clonalOccupy: Visualize the number of single cells with cloneSizes by...

In ncborcherding/scRepertoire: A toolkit for single-cell immune receptor profiling

Visualize the number of single cells with cloneSizes by cluster

Description

View the count of clones frequency group in Seurat or SCE object meta data after combineExpression. The visualization will take the new meta data variable "cloneSize" and plot the number of cells with each designation using a secondary variable, like cluster. Credit to the idea goes to Drs. Carmona and Andreatta and their work with ProjectTIL.

Usage

clonalOccupy(
  sc.data,
  x.axis = "ident",
  label = TRUE,
  facet.by = NULL,
  proportion = FALSE,
  na.include = FALSE,
  exportTable = FALSE,
  palette = "inferno"
)

Arguments

sc.data	The single-cell object after combineExpression.
x.axis	The variable in the meta data to graph along the x.axis.
label	Include the number of clone in each category by x.axis variable.
facet.by	The column header used for faceting the graph.
proportion	Convert the stacked bars into relative proportion.
na.include	Visualize NA values or not.
exportTable	Exports a table of the data into the global environment in addition to the visualization.
palette	Colors to use in visualization - input any hcl.pals.

Value

Stacked bar plot of counts of cells by clone frequency group

Examples

#Getting the combined contigs
combined <- combineTCR(contig_list, 
                        samples = c("P17B", "P17L", "P18B", "P18L", 
                                    "P19B","P19L", "P20B", "P20L"))

#Getting a sample of a Seurat object
scRep_example <- get(data("scRep_example"))

#Using combineExpresion()
scRep_example <- combineExpression(combined, scRep_example)

#Using clonalOccupy
clonalOccupy(scRep_example, x.axis = "ident")
table <- clonalOccupy(scRep_example, x.axis = "ident", exportTable = TRUE)

ncborcherding/scRepertoire documentation built on April 27, 2024, 8:34 p.m.