Skip to main content

Genion, an Accurate Tool to Detect Gene Fusion from Long Transcriptomics Reads

Date created
2022-02-14
Authors/Contributors
Abstract
Background  The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges.Results  We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions.Conclusions  Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion.
Document
Scholarly level
Peer reviewed?
Yes
Language
English
Member of collection

Views & downloads - as of June 2023

Views: 7
Downloads: 0