title: fluff: exploratory analysis and visualization of high-throughput sequencing data.
abstract: 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 http://fluff.readthedocs.org. Availability. fluff is implemented in Python and runs on Linux. The source code is freely available for download at https://github.com/simonvh/fluff.
authors.affiliation: Radboud University, Molecular Developmental Biology , Nijmegen , The Netherlands.
authors.forename: Georgios
authors.initials: G
authors.lastname: Georgiou
authors.affiliation: Radboud University, Molecular Developmental Biology , Nijmegen , The Netherlands.
authors.forename: Simon J
authors.initials: SJ
authors.lastname: van Heeringen
keywords: ChIP-seq; Clustering; High-throughput sequencing; Next-generation sequencing; Python; Visualization