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GimmeMotifs: a de novo motif prediction pipeline for ChIP-sequencing experiments.
Bioinformatics. 2010 Nov 15;
Authors: van Heeringen SJ, Veenstra GJ
SUMMARY: Accurate prediction of transcription factor binding motifs that are enriched in a collection of sequences remains a computational challenge. Here we report on GimmeMotifs, a pipeline that incorporates an ensemble of computational tools to predict motifs de novo from ChIP-sequencing (ChIP-seq) data. Similar, redundant motifs are compared using the Weighted Information Content similarity score and clustered using an iterative procedure. A comprehensive output report is generated with several different evaluation metrics to compare and evaluate the results. Benchmarks show that the method performs well on human and mouse ChIP-seq datasets. GimmeMotifs consists of a suite of command-line scripts that can be easily implemented in a ChIP-seq analysis pipeline. AVAILABILITY: GimmeMotifs is implemented in Python and runs on Linux. The source code is freely available for download at http://www.ncmls.eu/bioinfo/gimmemotifs/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: On-line supplementary information is available at the journal website and at http://www.ncmls.eu/bioinfo/gimmemotifs/
PMID: 21081511 [PubMed - as supplied by publisher]
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GimmeMotifs: a de novo motif prediction pipeline for ChIP-sequencing experiments.
Bioinformatics. 2010 Nov 15;
Authors: van Heeringen SJ, Veenstra GJ
SUMMARY: Accurate prediction of transcription factor binding motifs that are enriched in a collection of sequences remains a computational challenge. Here we report on GimmeMotifs, a pipeline that incorporates an ensemble of computational tools to predict motifs de novo from ChIP-sequencing (ChIP-seq) data. Similar, redundant motifs are compared using the Weighted Information Content similarity score and clustered using an iterative procedure. A comprehensive output report is generated with several different evaluation metrics to compare and evaluate the results. Benchmarks show that the method performs well on human and mouse ChIP-seq datasets. GimmeMotifs consists of a suite of command-line scripts that can be easily implemented in a ChIP-seq analysis pipeline. AVAILABILITY: GimmeMotifs is implemented in Python and runs on Linux. The source code is freely available for download at http://www.ncmls.eu/bioinfo/gimmemotifs/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: On-line supplementary information is available at the journal website and at http://www.ncmls.eu/bioinfo/gimmemotifs/
PMID: 21081511 [PubMed - as supplied by publisher]
More...