ChimerDB 4.0: An updated and expanded database of fusion genes

Ye Eun Jang, Insu Jang, Sunkyu Kim, Subin Cho, Daehan Kim, Keonwoo Kim, Jaewon Kim, Jimin Hwang, Sangok Kim, Jaesang Kim, Jaewoo Kang, Byungwook Lee, Sanghyuk Lee

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


Fusion genes represent an important class of biomarkers and therapeutic targets in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data (ChimerSeq) and text mining of publications (ChimerPub) with extensive manual annotations (ChimerKB). In this update, we present all three modules substantially enhanced by incorporating the recent flood of deep sequencing data and related publications. ChimerSeq now covers all 10 565 patients in the TCGA project, with compilation of computational results from two reliable programs of STAR-Fusion and FusionScan with several public resources. In sum, ChimerSeq includes 65 945 fusion candidates, 21 106 of which were predicted by multiple programs (ChimerSeq-Plus). ChimerPub has been upgraded by applying a deep learning method for text mining followed by extensive manual curation, which yielded 1257 fusion genes including 777 cases with experimental supports (ChimerPub-Plus). ChimerKB includes 1597 fusion genes with publication support, experimental evidences and breakpoint information. Importantly, we implemented several new features to aid estimation of functional significance, including the fusion structure viewer with domain information, gene expression plot of fusion positive versus negative patients and a STRING network viewer. The user interface also was greatly enhanced by applying responsive web design. ChimerDB 4.0 is available at

Original languageEnglish
Pages (from-to)D817-D824
JournalNucleic Acids Research
Issue numberD1
StatePublished - 1 Jan 2020

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Publisher Copyright:
© 2019 The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.


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