CytoGLMM

This is the development version of CytoGLMM; for the stable release version, see CytoGLMM.

Conditional Differential Analysis for Flow and Mass Cytometry Experiments

Platform availability badge Ranking badge Support activity badge Years in BioConductor badge Build results badge Last commit badge Dependency count badge

DOI: 10.18129/B9.bioc.CytoGLMM

Bioconductor version: Development (3.23)

The CytoGLMM R package implements two multiple regression strategies: A bootstrapped generalized linear model (GLM) and a generalized linear mixed model (GLMM). Most current data analysis tools compare expressions across many computationally discovered cell types. CytoGLMM focuses on just one cell type. Our narrower field of application allows us to define a more specific statistical model with easier to control statistical guarantees. As a result, CytoGLMM finds differential proteins in flow and mass cytometry data while reducing biases arising from marker correlations and safeguarding against false discoveries induced by patient heterogeneity.

Author: Christof Seiler [aut, cre] ORCID iD ORCID: 0000-0001-8802-3642

Maintainer: Christof Seiler <christof.seiler at maastrichtuniversity.nl>

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

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("CytoGLMM")

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