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Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data
BACKGROUND: The binding events of DNA-interacting proteins and their patterns can be extensively characterized by high density ChIP-chip tiling array data. The characteristics of the binding events could be different for different transcription factors. They may even vary for a given transcription f...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3090766/ https://www.ncbi.nlm.nih.gov/pubmed/21554766 http://dx.doi.org/10.1186/1753-6561-5-S2-S8 |
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author | Li, Juntao Zhu, Lei Eshaghi, Majid Liu, Jianhua Karuturi, Krishna Murthy R |
author_facet | Li, Juntao Zhu, Lei Eshaghi, Majid Liu, Jianhua Karuturi, Krishna Murthy R |
author_sort | Li, Juntao |
collection | PubMed |
description | BACKGROUND: The binding events of DNA-interacting proteins and their patterns can be extensively characterized by high density ChIP-chip tiling array data. The characteristics of the binding events could be different for different transcription factors. They may even vary for a given transcription factor among different interaction loci. The knowledge of binding sites and binding occupancy patterns are all very useful to understand the DNA-protein interaction and its role in the transcriptional regulation of genes. RESULTS: In the view of the complexity of the DNA-protein interaction and the opportunity offered by high density tiled ChIP-chip data, we present a statistical procedure which focuses on identifying the interaction signal regions instead of signal peaks using moving window binomial testing method and deconvolving the patterns of interaction using peakedness and skewness scores. We analyzed ChIP-chip data of 4 different DNA interacting proteins including transcription factors and RNA polymerase in fission yeast using our procedure. Our analysis revealed the variation of binding patterns within and across different DNA interacting proteins. We present their utility in understanding transcriptional regulation from ChIP-chip data. CONCLUSIONS: Our method can successfully detect the signal regions and characterize the binding patterns in ChIP-chip data which help appropriate analysis of the ChIP-chip data. |
format | Text |
id | pubmed-3090766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30907662011-05-28 Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data Li, Juntao Zhu, Lei Eshaghi, Majid Liu, Jianhua Karuturi, Krishna Murthy R BMC Proc Proceedings BACKGROUND: The binding events of DNA-interacting proteins and their patterns can be extensively characterized by high density ChIP-chip tiling array data. The characteristics of the binding events could be different for different transcription factors. They may even vary for a given transcription factor among different interaction loci. The knowledge of binding sites and binding occupancy patterns are all very useful to understand the DNA-protein interaction and its role in the transcriptional regulation of genes. RESULTS: In the view of the complexity of the DNA-protein interaction and the opportunity offered by high density tiled ChIP-chip data, we present a statistical procedure which focuses on identifying the interaction signal regions instead of signal peaks using moving window binomial testing method and deconvolving the patterns of interaction using peakedness and skewness scores. We analyzed ChIP-chip data of 4 different DNA interacting proteins including transcription factors and RNA polymerase in fission yeast using our procedure. Our analysis revealed the variation of binding patterns within and across different DNA interacting proteins. We present their utility in understanding transcriptional regulation from ChIP-chip data. CONCLUSIONS: Our method can successfully detect the signal regions and characterize the binding patterns in ChIP-chip data which help appropriate analysis of the ChIP-chip data. BioMed Central 2011-05-28 /pmc/articles/PMC3090766/ /pubmed/21554766 http://dx.doi.org/10.1186/1753-6561-5-S2-S8 Text en Copyright ©2011 Li et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Li, Juntao Zhu, Lei Eshaghi, Majid Liu, Jianhua Karuturi, Krishna Murthy R Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data |
title | Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data |
title_full | Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data |
title_fullStr | Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data |
title_full_unstemmed | Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data |
title_short | Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data |
title_sort | deciphering transcription factor binding patterns from genome-wide high density chip-chip tiling array data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3090766/ https://www.ncbi.nlm.nih.gov/pubmed/21554766 http://dx.doi.org/10.1186/1753-6561-5-S2-S8 |
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