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.
Highlights
All current-generation sequencing technologies, including Illumina, ABI SOLiD, and Ion Torrent, require a library construction step that involves the introduction of short adapter sequences at the ends of the template DNA fragments
We focused on making three specific improvements to Cutadapt: (1) improve the accuracy of paired-end read trimming by implementing an insert-match algorithm; (2) improve the performance by adding multiprocessing support; and (3) add important additional features such as automated trimming of Methyl-Seq reads, automated detection of adapter sequences in reads where the experimental protocols are not known to the analyst, estimation of sequencing error, and generation of quality control (QC) metrics
Performance On a desktop computer with four processing cores, we found that AdapterRemoval had the fastest overall execution time, followed closely by SeqPurge, Atropos, and Skewer (Fig. 2A; Table S2)
Summary
All current-generation sequencing technologies, including Illumina, ABI SOLiD, and Ion Torrent, require a library construction step that involves the introduction of short adapter sequences at the ends of the template DNA fragments. Depending on the sequencing platform and the fragment size distribution of the sequencing library, an often substantial fraction of reads will consist of both template and adapter sequences (Fig. 1A). The error rates of these sequencing technologies vary from 0.1% on Illumina to 5% or more on long-read sequencing platforms. Error rates tend to be enriched at the ends of reads (where adapters are located), exacerbating the effects of adapter contamination. Adapter contamination and sequencing errors can lead to increased rates of misaligned and unaligned reads, which results in errors in downstream analysis including spurious variant calls (Del Fabbro et al, 2013; Sturm, Schroeder & Bauer, 2016). Some methylation sequencing (Methyl-Seq) protocols result in artificially
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