plotAbundances: Population frequencies across samples & clusters

In HelenaLC/CATALYST: Cytometry dATa anALYSis Tools

Population frequencies across samples & clusters

Description

Plots the relative population abundances of the specified clustering.

Usage

plotAbundances(
  x,
  k = "meta20",
  by = c("sample_id", "cluster_id"),
  group_by = "condition",
  shape_by = NULL,
  col_clust = TRUE,
  distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  linkage = c("average", "ward.D", "single", "complete", "mcquitty", "median",
    "centroid", "ward.D2"),
  k_pal = .cluster_cols
)

Arguments

x	a SingleCellExperiment.
k	character string specifying which clustering to use; valid values are names(cluster_codes(x)).
by	a character string specifying whether to plot frequencies by samples or clusters.
group_by	character string specifying a non-numeric cell metadata columnd to group by (determines the color coding); valid values are names(colData(x)) other than "sample_id" and "cluster_id".
shape_by	character string specifying a non-numeric cell metadata columnd to shape by; valid values are names(colData(x)) other than "sample_id" and "cluster_id".
col_clust	for by = "sample_id", specifies whether to hierarchically cluster samples and reorder them accordingly. When col_clust = FALSE, samples are ordered according to levels(x$sample_id) (or alphabetically, when x$sample_id is not a factor).
distance	character string specifying the distance metric to use for sample clustering; passed to dist
linkage	character string specifying the agglomeration method to use for sample clustering; passed to hclust.
k_pal	character string specifying the cluster color palette; ignored when by = "cluster_id". If less than nlevels(cluster_ids(x, k)) are supplied, colors will be interpolated via colorRampPalette.

Value

a ggplot 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)

Examples

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

# plot relative population abundances 
# by sample & cluster, respectively
plotAbundances(sce, k = "meta12")                  
plotAbundances(sce, k = "meta8", by = "cluster_id") 

# use custom cluster color palette
plotAbundances(sce, k = "meta10", 
  k_pal = c("lightgrey", "cornflowerblue", "navy"))

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