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:
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.
Description
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:
very good detection rate for finding candidate somatic fusion
genes (see somatic mutations; using a matched normal sample is
optional; several databases of known fusion genes found in healthy
samples are used as a list of known false positives; biological
knowledge is used, like for example gene fusion between a gene and
its pseudogene is filtered out),
very good RT-PCR validation rate of found candidate somatic fusion
genes (this is very important for us),
very good detection of challenging fusion genes, like for example
IGH fusions, CIC fusions, DUX4 fusions, CRLF2 fusions, TCF3 fusions, etc.
very easy to use (i.e. no a priori knowledge of bioinformatic
databases and bioinformatics is needed in order to run FusionCatcher BUT
Linux/Unix knowledge is needed; it allows a very high level of control
for expert users),
to be as automatic as possible (i.e. the FusionCatcher will choose
automatically the best parameters in order to find candidate somatic
fusion genes, e.g. finding automatically the adapters, quality trimming
of reads, building the exon-exon junctions automatically based on the
length of the reads given as input, etc. while giving also full control
to expert users) while providing the best possible detection rate for
finding somatic fusion genes (with a very low rate of false positives
but a very good precision).
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
FusionCatcher
Finder of somatic fusion-genes in RNA-seq data.
Download / Install / Update / Upgrade FusionCatcher
Use this one-line command:
If one wants to have all the questions asked by boostrap.py answered automatically with yes then add
-yto the command above. For more installing options, see:On Ubuntu Linux running this command before installing FusionCatcher using
bootstrap.pywould help making the installation process smoother:FusionCatcher can be installed also using
conda, as follows:FusionCatcher can be installed also from GitHub, as follows:
NOTE: Here it is assumed that Python 2.7.x, BioPython (>v1.5), and Java Runtime Environment 1.8 are already installed.
Description
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:
Manual
A detailed manual is available here.
Forum
A forum for FusionCatcher is available at Google Groups.
Release history
A complete release history can be found here.
Official releases
Old releases and the latest official release of FusionCatcher are on https://sourceforge.net/projects/fusioncatcher/files/
Citing
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