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TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data

机译:TcGabiolinks:用于TCGA数据的整合分析的R / Biocumond封装

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The Cancer Genome Atlas (TCGA) research network has made public a large collection of clinical and molecular phenotypes of more than 10 000 tumor patients across 33 different tumor types. Using this cohort, TCGA has published over 20 marker papers detailing the genomic and epigenomic alterations associated with these tumor types. Although many important discoveries have been made by TCGA's research network, opportunities still exist to implement novel methods, thereby elucidating new biological pathways and diagnostic markers. However, mining the TCGA data presents several bioinformatics challenges, such as data retrieval and integration with clinical data and other molecular data types (e.g. RNA and DNA methylation). We developed an R/Bioconductor package called TCGAbiolinks to address these challenges and offer bioinformatics solutions by using a guided workflow to allow users to query, download and perform integrative analyses of TCGA data. We combined methods from computer science and statistics into the pipeline and incorporated methodologies developed in previous TCGA marker studies and in our own group. Using four different TCGA tumor types (Kidney, Brain, Breast and Colon) as examples, we provide case studies to illustrate examples of reproducibility, integrative analysis and utilization of different Bioconductor packages to advance and accelerate novel discoveries.
机译:癌症基因组阿特拉斯(TCGA)研究网络已经在33种不同的肿瘤类型中公布了大量临床和分子表型的临床和分子表型。使用此队列,TCGA已发表于20篇标记纸,详细介绍与这些肿瘤类型相关的基因组和表观胶质改变。虽然TCGA的研究网络已经进行了许多重要的发现,但仍然存在机会以实施新的方法,从而阐明新的生物途径和诊断标志物。然而,挖掘TCGA数据呈现几种生物信息学挑战,例如与临床数据和其他分子数据类型的数据检索和集成(例如RNA和DNA甲基化)。我们开发了一个称为TCGabiolinks的R / Biocumonds封装,以解决这些挑战,并通过使用导游的工作流程提供生物信息学解决方案,以允许用户查询,下载和执行TCGA数据的集成分析。我们将计算机科学和统计数据的组合到Pipeline和Incorporated方法中,在先前的TCGA标记研究和我们自己的团队中开发。使用四种不同的TCGA肿瘤类型(肾脏,脑,乳房和结肠)作为示例,我们提供了案例研究,以说明不同的生物导体包装的再现性,综合分析和利用的例子,以推进和加速新的发现。

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