Trinity: Transcriptome assembly for genetic and functional analysis of cancer

Trinity：用于癌症遗传和功能分析的转录组组装

• 批准号: 9126450
• 负责人: AVIV REGEV
• 金额: $ 66.45万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-17 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9126450
• 关键词: Adopted; Algorithms; Alternative Splicing; Automobile Driving; Bacteria; Bioinformatics; Cancer Biology; Cells; Cloud Computing; Code; Communities; Computer Analysis; Computer software; Data; Data Set; Diagnostic; Documentation; Educational workshop; Emerging Technologies; Environment; Epigenetic Process; Exons; Fee-for-Service Plans; Funding; Galaxy; Genetic; Genetic Heterogeneity; Genetic Transcription; Genetic Variation; Genome; Health; High Performance Computing; Human; Industry; Inferior; Introns; Lead; Letters; Malignant Neoplasms; Manuals; Maps; Measures; Messenger RNA; Methods; Microbe; Mining; Mutation; Online Systems; Pattern; Performance; Persons; Process; RNA; RNA Editing; RNA Splicing; Reading; Research; Research Infrastructure; Research Personnel; Resort; Resources; Sampling; Sequence Analysis; Services; Shapes; Speed; Structure; Technology; The Cancer Genome Atlas; Training; Training Support; Transcript; Update; Variant; Viral; Work; anticancer research; base; cancer cell; cancer genome; computing resources; disease diagnosis; epigenetic variation; improved; literature citation; microbial; microbiome; new therapeutic target; open source; reconstruction; reference genome; symposium; tool; transcriptome; transcriptome sequencing; transcriptomics; tumor; tumor heterogeneity; tumorigenesis; user-friendly; virome

DESCRIPTION (provided by applicant): RNA-Seq studies indicate that the cancer transcriptome are shaped by genetic changes, variation in gene transcription, mRNA processing, editing and stability, and the cancer microbiome. Deciphering this variation and understanding its implications on tumorigenesis requires sophisticated computational analyses. Most RNA-Seq analyses rely on methods that first map short reads to a reference genome, and then compare them to annotated transcripts or assemble them. However, this strategy can be limited when the cancer genome is substantially different than the reference or for detecting sequences from the cancer microbiome. 'Assembly first' (de novo) methods that combine reads into transcripts without any mapping are a compelling alternative. The assembled transcriptome can then be used to identify mutations, splicing patterns, expression levels, tumor-associated microbes, and - if collected from single cells - characterize tumor heterogeneity. There is thus an enormous need for computationally efficient, accurate and user friendly tools for transcriptome reconstruction and analysis in cancer. Trinity, first released in mid-2011 and freely available as Open Source, is the leading software for de novo RNA-Seq assembly, with over 16,000 downloads, 177 literature citations, and a host of modules for downstream analyses, contributed by 3rd party developers. While widely-adopted in the general research community, Trinity (and any de novo RNA-Seq assembly) is only now emerging in the cancer domain. Here, we will enhance and maintain Trinity as a leading tool for cancer transcriptomics. We will tailor analytic modules for critical tasks in cancer biology, working with a network of cancer researchers on Driving Cancer Projects (Aim 1). We will continue to update the Trinity software to enhance the core algorithm, leverage new sequencing technologies as they arise, and incorporate additional 3rd party tools (Aim 2). We will enhance the Trinity software for different computational environments, including user-friendly interfaces to high performance computing infrastructure freely available to any NCI-funded researcher (Aim 3). We will grow the Trinity cancer user community, using online and in- person training and support (Aim 4), to allow any cancer researcher to leverage it.

描述（由申请人提供）：RNA-seq研究表明，癌症转录组是由遗传变化，基因转录变化，mRNA加工，编辑和稳定性以及癌症微生物组塑造的。解释这种变化并理解其对肿瘤发生的影响需要复杂的计算分析。大多数RNA-seq分析都依赖于首先映射简短读取为参考基因组的方法，然后将它们与注释的转录本进行比较或组装。但是，当癌症基因组与参考或检测癌症微生物组序列的参考大大不同时，该策略可能会受到限制。组合读取为成绩单而无需任何映射的“从头组装”（从头开始）是令人信服的选择。然后，组装的转录组可用于鉴定突变，剪接模式，表达水平，与肿瘤相关的微生物，如果是从单个细胞中收集的 - 表征肿瘤异质性。因此，迫切需要计算高效，准确和用户友好的工具，用于癌症的转录组重建和分析。三位一体，首次于2011年中期发布，自由发行 作为开源的可用，是从头RNA-seq组装的领先软件，由第三方开发人员贡献了16,000多次下载，177个文献引用和许多用于下游分析的模块。虽然在一般研究界广泛采用了广泛的补充，但Trinity（和任何从头RNA-Seq组装）仅在癌症领域才出现。在这里，我们将增强和维持三位一体作为癌症转录组学的领先工具。我们将针对癌症生物学的关键任务量身定制分析模块，并与癌症研究人员网络一起驱动癌症项目（AIM 1）。我们将继续更新三位一体软件，以增强核心算法，利用新的测序技术出现，并结合其他第三方工具（AIM 2）。我们将增强针对不同计算环境的三位一体软件，包括可自由使用的NCI资助研究人员可免费使用的高性能计算基础架构的用户友好接口（AIM 3）。我们将使用在线和人工培训和支持（AIM 4）来发展Trinity Cancer用户社区，以允许任何癌症研究人员利用它。