ChimerDB 3.0: An enhanced database for fusion genes from cancer transcriptome and literature data mining

Myunggyo Lee, Kyubum Lee, Namhee Yu, Insu Jang, Ikjung Choi, Pora Kim, Ye EunJang, Byounggun Kim, Sunkyu Kim, Byungwook Lee, Jaewoo Kang, Sanghyuk Lee

    Research output: Contribution to journalArticlepeer-review

    70 Citations (Scopus)

    Abstract

    Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/.

    Original languageEnglish
    Pages (from-to)D784-D789
    JournalNucleic acids research
    Volume45
    Issue numberD1
    Publication statusPublished - 2017 Jan 1

    Bibliographical note

    Publisher Copyright:
    © The Author(s) 2016.

    ASJC Scopus subject areas

    • Genetics

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