CASSys: an integrated software-system for the interactive analysis of ChIP-seq data

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doi doi:10.2390/biecoll-jib-2011-155
submission April 30, 2011
published June 21, 2011
NCBI PubMed PubMed ID 21690655

Malik Alawi, Stefan Kurtz and Michael Beckstette

Correspondence should be addressed to:
Michael Beckstette
Center for Bioinformatics, University of Hamburg, Bundesstraße 43, 20146 Hamburg, Germany


The mapping of DNA-protein interactions is crucial for a full understanding of transcriptional regulation. Chromatin-immunoprecipitation followed by massively parallel sequencing (ChIP-seq) has become the standard technique for analyzing these interactions on a genome-wide scale. We have developed a software system called CASSys (ChIP-seq data Analysis Software System) spanning all steps of ChIP-seq data analysis. It supersedes the laborious application of several single command line tools. CASSys provides functionality ranging from quality assessment and -control of short reads, over the mapping of reads against a reference genome (readmapping) and the detection of enriched regions (peakdetection) to various follow-up analyses. The latter are accessible via a state-of-the-art web interface and can be performed interactively by the user. The follow-up analyses allow for flexible user defined association of putative interaction sites with genes, visualization of their genomic context with an integrated genome browser, the detection of putative binding motifs, the identification of over-represented Gene Ontology-terms, pathway analysis and the visualization of interaction networks. The system is client-server based, accessible via a web browser and does not require any software installation on the client side. To demonstrate CASSys's functionality we used the system for the complete data analysis of a publicly available Chip-seq study that investigated the role of the transcription factor estrogen receptor-α in breast cancer cells.


Malik Alawi, Stefan Kurtz and Michael Beckstette. CASSys: an integrated software-system for the interactive analysis of ChIP-seq data. Journal of Integrative Bioinformatics, 8(2):155, 2011. Online Journal:
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