Plot tree with results from multivariate testing

Usage

plotTreeTest(
  tree,
  low = "grey90",
  mid = "red",
  high = "darkred",
  xmax.scale = 1.5
)

Arguments

tree: phylo object storing tree
low: low color on gradient
mid: mid color on gradient
high: high color on gradient
xmax.scale: expand the x-axis by this factor so leaf labels fit in the plot

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 hierarchy and testing results
plotTreeTest(res)


# Extract results for first 3 nodes
res[1:3, ]
#> # A tibble: 3 × 9
#>    node    beta     se  stat pvalue n_features lambda method          FDR
#>   <int>   <dbl>  <dbl> <dbl>  <dbl>      <dbl>  <dbl> <chr>         <dbl>
#> 1     1 -0.105  0.0348 -3.01 0.0137          1   0.01 FE.empirical 0.0513
#> 2     2 -0.105  0.0337 -3.12 0.0114          1   0.01 FE.empirical 0.0513
#> 3     3 -0.0784 0.0351 -2.23 0.0509          1   0.01 FE.empirical 0.109