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PeerJ. 2016 Jul 19;4:e2209. doi: 10.7717/peerj.2209. eCollection 2016.

fluff: exploratory analysis and visualization of high-throughput sequencing data.

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Radboud University, Molecular Developmental Biology , Nijmegen , The Netherlands.


In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at


fluff is implemented in Python and runs on Linux. The source code is freely available for download at


ChIP-seq; Clustering; High-throughput sequencing; Next-generation sequencing; Python; Visualization

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