Finder of somatic fusion-genes in RNA-seq data.
Download / Install / Update / Upgrade FusionCatcher
Use this one-line command:
wget http://sf.net/projects/fusioncatcher/files/bootstrap.py -O bootstrap.py && python bootstrap.py -t --downloadFor more see: bootstrap.py --help
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 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).
A detailed manual is available here.
A forum for FusionCatcher is available at Google Groups.
A complete release history can be found here.
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