plotDiffHeatmap {CATALYST}R Documentation

Plot differential heatmap

Description

Heatmaps summarizing differental abundance & differential state testing results.

Usage

plotDiffHeatmap(x, y, ...)

## S4 method for signature 'matrix,SummarizedExperiment'
plotDiffHeatmap(x, y, top_n = 20,
  all = FALSE, order = TRUE, th = 0.1, hm1 = TRUE,
  normalize = TRUE, row_anno = TRUE, col_anno = TRUE, ...)

## S4 method for signature 'daFrame,SummarizedExperiment'
plotDiffHeatmap(x, y,
  top_n = 20, all = FALSE, order = TRUE, th = 0.1, hm1 = TRUE,
  normalize = TRUE, row_anno = TRUE, col_anno = TRUE, ...)

## S4 method for signature 'SummarizedExperiment,SummarizedExperiment'
plotDiffHeatmap(x, y,
  top_n = 20, all = FALSE, order = TRUE, th = 0.1, hm1 = TRUE,
  normalize = TRUE, row_anno = TRUE, col_anno = TRUE, ...)

## S4 method for signature 'ANY,list'
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 daFrame or SummarizedExperiment.

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.

...

optional arguments.

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

For DS tests, plotDiffHeatmap will display

Value

a HeatmapList-class object.

Author(s)

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

Examples

# construct daFrame
data(PBMC_fs, PBMC_panel, PBMC_md)
re <- daFrame(PBMC_fs, PBMC_panel, PBMC_md)

# run clustering
re <- cluster(re)

## 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(re, design = design, contrast = contrast, 
    analysis_type = "DA", method_DA = "diffcyt-DA-edgeR",
    clustering_to_use = "meta20")
ds <- diffcyt(re, 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(re, da)
plotDiffHeatmap(re, ds)


[Package CATALYST version 1.8.3 Index]