plotMultiHeatmap: Multi-panel expression & frequency heatmaps

In HelenaLC/CATALYST: Cytometry dATa anALYSis Tools

Multi-panel expression & frequency heatmaps

Description

Combines expression and frequency heatmaps from plotExprHeatmap and plotFreqHeatmap, respectively, into a HeatmapList.

Usage

plotMultiHeatmap(
  x,
  hm1 = "type",
  hm2 = "abundances",
  k = "meta20",
  m = NULL,
  assay = "exprs",
  fun = c("median", "mean", "sum"),
  scale = c("first", ifelse(hm2 == "state", "first", "last")),
  q = c(0.01, ifelse(hm2 == "state", 0.01, 0)),
  normalize = TRUE,
  row_anno = TRUE,
  col_anno = TRUE,
  row_clust = TRUE,
  col_clust = c(TRUE, hm2 == "state"),
  row_dend = TRUE,
  col_dend = c(TRUE, hm2 == "state"),
  bars = FALSE,
  perc = FALSE,
  hm1_pal = rev(brewer.pal(11, "RdYlBu")),
  hm2_pal = if (isTRUE(hm2 == "abundances")) rev(brewer.pal(11, "PuOr")) else hm1_pal,
  k_pal = .cluster_cols,
  m_pal = k_pal,
  distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  linkage = c("average", "ward.D", "single", "complete", "mcquitty", "median",
    "centroid", "ward.D2")
)

Arguments

x	a SingleCellExperiment.
hm1	character string specifying which features to include in the 1st heatmap; valid values are "type"/"state" for type/state_markers(x) if rowData(x)$marker_class have been specified; a subset of rownames(x); NULL to use all features; and FALSE to omit the 1st heatmap altogether.
hm2	character string. Specifies the right-hand side heatmap. One of: "abundances": cluster frequencies across samples "state": median state-marker expressions across clusters (analogous to the left-hand side heatmap) a character string/vector corresponding to one/multiple marker(s): median marker expressions across samples and clusters
k	character string specifying which; valid values are names(cluster_codes(x)).
m	character string specifying a metaclustering to include as an annotation when row_anno = TRUE.
assay	character string specifying which assay data to use; valid values are assayNames(x).
fun	character string specifying the function to use as summary statistic.
scale	character string specifying the scaling strategy; for expression heatmaps (see plotExprHeatmap).
q	single numeric in [0,1) determining the quantiles to trim when scale != "never".
normalize	logical specifying whether to Z-score normalize cluster frequencies across samples; see plotFreqHeatmap.
row_anno, col_anno	logical specifying whether to include row/column annotations for cell metadata variables and clustering(s); see plotExprHeatmap and plotFreqHeatmap.
row_clust, col_clust	logical specifying whether rows/columns should be hierarchically clustered and re-ordered accordingly.
row_dend, col_dend	logical specifying whether to include the row/column dendrograms.
bars	logical specifying whether to include a barplot of cell counts per cluster as a right-hand side row annotation.
perc	logical specifying whether to display percentage labels next to bars when bars = TRUE.
hm1_pal, hm2_pal	character vector of colors to interpolate for each heatmap.
k_pal, m_pal	character vector of colors to use for cluster and merging row annotations. If less than nlevels(cluster_ids(x, k/m)) values are supplied, colors will be interpolated via colorRampPalette.
distance	character string specifying the distance metric to use in dist for hierarchical clustering.
linkage	character string specifying the agglomeration method to use in hclust for hierarchical clustering.

Details

In its 1st panel, plotMultiHeatmap will display (scaled) type-marker expressions aggregated by cluster (across all samples). Depending on argument hm2, the 2nd panel will contain one of:

hm2 = "abundances"

relataive cluster abundances by cluster & sample

hm2 = "state"

aggregated (scaled) state-marker expressions by cluster (across all samples; analogous to panel 1)

hm2 %in% rownames(x)

aggregated (scaled) marker expressions by cluster & sample

Value

a HeatmapList-class object.

Author(s)

Helena L Crowell [e-mail]

References

Nowicka M, Krieg C, Crowell HL, Weber LM et al. CyTOF workflow: Differential discovery in high-throughput high-dimensional cytometry datasets. F1000Research 2017, 6:748 (doi: 10.12688/f1000research.11622.1)

See Also

plotAbundances, plotExprHeatmap, plotFreqHeatmap

Examples

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

# state-markers + cluster frequencies
plotMultiHeatmap(sce, 
  hm1 = "state", hm2 = "abundances", 
  bars = TRUE, perc = TRUE)

# type-markers + marker of interest
plotMultiHeatmap(sce, hm2 = "pp38", k = "meta12", m = "meta8")

# both, type- & state-markers
plotMultiHeatmap(sce, hm2 = "state")

# plot markers of interest side-by-side 
# without left-hand side heatmap
plotMultiHeatmap(sce, k = "meta10", 
  hm1 = NULL, hm2 = c("pS6", "pNFkB", "pBtk"), 
  row_anno = FALSE, hm2_pal = c("white", "black"))

HelenaLC/CATALYST documentation built on Oct. 16, 2024, 12:21 a.m.