Trawler: de novo regulatory motif discovery pipeline for chromatin immunoprecipitation
We developed Trawler, the fastest computational pipeline to date, to efficiently discover over-represented motifs in chromatin immunoprecipitation (ChIP) experiments and to predict their functional instances. When we applied Trawler to data from yeast and mammals, 83% of the known binding sites were...
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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
24 June 2007
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| In: |
Nature methods
Year: 2007, Volume: 4, Issue: 7, Pages: 563-565 |
| ISSN: | 1548-7105 |
| DOI: | 10.1038/nmeth1061 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1038/nmeth1061 Verlag, Volltext: https://www.nature.com/nmeth/journal/v4/n7/full/nmeth1061.html 
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| Author Notes: | Laurence Ettwiller, Benedict Paten, Mirana Ramialison, Ewan Birney, Joachim Wittbrodt |
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| 520 | |a We developed Trawler, the fastest computational pipeline to date, to efficiently discover over-represented motifs in chromatin immunoprecipitation (ChIP) experiments and to predict their functional instances. When we applied Trawler to data from yeast and mammals, 83% of the known binding sites were accurately called, often with other additional binding sites, providing hints of combinatorial input. Newly discovered motifs and their features (identity, conservation, position in sequence) are displayed on a web interface. | ||
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