The INCOMMON package implements the statistical framework described in Calonaci et al; medRxiv (2024) to infer mutation copy number and multiplicity directly from tumor-only clinical targeted sequencing data, without requiring matched normal samples. This information is used to derive gene mutant dosage, an emergent property of the interplay between somatic mutations and copy-number alterations that is overlooked by standard binary mutant/wild-type models. INCOMMON stratifies patients by mutant dosage of oncogenes and tumor suppressor genes to identify biomarkers of prognosis and metastatic tropism.
INCOMMON is also available as a user-friendly ShinyApp (see this vignette for a brief overview of what it offers).
You can download the results of our analysis from Zenodo.
Citation
If you use INCOMMON, please cite our preprint:
- Calonaci, N., Krasniqi, E., Čolić, D. et al. Gene mutant dosage is associated with prognosis and metastatic tropism in 60,000 clinical cancer samples. medRxiv (2024).
Installation
You can install INCOMMON from GitHub with:
# install.packages("devtools")
devtools::install_github("caravagnalab/INCOMMON")If you want to run INCOMMON classification (classify()) yourself, you also need cmdstanr and a working Stan toolchain, which are not installed automatically:
install.packages("cmdstanr", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
cmdstanr::install_cmdstan()Alternatively, the INCOMMON web app (see this vignette) runs the same model in your browser, with no local Stan installation required.
