Title |
PureCLIP: capturing target-specific protein–RNA interaction footprints from single-nucleotide CLIP-seq data
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Published in |
Genome Biology, December 2017
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DOI | 10.1186/s13059-017-1364-2 |
Pubmed ID | |
Authors |
Sabrina Krakau, Hugues Richard, Annalisa Marsico |
Abstract |
The iCLIP and eCLIP techniques facilitate the detection of protein-RNA interaction sites at high resolution, based on diagnostic events at crosslink sites. However, previous methods do not explicitly model the specifics of iCLIP and eCLIP truncation patterns and possible biases. We developed PureCLIP ( https://github.com/skrakau/PureCLIP ), a hidden Markov model based approach, which simultaneously performs peak-calling and individual crosslink site detection. It explicitly incorporates a non-specific background signal and, for the first time, non-specific sequence biases. On both simulated and real data, PureCLIP is more accurate in calling crosslink sites than other state-of-the-art methods and has a higher agreement across replicates. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 3 | 18% |
Switzerland | 2 | 12% |
Germany | 2 | 12% |
Canada | 1 | 6% |
France | 1 | 6% |
United Kingdom | 1 | 6% |
Unknown | 7 | 41% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 10 | 59% |
Members of the public | 6 | 35% |
Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 132 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 35 | 27% |
Researcher | 19 | 14% |
Student > Master | 16 | 12% |
Student > Bachelor | 12 | 9% |
Student > Doctoral Student | 6 | 5% |
Other | 16 | 12% |
Unknown | 28 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 49 | 37% |
Agricultural and Biological Sciences | 26 | 20% |
Computer Science | 12 | 9% |
Neuroscience | 3 | 2% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 2% |
Other | 9 | 7% |
Unknown | 30 | 23% |