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DESCRIPTION
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DESCRIPTION
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Package: cytofWorkflow
Title: CyTOF workflow: differential discovery in high-throughput
high-dimensional cytometry datasets
Version: 1.0.4
Date: 2017-10-19
Authors@R: c(person(role=c("aut", "cre"), "Malgorzata", "Nowicka",
email = "gosia.nowicka.uzh@gmail.com"), person(role=c("aut"), "Mark
D.", "Robinson", email = "mark.robinson@imls.uzh.ch"))
Description: High dimensional mass and flow cytometry (HDCyto)
experiments have become a method of choice for high throughput
interrogation and characterization of cell populations. Here,
we present an R-based pipeline for differential analyses of
HDCyto data, largely based on Bioconductor packages. We
computationally define cell populations using FlowSOM
clustering, and facilitate an optional but reproducible
strategy for manual merging of algorithm-generated clusters.
Our workflow offers different analysis paths, including
association of cell type abundance with a phenotype or changes
in signaling markers within specific subpopulations, or
differential analyses of aggregated signals. Importantly, the
differential analyses we show are based on regression
frameworks where the HDCyto data is the response; thus, we are
able to model arbitrary experimental designs, such as those
with batch effects, paired designs and so on. In particular, we
apply generalized linear mixed models to analyses of cell
population abundance or cell-population-specific analyses of
signaling markers, allowing overdispersion in cell count or
aggregated signals across samples to be appropriately modeled.
To support the formal statistical analyses, we encourage
exploratory data analysis at every step, including quality
control (e.g. multi-dimensional scaling plots), reporting of
clustering results (dimensionality reduction, heatmaps with
dendrograms) and differential analyses (e.g. plots of
aggregated signals).
Depends: R (>= 3.4.0)
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
biocViews: WorkflowStep, SingleCell
VignetteBuilder: knitr
Imports: BiocStyle, knitr, readxl, matrixStats, flowCore, ggplot2, ggridges,
reshape2, dplyr, limma, ggrepel, RColorBrewer, pheatmap, ComplexHeatmap,
FlowSOM, ConsensusClusterPlus, Rtsne, cowplot, lme4, multcomp
Suggests: knitcitations
NeedsCompilation: no
Workflow: true
URL: https://github.com/gosianow/cytofWorkflow
BugReports: https://github.com/gosianow/cytofWorkflow/issues