Atropos: specific, sensitive, and speedy trimming of sequencing reads

John P Didion; Marcel Martin; Francis S Collins

doi:10.7717/peerj.3720

Atropos: specific, sensitive, and speedy trimming of sequencing reads

PeerJ. 2017 Aug 30:5:e3720. doi: 10.7717/peerj.3720. eCollection 2017.

Authors

John P Didion¹, Marcel Martin², Francis S Collins¹

Affiliations

¹ National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
² Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.

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 significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos.

Keywords: Adapter; Cutadapt; Illumina; NGS; Preprocessing; Read; Sequencing; Trimming.

Grants and funding

JPD and FSC are funded by the NIH intramural program. Additionally, JPD is funded by the American Diabetes Association (1-17-PDF-100). MM is supported by a grant from the Knut and Alice Wallenberg Foundation to the Wallenberg Advanced Bioinformatics Infrastructure. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.