Combiroc

Combiroc is a brand new music in multi-markers analysis: an R package for efficient and easy combinatorial selection of biomarkers and sensitivity/specificity-driven prioritization of features.

While the legacy Shiny App was meant to be used for short lists of biomarkers, the R package introduces new features to work on single-cell RNAseq datasets, selecting smaller markers sub-signatures that can be used to efficiently identify and annotate cell clusters. Such new features are also documented in our latest publication on Scientific Reports..

This is the development version of CombiROC package (combiroc), code in this repo is always work in progress and it is uploaded here "as-is" with no warranties implied. Improvements and new features will be added on a regular basis, please check on this github page for new features and releases.

The legacy CombiROC Shiny web-app

The CombiROC approach was first released as a Shiny Application which is still available at combiroc.eu but it has limited features as well as low computational power and is not further maintained. If you need to cite the web-app please refer to Mazzara et al. Scientific Reports 2017 and Bombaci & Rossi, Methods Mol Biol 2019.

For full capabilities and customized analyses we suggest to use the R package (this repo & see below) and not the Shiny app version.

The combiroc R package (and how to cite it)

If you are using the combiroc package in your research, please cite our latest paper (2026) on Scientific Reports featuring combiroc's usage with single cell RNAseq data: Ferrari et al. *Single cell RNAseq signatures refined with combiroc enhance identification of NK cells in blood and solid tissues; doi: https://doi.org/10.1038/s41598-025-29876-5

Combiroc's Scientific Reports paper Supplementary material

The Supplementary Material 1 and 2 (documented protocols/vignettes) can be accessed here:

• Supplementary Material 1 (Standard vignette): Standard worlkflow.
• Supplementary Material 2 (single cell RNAseq protocol): scRNAseq workflow.

"Less is more" version of the paper (preprint)

The 2026 Scientific Reports paper was anticipated by our previous "Less is more" bioRxiv preprint: Ferrari et al. Combiroc: when 'less is more' in bulk and single cell marker signatures. bioRxiv 2022.01.17.476603; doi: https://doi.org/10.1101/2022.01.17.476603

Package installation (from CRAN)

Documentation on these pages refers to the latest development version and can quickly evolve: if you install combiroc from CRAN please be sure to refer to documentation available on CRAN's combiroc page. Be aware that CRAN version is not necessarily in sync with the development version: current version on CRAN is v.0.3.4.

# You can install combiroc pulling it from CRAN:
install.packages("combiroc")

Development version

# To install the most recent development version from this repository install "remotes" first:
install.packages("remotes")
library(remotes)
# remotes is a lightweight replacement of install functions from devtools
# if you already have devtools, you can also use devtools::install_github() 

# Then install the development version of CombiROC:
remotes::install_github("ingmbioinfo/combiroc", 
                        dependencies = TRUE, build_vignettes = TRUE)

Full Documentation - Tutorial

Full documentation is in the package's vignette. You can also find the rendered version of the vignette in the combiroc-package website created with pkgdown.

Quick start example

library(combiroc)

# load the preformatted demo dataset
# (you can load a dataset of yours using load_data() function: see full docs)
data <- demo_data

# shape it in long format (prone to plotting)
data_long <- combiroc_long(data)

# study the distribution of you markers' signal
# arguments values to be adjusted according to  data
distr <- markers_distribution(data_long, case_class = 'A', 
                              y_lim = 0.0015, x_lim = 3000, 
                              signalthr_prediction = TRUE, 
                              min_SE = 40, min_SP = 80, 
                              boxplot_lim = 2000)

# explore the distr object: boxplot of signals
distr$Boxplot

# explore the distr object: densities of classes with signal threshold (signalthr)
distr$Density_plot
distr$Density_summary

# explore the distr object: ROC and its coordinates
distr$ROC
head(distr$Coord, n=10)

# combinatorial analysis, indicatinf case class anf for combinations of up to 3 markers:
tab <- combi(data, signalthr = 328, combithr = 1,
             case_class = "A", max_length = 3)

# ranked combinations              
rmks <- ranked_combs(tab, min_SE = 40, min_SP = 80)

# check ranked combinations
rmks$table
rmks$bubble_chart

# results report for specific markers/combinations
reports <-roc_reports(data, markers_table = tab, case_class = 'A',
                      single_markers =c('Marker1'), 
                      selected_combinations = c(11,15))

# results outputs
reports$Plot
reports$Metrics

Issues - Bugs

If you find a bug, or to share ideas for improvement, feel free to start an issue. We do have a roadmap but we also listen!

Contributors

• Package authors and maintainers: Ivan Ferrari & Riccardo L. Rossi
• Original code of Shiny App: Saveria Mazzara
• Initial idea & conception: Mauro Bombaci

Trivia

We were so happy to finally had the chance to develop the combiroc package that we felt very "rock": this is why the combiroc hexagon sticker logo is a homage to Eddie Van Halen who left us in 2020, and the "Frankenstrat", his iconic guitar.