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iFORM: Incorporating Find Occurrence of Regulatory Motifs
Accurately identifying the binding sites of transcription factors (TFs) is crucial to understanding the mechanisms of transcriptional regulation and human disease. We present incorporating Find Occurrence of Regulatory Motifs (iFORM), an easy-to-use and efficient tool for scanning DNA sequences with...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5167396/ https://www.ncbi.nlm.nih.gov/pubmed/27992540 http://dx.doi.org/10.1371/journal.pone.0168607 |
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author | Ren, Chao Chen, Hebing Yang, Bite Liu, Feng Ouyang, Zhangyi Bo, Xiaochen Shu, Wenjie |
author_facet | Ren, Chao Chen, Hebing Yang, Bite Liu, Feng Ouyang, Zhangyi Bo, Xiaochen Shu, Wenjie |
author_sort | Ren, Chao |
collection | PubMed |
description | Accurately identifying the binding sites of transcription factors (TFs) is crucial to understanding the mechanisms of transcriptional regulation and human disease. We present incorporating Find Occurrence of Regulatory Motifs (iFORM), an easy-to-use and efficient tool for scanning DNA sequences with TF motifs described as position weight matrices (PWMs). Both performance assessment with a receiver operating characteristic (ROC) curve and a correlation-based approach demonstrated that iFORM achieves higher accuracy and sensitivity by integrating five classical motif discovery programs using Fisher’s combined probability test. We have used iFORM to provide accurate results on a variety of data in the ENCODE Project and the NIH Roadmap Epigenomics Project, and the tool has demonstrated its utility in further elucidating individual roles of functional elements. Both the source and binary codes for iFORM can be freely accessed at https://github.com/wenjiegroup/iFORM. The identified TF binding sites across human cell and tissue types using iFORM have been deposited in the Gene Expression Omnibus under the accession ID GSE53962. |
format | Online Article Text |
id | pubmed-5167396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-51673962017-01-04 iFORM: Incorporating Find Occurrence of Regulatory Motifs Ren, Chao Chen, Hebing Yang, Bite Liu, Feng Ouyang, Zhangyi Bo, Xiaochen Shu, Wenjie PLoS One Research Article Accurately identifying the binding sites of transcription factors (TFs) is crucial to understanding the mechanisms of transcriptional regulation and human disease. We present incorporating Find Occurrence of Regulatory Motifs (iFORM), an easy-to-use and efficient tool for scanning DNA sequences with TF motifs described as position weight matrices (PWMs). Both performance assessment with a receiver operating characteristic (ROC) curve and a correlation-based approach demonstrated that iFORM achieves higher accuracy and sensitivity by integrating five classical motif discovery programs using Fisher’s combined probability test. We have used iFORM to provide accurate results on a variety of data in the ENCODE Project and the NIH Roadmap Epigenomics Project, and the tool has demonstrated its utility in further elucidating individual roles of functional elements. Both the source and binary codes for iFORM can be freely accessed at https://github.com/wenjiegroup/iFORM. The identified TF binding sites across human cell and tissue types using iFORM have been deposited in the Gene Expression Omnibus under the accession ID GSE53962. Public Library of Science 2016-12-19 /pmc/articles/PMC5167396/ /pubmed/27992540 http://dx.doi.org/10.1371/journal.pone.0168607 Text en © 2016 Ren et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Ren, Chao Chen, Hebing Yang, Bite Liu, Feng Ouyang, Zhangyi Bo, Xiaochen Shu, Wenjie iFORM: Incorporating Find Occurrence of Regulatory Motifs |
title | iFORM: Incorporating Find Occurrence of Regulatory Motifs |
title_full | iFORM: Incorporating Find Occurrence of Regulatory Motifs |
title_fullStr | iFORM: Incorporating Find Occurrence of Regulatory Motifs |
title_full_unstemmed | iFORM: Incorporating Find Occurrence of Regulatory Motifs |
title_short | iFORM: Incorporating Find Occurrence of Regulatory Motifs |
title_sort | iform: incorporating find occurrence of regulatory motifs |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5167396/ https://www.ncbi.nlm.nih.gov/pubmed/27992540 http://dx.doi.org/10.1371/journal.pone.0168607 |
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