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Robust prediction of clinical outcomes using cytometry data without cell gating

Bioconductor version: Release (3.19)

This package provides functions that predict clinical outcomes using single cell data (such as flow cytometry data, RNA single cell sequencing data) without the requirement of cell gating or clustering.

Author: Zicheng Hu

Maintainer: Zicheng Hu < at>

Citation (from within R, enter citation("CytoDx")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Introduction to CytoDx PDF R Script
Reference Manual PDF


biocViews CellBasedAssays, CellBiology, Classification, FlowCytometry, ImmunoOncology, Regression, Software, StatisticalMethod, Survival
Version 1.24.0
In Bioconductor since BioC 3.7 (R-3.5) (6 years)
License GPL-2
Depends R (>= 3.5)
Imports doParallel, dplyr, glmnet, rpart, rpart.plot, stats, flowCore, grDevices, graphics, utils
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Suggests knitr, rmarkdown
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Follow Installation instructions to use this package in your R session.

Source Package CytoDx_1.24.0.tar.gz
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macOS Binary (x86_64) CytoDx_1.24.0.tgz
macOS Binary (arm64) CytoDx_1.24.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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