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Probabilistic Inference for Nucleosome Positioning with MNase-Based or Sonicated Short-Read Data

Overview of attention for article published in PLOS ONE, February 2012
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Title
Probabilistic Inference for Nucleosome Positioning with MNase-Based or Sonicated Short-Read Data
Published in
PLOS ONE, February 2012
DOI 10.1371/journal.pone.0032095
Pubmed ID
Authors

Xuekui Zhang, Gordon Robertson, Sangsoon Woo, Brad G. Hoffman, Raphael Gottardo

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.

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Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 12%
France 2 4%
Spain 1 2%
Unknown 42 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 29%
Student > Ph. D. Student 13 25%
Student > Master 5 10%
Professor > Associate Professor 4 8%
Student > Postgraduate 3 6%
Other 8 16%
Unknown 3 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 63%
Biochemistry, Genetics and Molecular Biology 6 12%
Computer Science 4 8%
Medicine and Dentistry 2 4%
Mathematics 1 2%
Other 2 4%
Unknown 4 8%