Finder of somatic fusion-genes in RNA-seq data.
Use this one-line command:
wget http://sf.net/projects/fusioncatcher/files/bootstrap.py -O bootstrap.py && python bootstrap.py -t --download
If one wants to have all the questions asked by boostrap.py answered automatically with yes then add -y
to the
command above. For more installing options, see:
bootstrap.py --help
On Ubuntu Linux running this command before installing FusionCatcher using bootstrap.py
would help making the installation process smoother:
sudo apt-get install wget gawk gcc g++ make cmake automake curl unzip zip bzip2 tar gzip pigz parallel build-essential libncurses5-dev libc6-dev zlib1g zlib1g-dev libtbb-dev libtbb2 python python-dev python-numpy python-biopython python-xlrd python-openpyxl default-jdk
FusionCatcher can be installed also using conda
, as follows:
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda create -n fusioncatcher fusioncatcher
source activate fusioncatcher
download-human-db.sh
FusionCatcher can be installed also from GitHub, as follows:
git clone https://github.com/ndaniel/fusioncatcher
cd fusioncatcher/tools/
./install_tools.sh
cd ../data
./download-human-db.sh
NOTE: Here it is assumed that Python 2.7.x, BioPython (>v1.5), and Java Runtime Environment 1.8 are already installed.
FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data (paired-end or single-end reads from Illumina NGS platforms like Solexa/HiSeq/NextSeq/MiSeq/MiniSeq) from diseased samples.
The aims of FusionCatcher are:
A detailed manual is available here.
A forum for FusionCatcher is available at Google Groups.
A complete release history can be found here.
Old releases and the latest official release of FusionCatcher are on https://sourceforge.net/projects/fusioncatcher/files/
D. Nicorici, M. Satalan, H. Edgren, S. Kangaspeska, A. Murumagi, O. Kallioniemi, S. Virtanen, O. Kilkku, FusionCatcher – a tool for finding somatic fusion genes in paired-end RNA-sequencing data, bioRxiv, Nov. 2014, DOI:10.1101/011650