Forest plot

Forest plot

Forest plot of effect size estimates at the leaves of the tree

Usage

plotForest(x, ...)

# S4 method for treedata
plotForest(x, ..., hide = FALSE)

Arguments

x

result from treeTest()

...

other arguments

hide

hide rownames and legend

Examples

library(variancePartition)

# Load cell counts, clustering and metadata
# from Kang, et al. (2018) https://doi.org/10.1038/nbt.4042
data(IFNCellCounts)

# Apply crumblr transformation
cobj <- crumblr(df_cellCounts)

# Use dream workflow to analyze each cell separately
fit <- dream(cobj, ~ StimStatus + ind, info)
fit <- eBayes(fit)

# Perform multivariate test across the hierarchy
res <- treeTest(fit, cobj, hcl, coef = "StimStatusstim")

# Plot log fold changes from coef
plotForest(res)