How do you generate read-length vs read-quality plot for long-read sequencing data (e.g., MinION)? How do you generate read-length vs read-quality plot (heat map with histograms in the margin) for long-read sequencing data from the Oxford Nanopore Technologies (ONT) MinION? The MinKNOW software from ONT provides a plot like this during base calling.

This would also be very helpful for PacBio data.
I also wrote a package to create various plots from Oxford Nanopore sequencing data and alignments: NanoPlot. It can be installed through pip (see also the README on Github). In addition to multiple plots also a limited NanoStats output is created (see also NanoStat). Data can be presented using:


A fastq file (optionally compressed)
A bam file
The sequencing_summary.txt file generated by albacore


Using optional flags you can:


Log transform the read lengths
Use aligned reads rather than sequenced reads
Downsample the reads
Set a maximum read length


I've added an example below, plotting log transformed read length vs average read quality (using a kernel density estimate). More examples can be found in the gallery on my blog.

I welcome all feedback and suggestions!