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Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples

机译:消除歧义:一种开源应用程序用于消除嫁接样品的下一代测序数据中的两种物种

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摘要

Grafting of cell lines and primary tumours is a crucial step in the drug development process between cell line studies and clinical trials. Disambiguate is a program for computationally separating the sequencing reads of two species derived from grafted samples. Disambiguate operates on DNA or RNA-seq alignments to the two species and separates the components at very high sensitivity and specificity as illustrated in artificially mixed human-mouse samples. This allows for maximum recovery of data from target tumours for more accurate variant calling and gene expression quantification. Given that no general use open source algorithm accessible to the bioinformatics community exists for the purposes of separating the two species data, the proposed Disambiguate tool presents a novel approach and improvement to performing sequence analysis of grafted samples. Both Python and C++ implementations are available and they are integrated into several open and closed source pipelines. Disambiguate is open source and is freely available at .
机译:细胞系和原发性肿瘤的移植是细胞系研究和临床试验之间药物开发过程中的关键步骤。歧义消除程序是一种用于从计算嫁接样品中分离出两种物种的测序读数的程序。歧义消除酶通过对这两个物种的DNA或RNA-seq比对进行操作,并以非常高的灵敏度和特异性分离组分,如人工混合的人-鼠样品中所示。这样可以最大程度地从靶肿瘤中回收数据,以进行更准确的变异调用和基因表达定量。鉴于不存在用于分离两个物种数据的生物信息学界可访问的通用开源算法,因此所提出的歧义消除工具提出了一种新颖的方法,并对进行嫁接样品的序列分析进行了改进。 Python和C ++实现均可用,并且已集成到多个开放和封闭源代码管道中。歧义消除是开源的,可以在上免费获得。

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