Sign in
BioinformaticsbioRxiv
Preprint

seqproc: An efficient, flexible, and concise tool for sequence geometry description and transformation

Noah CapeiD, Elan FisheriD, Daniel LiuiD, Rob PatroiD

Abstract

Complex sequencing protocols encode technical information in read structure and require accurate, e[ff]icient preprocessing. We introduce seqproc, which compiles concise sequence-geometry descriptions into execution graphs. Across four single-cell RNA-sequencing protocols, seqproc has the lowest mean runtime at every tested thread count and uses substantially less memory than the next-fastest tool. It has the highest F1 agreement with conservative structural references on all three discriminative chemistries and ties both alternatives on the 10x length-filter control. By separating protocol description from execution, seqproc makes complex read transformations compact, reusable, and efficient.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISBray '16Liao '19Schuster '25Sklarz '18Melsted '26Melsted '21
58% semantic matchBioinformatics
Nicolas Bray, Harold Pimentel, Páll Melsted+1 more·Nature Biotechnology·Apr 4, 2016· 9,722 citations