fastQ_brew：用于FASTQ序列数据的分析、预处理和重新格式化的模块。

fastQ_brew: module for analysis, preprocessing, and reformatting of FASTQ sequence data.

作者信息

O'Halloran Damien M

机构信息

Institute for Neuroscience, The George Washington University, 636 Ross Hall, 2300 I St. N.W., Washington, DC, 20052, USA.

Department of Biological Sciences, The George Washington University, 636 Ross Hall, 2300 I St. N.W., Washington, DC, 20052, USA.

出版信息

BMC Res Notes. 2017 Jul 12;10(1):275. doi: 10.1186/s13104-017-2616-7.

DOI:10.1186/s13104-017-2616-7

PMID:28701181

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5508660/

Abstract

BACKGROUND

Next generation sequencing datasets are stored as FASTQ formatted files. In order to avoid downstream artefacts, it is critical to implement a robust preprocessing protocol of the FASTQ sequence in order to determine the integrity and quality of the data.

RESULTS

Here I describe fastQ_brew which is a package that provides a suite of methods to evaluate sequence data in FASTQ format and efficiently implements a variety of manipulations to filter sequence data by size, quality and/or sequence. fastQ_brew allows for mismatch searches to adapter sequences, left and right end trimming, removal of duplicate reads, as well as reads containing non-designated bases. fastQ_brew also returns summary statistics on the unfiltered and filtered FASTQ data, and offers FASTQ to FASTA conversion as well as FASTQ reverse complement and DNA to RNA manipulations.

CONCLUSIONS

fastQ_brew is open source and freely available to all users at the following webpage: https://github.com/dohalloran/fastQ_brew .

摘要

背景

下一代测序数据集以FASTQ格式文件存储。为避免下游出现假象，实施强大的FASTQ序列预处理协议以确定数据的完整性和质量至关重要。

结果

在此我描述了fastQ_brew，它是一个软件包，提供了一套评估FASTQ格式序列数据的方法，并有效地实施了各种操作，以按大小、质量和/或序列过滤序列数据。fastQ_brew允许对衔接子序列进行错配搜索、左右端修剪、去除重复读段以及去除包含非指定碱基的读段。fastQ_brew还返回未过滤和已过滤FASTQ数据的汇总统计信息，并提供FASTQ到FASTA的转换以及FASTQ反向互补和DNA到RNA的操作。