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. 2018 Aug 1;34(15):2666-2669.
doi: 10.1093/bioinformatics/bty149.

NanoPack: visualizing and processing long-read sequencing data

Wouter De Coster  1 , Svenn D'Hert  2 , Darrin T Schultz  3 , Marc Cruts  1 , Christine Van Broeckhoven  1
Affiliations

NanoPack: visualizing and processing long-read sequencing data

Wouter De Coster et al. Bioinformatics. .

Abstract

Summary: Here we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.

Availability and implementation: The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
Examples of plots of NanoPlot and NanoComp. (A) Cumulative yield plot (B) Flow cell activity heatmap showing number of reads per channel. (C) Violin plots comparing base call quality over time. (D) NanoComp plot comparing log transformed read lengths of the E.coli dataset with a K.pneumoniae and human dataset. (E) Bivariate plot of log transformed read length against base call quality with hexagonal bins and marginal histograms. (F) Bivariate plot of base call quality against percent identity with a kernel density estimate and marginal density plots
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