FUGAREC

FUGAREC is a tool to detect fusion genes from long read RNA-seq data.

Depencency

• Minimap2 (tested with version 2.17)
• BLAT (tested with version 36x2)
• python (tested with version 3.11.5)
• pandas (tested with version 2.1.1)
• numpy (tested with version 1.26.0)

Installation

1. Clone and enter this repository:

git clone https://github.com/Hideo-Matsuda/FUGAREC

2. Download Anaconda and prepare a python runtime environment.

3. Install python and necessary python libraries.

conda create -n FUGAREC
conda activate FUGAREC
conda install python==3.11.5 pandas==2.1.1 numpy==1.26.0

4. Download minimap2 and store a series of files in src/minimap2/

5. Install BLAT, which can be installed through bioconda.

6. Download additional files from FigShare (https://figshare.com/articles/dataset/testdata_fastq/24501754) and put the files the following locations.

data/testdata.fastq
data/ref/hg19_genCode19_rename.fa
data/ref/hg19.rm.fa
out/testdata_gap_blat_min15_stp5.psl

Data

Sequencing data should be placed in data/ in fastq format.

The breast cancer sequencing data used in the paper of FUGAREC is available in the sequence read archive (SRA) under accessions SRX22168673.

How to use

1. Align read to reference genome and transcriptome with minimap2

sh src/run_minimap2.sh

2. Prepare for re-aligning the GAP
   Run Prep_Gap-Realignment.ipynb

3. Align gap sequence to reference genome with blat

sh src/run_blat.sh

4. Detect fusion gene
   Run Detect_Fusion.ipynb

Citing this work

If you use the code or data in this tool, please cite:

@article{Keigo Masuda2024,
  title={Detecting Fusion Genes in Long-Read Transcriptome Sequencing Data with FUGAREC},
  author={Keigo Masuda and Yoshiaki Sota and Hideo Matsuda},
  journal={IPSJ Transactions on Bioinformatics},
  volume={17},
  number={ },
  pages={1-9},
  year={2024},
  doi={10.2197/ipsjtbio.17.1}
}