Title |
Chromatin segmentation based on a probabilistic model for read counts explains a large portion of the epigenome
|
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Published in |
Genome Biology, July 2015
|
DOI | 10.1186/s13059-015-0708-z |
Pubmed ID | |
Authors |
Alessandro Mammana, Ho-Ryun Chung |
Abstract |
Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an increasingly common experimental approach to generate genome-wide maps of histone modifications and to dissect the complexity of the epigenome. Here, we propose EpiCSeg: a novel algorithm that combines several histone modification maps for the segmentation and characterization of cell-type specific epigenomic landscapes. By using an accurate probabilistic model for the read counts, EpiCSeg provides a useful annotation for a considerably larger portion of the genome, shows a stronger association with validation data, and yields more consistent predictions across replicate experiments when compared to existing methods.The software is available at http://github.com/lamortenera/epicseg. |
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United States | 3 | 20% |
Germany | 1 | 7% |
Venezuela, Bolivarian Republic of | 1 | 7% |
Australia | 1 | 7% |
Sao Tome and Principe | 1 | 7% |
Unknown | 5 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 10 | 67% |
Scientists | 4 | 27% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 7 | 6% |
United Kingdom | 2 | 2% |
Germany | 2 | 2% |
Unknown | 110 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 40 | 33% |
Researcher | 27 | 22% |
Student > Master | 13 | 11% |
Student > Bachelor | 10 | 8% |
Student > Doctoral Student | 7 | 6% |
Other | 12 | 10% |
Unknown | 12 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 42 | 35% |
Biochemistry, Genetics and Molecular Biology | 39 | 32% |
Computer Science | 14 | 12% |
Mathematics | 4 | 3% |
Medicine and Dentistry | 2 | 2% |
Other | 5 | 4% |
Unknown | 15 | 12% |