vanheeringen-lab / seq2science

Automated and customizable preprocessing of Next-Generation Sequencing data, including full (sc)ATAC-seq, ChIP-seq, and (sc)RNA-seq workflows. Works equally easy with public as local data.
https://vanheeringen-lab.github.io/seq2science
MIT License
155 stars 27 forks source link

ASAP to trimmed FASTQs #969

Closed siebrenf closed 1 year ago

siebrenf commented 1 year ago

Prioritize getting trimmed fastqs, allowing intermediate files to be deleted. After reaching trimmed fastqs, file sizes balloon, so this should minimize disk usage.

I rewrote some other priorities as well, since generating aligner indexes remains a big bottleneck.