A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data

We present CSDeconv, a computational method that determines locations of transcription factor binding from ChIP-seq data. CSDeconv differs from prior methods in that it uses a blind deconvolution approach that allows closely-spaced binding sites to be called accurately. We apply CSDeconv to novel Ch...

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Detalles Bibliográficos
Autores principales: Lun, Desmond S, Sherrid, Ashley, Weiner, Brian, Sherman, David R, Galagan, James E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2812949/
https://www.ncbi.nlm.nih.gov/pubmed/20028542
http://dx.doi.org/10.1186/gb-2009-10-12-r142
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author Lun, Desmond S
Sherrid, Ashley
Weiner, Brian
Sherman, David R
Galagan, James E
author_facet Lun, Desmond S
Sherrid, Ashley
Weiner, Brian
Sherman, David R
Galagan, James E
author_sort Lun, Desmond S
collection PubMed
description We present CSDeconv, a computational method that determines locations of transcription factor binding from ChIP-seq data. CSDeconv differs from prior methods in that it uses a blind deconvolution approach that allows closely-spaced binding sites to be called accurately. We apply CSDeconv to novel ChIP-seq data for DosR binding in Mycobacterium tuberculosis and to existing data for GABP in humans and show that it can discriminate binding sites separated by as few as 40 bp.
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spelling pubmed-28129492010-01-29 A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data Lun, Desmond S Sherrid, Ashley Weiner, Brian Sherman, David R Galagan, James E Genome Biol Method We present CSDeconv, a computational method that determines locations of transcription factor binding from ChIP-seq data. CSDeconv differs from prior methods in that it uses a blind deconvolution approach that allows closely-spaced binding sites to be called accurately. We apply CSDeconv to novel ChIP-seq data for DosR binding in Mycobacterium tuberculosis and to existing data for GABP in humans and show that it can discriminate binding sites separated by as few as 40 bp. BioMed Central 2009 2009-12-22 /pmc/articles/PMC2812949/ /pubmed/20028542 http://dx.doi.org/10.1186/gb-2009-10-12-r142 Text en Copyright ©2009 Lun 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 Method
Lun, Desmond S
Sherrid, Ashley
Weiner, Brian
Sherman, David R
Galagan, James E
A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data
title A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data
title_full A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data
title_fullStr A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data
title_full_unstemmed A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data
title_short A blind deconvolution approach to high-resolution mapping of transcription factor binding sites from ChIP-seq data
title_sort blind deconvolution approach to high-resolution mapping of transcription factor binding sites from chip-seq data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2812949/
https://www.ncbi.nlm.nih.gov/pubmed/20028542
http://dx.doi.org/10.1186/gb-2009-10-12-r142
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