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首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >A Genomic Analysis Pipeline and Its Application to Pediatric Cancers
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A Genomic Analysis Pipeline and Its Application to Pediatric Cancers

机译：基因组分析管道及其在小儿癌症中的应用

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摘要

We present a cancer genomic analysis pipeline which takes as input sequencing reads for both germline and tumor genomes and outputs filtered lists of all genetic mutations in the form of short ranked list of the most affected genes in the tumor, using either the Complete Genomics or Illumina platforms. A novel reporting and ranking system has been developed that makes use of publicly available datasets and literature specific to each patient, including new methods for using publicly available expression data in the absence of proper control data. Previously implicated small and large variations (including gene fusions) are reported in addition to probable driver mutations. Relationships between cancer and the sequenced tumor genome are highlighted using a network-based approach that integrates known and predicted protein-protein, protein-TF, and protein-drug interaction data. By using an integrative approach, effects of genetic variations on gene expression are used to provide further evidence of driver mutations. This pipeline has been developed with the aim to be used in assisting in the analysis of pediatric tumors, as an unbiased and automated method for interpreting sequencing results along with identifying potentially therapeutic drugs and their targets. We present results that agree with previous literature and highlight specific findings in a few patients.
机译：我们提供了一个癌症基因组学分析流程，作为完整的种系和肿瘤基因组的输入测序读数，并使用完整基因组学或Illumina，以肿瘤中最易受影响的基因的短列表的形式输出所有遗传突变的过滤后的列表平台。已经开发了一种新颖的报告和排名系统，其利用了针对每个患者的公开可用数据集和文献，包括在没有适当对照数据的情况下使用公开可用表达数据的新方法。除了可能的驱动程序突变外，以前还涉及到大小变异（包括基因融合）。使用基于网络的方法突出显示癌症与测序的肿瘤基因组之间的关系，该方法整合了已知和预测的蛋白质-蛋白质，蛋白质-TF和蛋白质-药物相互作用数据。通过使用整合方法，遗传变异对基因表达的影响可用于提供驱动程序突变的进一步证据。开发此管道的目的是用于辅助分析儿科肿瘤，这是一种无偏倚的自动化方法，可用于解释测序结果以及鉴定潜在的治疗药物及其靶标。我们提供的结果与以前的文献一致，并着重介绍了少数患者的具体发现。

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