Package: CytoGLMM 1.21.0

Christof Seiler

CytoGLMM: Conditional Differential Analysis for Flow and Mass Cytometry Experiments

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.

Authors:Christof Seiler [aut, cre]

CytoGLMM_1.21.0.tar.gz
CytoGLMM_1.21.0.zip(r-4.7)CytoGLMM_1.21.0.zip(r-4.6)CytoGLMM_1.21.0.zip(r-4.5)
CytoGLMM_1.21.0.tgz(r-4.6-any)CytoGLMM_1.21.0.tgz(r-4.5-any)
CytoGLMM_1.21.0.tar.gz(r-4.7-any)CytoGLMM_1.21.0.tar.gz(r-4.6-any)
CytoGLMM_1.21.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
CytoGLMM/json (API)
NEWS

# Install 'CytoGLMM' in R:
install.packages('CytoGLMM', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/christofseiler/cytoglmm/issues

Pkgdown/docs site:https://christofseiler.github.io

On BioConductor:CytoGLMM-1.21.0(bioc 3.24)CytoGLMM-1.20.0(bioc 3.23)

flowcytometryproteomicssinglecellcellbasedassayscellbiologyimmunooncologyregressionstatisticalmethodsoftware

6.03 score 3 stars 1 packages 2 scripts 322 downloads 4 mentions 11 exports 170 dependencies

Last updated from:b457ea4ed5. Checks:8 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE188
linux-devel-x86_64NOTE313
source / vignettesOK359
linux-release-x86_64NOTE336
macos-release-arm64NOTE130
macos-oldrel-arm64NOTE166
windows-develNOTE196
windows-releaseNOTE182
windows-oldrelNOTE195
wasm-releaseOK170

Exports:cytoflexmixcytoglmcytoglmmcytogroupcytostabgenerate_dataplot_heatmapplot_ldaplot_mdsplot_model_selectionplot_prcomp

Dependencies:abindbackportsbase64encBHbigmemorybigmemory.sriBiocParallelbootbroombslibcachemcarcarDatacaretclasscliclockclustercodetoolscolorspacecorrplotcowplotcpp11crosstalkdata.tabledendextendDerivdiagramdigestdoBydoParalleldplyrDTe1071ellipseemmeansestimabilityevaluatefactoextraFactoMineRfarverfastmapflashClustflexmixfontawesomeforeachforecastformatRFormulafracdifffsfutile.loggerfutile.optionsfuturefuture.applygenericsggplot2ggpubrggrepelggsciggsignifglobalsgluegowergridExtragtablehardhathighrhtmltoolshtmlwidgetsipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelavalazyevalleapslifecyclelistenvlme4lmtestlogginglubridatemagrittrMASSMatrixMatrixModelsmbestmemoisemgcvmicrobenchmarkmimeminqaModelMetricsmodelrmodeltoolsmultcompViewmvtnormnlmenloptrnnetnumDerivotelparallellypbkrtestpheatmappillarpkgconfigplyrpolynompROCprodlimprogressrpromisesproxypurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackrecipesreformulasreshape2rlangrmarkdownrpartrstatixS7sandwichsassscalesscatterplot3dshapesnowSparseMsparsevctrsSQUAREMstringistringrstrucchangesurvivaltibbletidyrtidyselecttimechangetimeDatetinytextzdburcautf8uuidvctrsviridisviridisLitewithrxfunyamlzoo

CytoGLMM Workflow

Rendered fromCytoGLMM.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2025-07-18
Started: 2019-02-27