R: Plot differential heatmap

plotDiffHeatmap {CATALYST}

R Documentation

Plot differential heatmap

Description

Heatmaps summarizing differental abundance & differential state testing results.

Usage

plotDiffHeatmap(
  x,
  y,
  top_n = 20,
  all = FALSE,
  order = TRUE,
  th = 0.1,
  hm1 = TRUE,
  normalize = TRUE,
  row_anno = TRUE,
  col_anno = TRUE
)

Arguments

`x`	a `SingleCellExperiment`.
`y`	a `SummarizedExperiment` containing differential testing results as returned by one of `testDA_edgeR`, `testDA_voom`, `testDA_GLMM`, `testDS_limma`, or `testDS_LMM`. Alternatively, a list as returned by `diffcyt`.
`top_n`	numeric. Number of top clusters (if `type = "DA"`) or cluster-marker combinations (if `type = "DS"`) to display.
`all`	logical. Specifies whether all clusters or cluster-marker combinations should be displayed. If `TRUE`, `top_n` will be ignored.
`order`	logical. Should results be ordered by significance?
`th`	numeric. Threshold on adjusted p-values below which clusters (DA) or cluster-marker combinations (DS) should be considered significant.
`hm1`	logical. Specifies whether the left-hand side heatmap should be plotted.
`normalize`	logical. Specifies whether Z-score normalized values should be plotted in the right-hand side heatmap. If `y` contains DA analysis results, relative population abundances will be arcsine-square-root scaled prior to normalization.
`row_anno`	logical. Should a row annotation indicating whether cluster (DA) or cluster-marker combinations (DS) are significant, as well as adjusted p-values be included?
`col_anno`	logical. Should column annotations for each factor in `metadata(x)` be included?

Details

For DA tests, plotDiffHeatmap will display

median (arcsinh-transformed) cell-type marker expressions (across all samples)
cluster abundances by samples
row annotations indicating if detected clusteres are significant (i.e. adj. p-value >= th)

For DS tests, plotDiffHeatmap will display

median (arcsinh-transformed) cell-type marker expressions (across all samples)
median (arcsinh-transformed) cell-state marker expressions by sample
row annotations indicating if detected cluster-marker combinations are significant (i.e. adj. p-value >= th)

Value

a HeatmapList-class object.

Author(s)

Lukas M Weber and Helena Lucia Crowell helena.crowell@uzh.ch

Examples

# construct SCE & run clustering
data(PBMC_fs, PBMC_panel, PBMC_md)
sce <- prepData(PBMC_fs, PBMC_panel, PBMC_md)
sce <- cluster(sce)

## differential analysis
library(diffcyt)

# create design & constrast matrix
design <- createDesignMatrix(PBMC_md, cols_design=3:4)
contrast <- createContrast(c(0, 1, 0, 0, 0))

# test for
# - differential abundance (DA) of clusters
# - differential states (DS) within clusters

da <- diffcyt(sce, design = design, contrast = contrast, 
    analysis_type = "DA", method_DA = "diffcyt-DA-edgeR",
    clustering_to_use = "meta20")
    
ds <- diffcyt(sce, design = design, contrast = contrast, 
    analysis_type = "DS", method_DS = "diffcyt-DS-limma",
    clustering_to_use = "meta20")
    
# display test results for
# - top DA clusters
# - top DS cluster-marker combintations
plotDiffHeatmap(sce, da)
plotDiffHeatmap(sce, ds)

[Package CATALYST version 1.10.3 Index]