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GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly
Genome Research ( IF 7 ) Pub Date : 2017-12-01 , DOI: 10.1101/gr.222109.117
Daniel L. Cameron , Jan Schröder , Jocelyn Sietsma Penington , Hongdo Do , Ramyar Molania , Alexander Dobrovic , Terence P. Speed , Anthony T. Papenfuss

The identification of genomic rearrangements with high sensitivity and specificity using massively parallel sequencing remains a major challenge, particularly in precision medicine and cancer research. Here, we describe a new method for detecting rearrangements, GRIDSS (Genome Rearrangement IDentification Software Suite). GRIDSS is a multithreaded structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph-based assembler. By combining assembly, split read, and read pair evidence using a probabilistic scoring, GRIDSS achieves high sensitivity and specificity on simulated, cell line, and patient tumor data, recently winning SV subchallenge #5 of the ICGC-TCGA DREAM8.5 Somatic Mutation Calling Challenge. On human cell line data, GRIDSS halves the false discovery rate compared to other recent methods while matching or exceeding their sensitivity. GRIDSS identifies nontemplate sequence insertions, microhomologies, and large imperfect homologies, estimates a quality score for each breakpoint, stratifies calls into high or low confidence, and supports multisample analysis.



中文翻译:

GRIDSS:使用位置de Bruijn图装配进行灵敏且特定的基因组重排检测

使用大规模平行测序鉴定具有高灵敏度和特异性的基因组重排仍然是一个重大挑战,特别是在精密医学和癌症研究中。在这里,我们描述了一种检测重排的新方法GRIDSS(基因组重排IDentification软件套件)。GRIDSS是一个多线程结构变异(SV)调用程序,它使用新颖的基于位置de Bruijn图的汇编程序在进行变量调用之前执行有效的全基因组断裂末端组装。通过使用概率评分组合组装,拆分阅读和阅读对证据,GRIDSS在模拟,细胞系和患者肿瘤数据上实现了高灵敏度和特异性,最近赢得了ICGC-TCGA DREAM8.5体细胞突变的#5挑战挑战。在人类细胞系数据上,与其他最近的方法相比,GRIDSS的错误发现率降低了一半,同时达到或超过了它们的灵敏度。GRIDSS可以识别非模板序列插入,微观同源性和不完全同源性,估计每个断点的质量得分,将调用分为高置信度或低置信度,并支持多样本分析。

更新日期:2017-12-01
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