getCirclize | R Documentation |
This function will take the meta data from the product of
combineExpression()
and generate a relational data frame to
be used for a chord diagram. Each cord will represent the number of
clone unique and shared across the multiple group.by variable.
If using the downstream circlize R package, please read and cite the
following manuscript.
If looking for more advance ways for circular visualizations, there
is a great cookbook
for the circlize package.
getCirclize(
sc.data,
cloneCall = "strict",
group.by = NULL,
proportion = FALSE,
include.self = TRUE
)
sc.data |
The single-cell object after |
cloneCall |
How to call the clone - VDJC gene (gene), CDR3 nucleotide (nt), CDR3 amino acid (aa), VDJC gene + CDR3 nucleotide (strict) or a custom variable in the data. |
group.by |
The group header for which you would like to analyze the data. |
proportion |
Calculate the relationship unique clones (proportion = FALSE) or normalized by proportion (proportion = TRUE) |
include.self |
Include counting the clones within a single group.by comparison |
A data frame of shared clones between groups formated for chordDiagram
Dillon Corvino, Nick Borcherding
#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"))
scRep_example <- combineExpression(combined,
scRep_example)
#Getting data frame output for Circlize
circles <- getCirclize(scRep_example,
group.by = "seurat_clusters")
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