The package imports fusion results from tophat-fusion, tophat-fusion-post, mapSplice, deFuse, fusionmap, bellerophontes, fusionfinder, fusionhunter, STAR, Rsubread, fusionCatcher.
The package was design to facilitate the characterisation of fusion products events.
outputs for the above indicated fusion detection tools can be imported using
importFusionData in a list of
fSet-class offers various methods to extract information from the fSet objects.
The fusion names can be extracted with
The number of reads supporting a fusion event cam be extracted with the
The imported fusion list can be filtered using
Oncofuse can be installed in chimera with the function
Various information on the fusions location, on structural and functional domains affected by the fusion event as well as a prediction of the putative functional effect of the fusion on the cell can be obtained by using
chimeraSeqs generates the nucleotide sequence of a fusion transcript described in an fSet object.
chimeraSeqSet does the same but on a list of
fusionPeptides allows to investigate if the fusion events generate also a fusion at protein level.
subreadRun allows to remap reads on the fused transcripts reconstructed with
GapFiller is a seed-and-extend local assembler capable to produce (in-silico) longer and highly accurate sequences from a collection of Next Generation Sequencing reads. It can be installed in chimera with the function
gapfillerRun allows to check if reads mapped by
subreadRun over a fused transcript generated with
chimeraSeqs are able to reconstruct by de novo assembly the fusion break-point.
prettyPrint converts the information stored in a list of
fSet objects in a dataframe structure that is saved as tab delimited file.
Raffaele A Calogero Maintainer: Raffaele A Calogero <email@example.com>
Beccuti M, et al. The structure of state-of-art gene fusion-finder algorithms. OA Bioinformatics 2013;1(1):2. Carrara, M., et al. State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues? BMC bioinformatics 2013;14 Suppl 7:S2. Carrara, M., et al. State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity. BioMed research international 2013;2013:340620. Shugay, M., et al. Oncofuse: a computational framework for the prediction of the oncogenic potential of gene fusions. Bioinformatics 2013;29(20):2539-2546. Nadalin, F., et al. GapFiller: a de novo assembly approach to fill the gap within paired reads. BMC bioinformatics 2012;13 Suppl 14:S8.
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