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Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing

Sakrapee Paisitkriangkrai1, Kelly Quek2,3, Eva Nievergall4

  • 1School of Computer Science, The University of Adelaide, Adelaide, 5005, Australia.

Molecular Genetics and Genomics : MGG
|June 9, 2018
PubMed

Insights

A new software tool, Co-occurrence Fusion (Co-fuse), identifies recurrent fusion genes in cancer RNA-seq data. It aids in discovering new disease subgroups and potential therapeutic targets by analyzing gene patterns.

Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Recurrent oncogenic fusion genes are crucial in cancer development and can be therapeutic targets.
  • Existing analysis tools lack the ability to identify and compare fusion genes across multiple samples.

Purpose of the Study:

  • To develop a user-friendly software tool, Co-occurrence Fusion (Co-fuse), for identifying recurrent fusion genes.
  • To enable biologists to merge RNA-seq data for fusion gene discovery without extensive processing.

Main Methods:

  • Co-fuse utilizes pattern mining and statistical analysis to detect hidden patterns of recurrent fusion genes.
  • The tool was applied to RNA-seq data from leukemic cell lines and primary glioma samples.

Main Results:

  • Co-fuse identified two distinct clusters in leukemic cell lines based on fusion genes: one enriched in multiple myeloma (MM) and another in acute myeloid leukemia (AML).
  • The tool successfully identified known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM samples.
  • Co-fuse validated recurrent fusion genes in a dataset of 272 primary glioma samples.

Conclusions:

  • Co-fuse is a powerful tool for analyzing large RNA-seq datasets to identify recurrent fusion genes.
  • It has the potential to discover novel disease subgroups and driver genes for targeted therapy development.
  • The Co-fuse R source code is publicly available for broader research application.
Keywords:
CancerLeukemiaOncologyRNA-sequencingRecurrent fusion genes

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