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INCOMMON

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INCOMMON is a tool for the INference of COpy number and Mutation Multiplicity in ONcology. INCOMMON infers the copy number and multiplicity of somatic mutations from tumor-only read count data, and can be applied to classify mutations from large-size datasets in an efficient and fast way.

INCOMMON is also available as a user-friendly ShinyApp.

You can download the results of our analysis from Zenodo.

Check out our preprint on medRxiv!

Help and support

Please find the instructions on how to run the package and browse vignettes at:

Installation

You can install the INCOMMON from GitHub with:

# install.packages("devtools")
devtools::install_github("caravagnalab/INCOMMON")

Copyright and contacts

Cancer Data Science (CDS) Laboratory.

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Bayesian inference of gene mutant dosage from targeted panels without matched normal

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