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Atropos:对测序读数进行特定、灵敏且快速的修剪。

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

作者信息

Didion John P, Martin Marcel, Collins Francis S

机构信息

National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.

Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.

出版信息

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

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.

摘要

将原始测序读数转化为生物学见解的关键一步是去除接头序列和低质量碱基。已证明读段修剪可提高质量和可靠性,同时降低下游分析的计算需求。有许多读段修剪软件工具可供使用;然而,没有一种工具能同时提供处理现代基于测序的实验中产生的数据类型和数据量所需的准确性、计算效率和功能集。在这里,我们介绍Atropos,并表明它在保持领先速度的同时,能以高灵敏度和特异性修剪读段。与其他最先进的读段修剪工具相比,Atropos在修剪准确性上有显著提高,同时在执行时间上仍具竞争力。此外,即使在修剪测序错误率较高的数据时,Atropos也能保持高精度。Atropos提供的准确性、高性能和广泛的功能集使其成为Illumina、ABI SOLiD和其他当前一代短读测序数据集预处理的合适选择。Atropos是用Python(3.3+)编写的开源免费软件,可在https://github.com/jdidion/atropos上获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6da/5581536/7af77e47226c/peerj-05-3720-g001.jpg

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