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Fusionscan: Accurate prediction of fusion genes from RNA-seq data

Title
Fusionscan: Accurate prediction of fusion genes from RNA-seq data
Authors
Kim P.Jang Y.E.Lee S.
Ewha Authors
이상혁
SCOPUS Author ID
이상혁scopus
Issue Date
2019
Journal Title
Genomics and Informatics
ISSN
2234-0742JCR Link
Citation
Genomics and Informatics vol. 17, no. 3
Keywords
Chromosomal translocationFusion transcriptGene fusionRNA-SeqTranscriptome sequencing
Publisher
Korea Genome Organization
Indexed
SCOPUS scopus
Document Type
Article
Abstract
Identification of fusion gene is of prominent importance in cancer research field because of their potential as carcinogenic drivers. RNA sequencing (RNA-Seq) data have been the most useful source for identification of fusion transcripts. Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible. We still lack a reliable program that achieves high precision with reasonable recall rate. Here, we present FusionScan, a highly optimized tool for predicting fusion transcripts from RNA-Seq data. We specifically search for split reads composed of intact exons at the fusion boundaries. Using 269 known fusion cases as the reference, we have implemented various mapping and filtering strategies to remove false-positives without discarding genuine fusions. In the performance test using three cell line datasets with validated fusion cases (NCI-H660, K562, and MCF-7), FusionScan outperformed other existing programs by a considerable margin, achieving the precision and recall rates of 60% and 79%, respectively. Simulation test also demonstrated that FusionScan recovered most of true positives without producing an overwhelming number of false-positives regardless of sequencing depth and read length. The computation time was comparable to other leading tools. We also provide several curative means to help users investigate the details of fusion candidates easily. We believe that FusionScan would be a reliable, efficient and convenient program for detecting fusion transcripts that meet the requirements in the clinical and experimental community. FusionScan is freely available at http://fusionscan.ewha.ac.kr/. © 2019, Korea Genome Organization.
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DOI
10.5808/GI.2019.17.3.e26
Appears in Collections:
자연과학대학 > 생명과학전공 > Journal papers
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