DOI: 10.18129/B9.bioc.CytoGLMM  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see CytoGLMM.

Conditional Differential Analysis for Flow and Mass Cytometry Experiments

Bioconductor version: 3.17

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]

Maintainer: Christof Seiler <christof.seiler at>

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biocViews CellBasedAssays, CellBiology, FlowCytometry, ImmunoOncology, Proteomics, Regression, SingleCell, Software, StatisticalMethod
Version 1.8.0
In Bioconductor since BioC 3.13 (R-4.1) (2.5 years)
License LGPL-3
Imports stats, methods, BiocParallel, RColorBrewer, cowplot, doParallel, dplyr, factoextra, flexmix, ggplot2, magrittr, mbest, pheatmap, stringr, strucchange, tibble, ggrepel, MASS, logging, Matrix, tidyr, caret, rlang, grDevices
Suggests knitr, rmarkdown, testthat, BiocStyle
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