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A computational pipeline to extract the transcription factor binding motifs from ChIP-seq data, assuming no reference genome is available. denovochipseq combines de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of denovochipseq using human and mouse data. Analysis of fly data indicates that denovochipseq outperforms alignment based methods that utilize closely related species.

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denovochipseq classification

denovochipseq specifications

Software type:
Restrictions to use:
Operating system:
Command line interface
Input data:
The short reads from a ChIP-seq experiment of the TF being studied, and from a control experiment where non-specific antibody or input DNA is used.
Computer skills:
CD-HIT, meme suite, SEECER, razers, velvet

denovochipseq distribution


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denovochipseq support



  • Ziv Bar-Joseph <>


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Department of Human Genetics, The University of Chicago, CLSC, Chicago, IL, USA; Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA

Funding source(s)

The National Institute of Health (grant no. 1 U01 HL122626-01); the National Science Foundation (grant no. DBI- 1356505)

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