Probabilistic inference for nucleosome positioning with MNase-based or sonicated short-read data.

Details

Serval ID
serval:BIB_2703A25EEC93
Type
Article: article from journal or magazin.
Collection
Publications
Title
Probabilistic inference for nucleosome positioning with MNase-based or sonicated short-read data.
Journal
PloS one
Author(s)
Zhang X., Robertson G., Woo S., Hoffman B.G., Gottardo R.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Publication state
Published
Issued date
2012
Peer-reviewed
Oui
Volume
7
Number
2
Pages
e32095
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
We describe a model-based method, PING, for predicting nucleosome positions in MNase-Seq and MNase- or sonicated-ChIP-Seq data. PING compares favorably to NPS and TemplateFilter in scalability, accuracy and robustness to low read density. To demonstrate that PING predictions from widely available sonicated data can have sufficient spatial resolution to be to be useful for biological inference, we use Illumina H3K4me1 ChIP-seq data to detect changes in nucleosome positioning around transcription factor binding sites due to tamoxifen stimulation, to discriminate functional and non-functional transcription factor binding sites more effectively than with enrichment profiles, and to confirm that the pioneer transcription factor Foxa2 associates with the accessible major groove of nucleosomal DNA.
Keywords
Algorithms, Animals, Area Under Curve, Binding Sites, Chromatin Immunoprecipitation, Computational Biology/methods, Gene Expression Profiling, Gene Expression Regulation, Hepatocyte Nuclear Factor 3-beta/metabolism, Histones/chemistry, Homeodomain Proteins/metabolism, Humans, Islets of Langerhans/metabolism, Mice, Micrococcal Nuclease/chemistry, Models, Statistical, Nucleosomes/metabolism, Probability, Reproducibility of Results, Tamoxifen/chemistry, Trans-Activators/metabolism, Transcription Factors/chemistry
Pubmed
Web of science
Open Access
Yes
Create date
28/02/2022 11:45
Last modification date
23/03/2024 7:24
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