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BioinformaticsNature Communications
Peer-reviewed journal article

Single cell gene fusion detection by scFusion

Zijie JiniD, Wenjian HuangiD, Ning SheniD, Juan LiiD, Xiao-Chen WangiD, Jiqiao Dong, Peter J. ParkiD, Ruibin XiiD

Abstract

Gene fusions are widespread in tumor cells and can play important roles in tumor initiation and progression. Using full length single cell RNA sequencing (scRNA-seq), gene fusions can now be detected at single cell level. However, scRNA-seq data has a high noise level and contains various technical artefacts that can lead to spurous fusion discoveries. Here we present a computational tool, scFusion, for gene fusion detection based on scRNA-seq. scFusion can efficiently and sensitively detect fusions with a low false discovery rate. In a T cell data, scFusion detected the invariant TCR gene recombinations in Mucosal-associated invariant T cells that many methods developed for bulk-data failed to detect. In a multiple myeloma data, scFusion detected the known recurrent fusion IgH-WHSC1, which was associated with overexpression of the WHSC1 oncogene.

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