Vats Pankaj, Chinnaiyan Arul M, Kumar-Sinha Chandan
Department of Pathology, Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Methods Mol Biol. 2020;2079:69-79. doi: 10.1007/978-1-4939-9904-0_5.
RNA-seq provides an efficient and sensitive methodology to identify fusion transcripts in cancer tissues. Chimeric reads mapping across two different genes represent potential gene fusions. Various methodologies have been implemented in the detection of gene fusions by RNA-seq. Here we describe a general methodology used in processing and filtering of RNA-seq data, followed by filtering of multiple varieties of artifacts to nominate potentially relevant gene fusions. Functional relevance of gene fusions is assessed based on the predicted domain architecture of the putative fusion proteins.
RNA测序提供了一种高效且灵敏的方法来识别癌组织中的融合转录本。跨越两个不同基因的嵌合 reads 代表潜在的基因融合。在通过RNA测序检测基因融合方面已经实施了各种方法。在这里，我们描述了一种用于处理和过滤RNA测序数据的通用方法，随后对多种假象进行过滤以提名潜在相关的基因融合。基于推定融合蛋白的预测结构域结构评估基因融合的功能相关性。
