4.6 Article

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

Journal

PEERJ
Volume 4, Issue -, Pages -

Publisher

PEERJ INC
DOI: 10.7717/peerj.2209

Keywords

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

Funding

  1. Netherlands Organisation for Scientific Research (NWO-ALW) [863.12.002]
  2. US National Institutes of Health (NICHD) [R01HD069344]

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A Summary. 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 gehomic profiles As command -line tools, the fluff programs can easily be integrated into standard analysis pipelines.

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