Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown.
Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown.
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DOI：
10.1038/nprot.2016.095
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发表时间：
2016-09
期刊：
影响因子：
14.8
通讯作者：
Salzberg, Steven L.
中科院分区：
文献类型：
--
作者：
Pertea, Mihaela;Kim, Daehwan;Pertea, Geo M.;Leek, Jeffrey T.;Salzberg, Steven L.
信使RNA的高通量测序（RNA-seq）已成为测量和比较各种物种和条件下基因表达水平的标准方法。RNA-seq实验生成非常大的复杂数据集，需要快速，准确和灵活的软件来将原始读取数据简化为可理解的结果。HISAT，StringTie和Ballgown是免费的开源软件工具，用于全面分析RNA-seq实验。总之，它们使科学家能够将读段与基因组对齐，组装包括新型剪接变体在内的转录本，计算每个样本中这些转录本的丰度，并比较实验以识别差异表达的基因和转录本。该方案描述了处理大量原始测序读数并创建基因转录物、表达水平以及差异表达基因和转录物列表所需的所有步骤。协议的执行时间取决于计算资源，但通常需要不到45分钟的计算机时间。Pertea等人描述了使用HISAT、StringTie和Ballgouge（“新的燕尾服”包）分析RNA-seq数据的方案。该方案可用于转录本的组装、基因表达水平的定量和差异表达分析。
High-throughput sequencing of messenger RNA (RNA-seq) has become the standard method for measuring and comparing the levels of gene expression in a wide variety of species and conditions. RNA-seq experiments generate very large, complex data sets that demand fast, accurate, and flexible software to reduce the raw read data to comprehensible results. HISAT, StringTie, and Ballgown are free, open-source software tools for comprehensive analysis of RNA-seq experiments. Together, they allow scientists to align reads to a genome, assemble transcripts including novel splice variants, compute the abundance of these transcripts in each sample, and compare experiments to identify differentially expressed genes and transcripts. This protocol describes all the steps necessary to process a large set of raw sequencing reads and create lists of gene transcripts, expression levels, and differentially expressed genes and transcripts. The protocol’s execution time depends on the computing resources, but typically takes under 45 minutes of computer time. Pertea et al. describe a protocol to analyze RNA-seq data using HISAT, StringTie, and Ballgown (the “new Tuxedo” package). The protocol can be used for assembly of transcripts, quantification of gene expression levels and differential expression analysis.
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