Subsample FASTQ by sampling connected components of a de-Bruijn graph
Taking a subsample from a FASTQ can lead to poor coverage of some regions in the subsample, causing the subsample to have informational properties that are not representative of the full read set.
graphsample addresses this problem by building a de-Bruijn graph from the reads, identifying all the connected components, and randomly sampling those components. It outputs the reads that belong to the sampled components.
What's the point? Glad you asked! graphsample allows you to take a small subsample from a large set of reads, and use the subsample to optimise the parameters of any tools and algorithms you want to run on the full set.
$ git clone --recursive https://github.com/Blahah/graphsample.git
$ cd graphsample
$ make$ bin/graphsample --help