De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity
De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity
复制标题
DOI：
--
复制
发表时间：
2013-07
期刊：
影响因子：
--
通讯作者：
B. Haas;A. Papanicolaou;M. Yassour;M. Grabherr;Philip D. Blood;Joshua C. Bowden;M. B. Couger;
中科院分区：
文献类型：
--
作者：
B. Haas;A. Papanicolaou;M. Yassour;M. Grabherr;Philip D. Blood;Joshua C. Bowden;M. B. Couger;
RNA-Seq 数据的从头组装使我们能够在不需要基因组序列的情况下研究转录组，例如具有生态和进化重要性的非模型生物、癌症样本或微生物组。在本协议中，我们描述了使用 Trinity 平台从非模型生物体中的 RNA-Seq 数据进行从头转录组组装。我们还介绍了 Trinity 支持的下游应用配套实用程序，包括用于转录本丰度估计的 RSEM、用于识别跨样本差异表达转录本的 R/Bioconductor 包，以及识别蛋白质编码基因的方法。在随附的教程中，我们提供了利用 Trinity 平台进行独立于基因组的转录组分析的工作流程。该软件、文档和演示可从 http://trinityrnaseq.sf.net 免费获取。
De novo assembly of RNA-Seq data allows us to study transcriptomes without the need for a genome sequence, such as in non-model organisms of ecological and evolutionary importance, cancer samples, or the microbiome. In this protocol, we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-Seq data in non-model organisms. We also present Trinity’s supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples, and approaches to identify protein coding genes. In an included tutorial we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http:// trinityrnaseq.sf.net.