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

机译:FASTQ_BREW:用于分析,预处理和重新格式化FASTQ序列数据的模块

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摘要

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 .
机译:抽象背景下一代测序数据集存储为FASTQ格式化文件。为了避免下游人工制品,实现FASTQ序列的鲁棒预处理协议是至关重要的,以便确定数据的完整性和质量。这里的结果我描述了FastQ_BREW,它是一种包,其提供了一套方法,以便以FASTQ格式评估序列数据,有效地实现各种操作,以便按大小,质量和/或序列过滤序列数据。 FASTQ_BREW允许不匹配搜索到适配器序列,左右结束修剪,删除重复读取,以及包含未指定基础的读取。 FASTQ_BREW还返回未过滤和过滤的FASTQ数据的摘要统计信息,并为FASTQ进行FASTQ转换,以及FASTQ反相和DNA到RNA操纵。结论FASTQ_BREW是开源的,并自由地提供给以下网页的所有用户:https://github.com/dohalloran/fastq_brew。

著录项

  • 作者

    Damien M. O’Halloran;

  • 作者单位
  • 年度 2017
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  • 原文格式 PDF
  • 正文语种 eng
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