coetzee, Gerhard A.
Hazelett, Dennis J.
motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites
title motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites
title_full motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites
title_fullStr motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites
title_full_unstemmed motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites
title_short motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites
title_sort motifbreakr: an r/bioconductor package for predicting variant effects at transcription factor binding sites
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653394/
https://www.ncbi.nlm.nih.gov/pubmed/26272984
http://dx.doi.org/10.1093/bioinformatics/btv470
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