Atropos: specific, sensitive, and speedy trimming of sequencing reads
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology, Genomics, Computational Science
- Keywords
- genomics, pre-processing, sequencing, read trimming, bioinformatics
- Copyright
- © 2016 Didion et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Atropos: specific, sensitive, and speedy trimming of sequencing reads. PeerJ Preprints 4:e2452v1 https://doi.org/10.7287/peerj.preprints.2452v1
Abstract
A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves a four-fold increase in trimming accuracy and a decrease in execution time of ~50% (using 16 parallel execution threads). Furthermore, Atropos maintains high accuracy even when trimming simulated data with a high rate of error. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of most current-generation sequencing data sets.
Atropos is open source and free software written in Python and available at https://github.com/jdidion/atropos.
Author Comment
This is a submission to PeerJ PrePrints.