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Calculate Clonal Bias Towards a Cluster or Compartment

Source: R/clonalBias.R
clonalBias.Rd

The metric seeks to quantify how individual clones are skewed towards a specific cellular compartment or cluster. A clone bias of 1 - indicates that a clone is composed of cells from a single compartment or cluster, while a clone bias of 0 - matches the background subtype distribution. Please read and cite the following manuscript if using clonalBias().

Usage

clonalBias(
  sc.data,
  clone.call = NULL,
  split.by = NULL,
  group.by = NULL,
  n.boots = 20,
  min.expand = 10,
  export.table = NULL,
  palette = "inferno",
  cloneCall = NULL,
  exportTable = NULL,
  ...
)

Arguments

sc.data

The single-cell object after combineExpression().

clone.call

Defines the clonal sequence grouping. Accepted values are: gene (VDJC genes), nt (CDR3 nucleotide sequence), aa (CDR3 amino acid sequence), or strict (VDJC + nt). A custom column header can also be used.

split.by

The variable to use for calculating the baseline frequencies. For example, "Type" for lung vs peripheral blood comparison

group.by

A column header in the metadata that bias will be based on.

n.boots

number of bootstraps to downsample.

min.expand

clone frequency cut off for the purpose of comparison.

export.table

If TRUE, returns a data frame or matrix of the results instead of a plot.

palette

Colors to use in visualization - input any hcl.pals.

cloneCall

[Deprecated] Use clone.call instead.

exportTable

[Deprecated] Use export.table instead.

...

Additional arguments passed to the ggplot theme

Value

ggplot scatter plot with clone bias

Examples

# Making combined contig data
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)
scRep_example$Patient <- substring(scRep_example$orig.ident,1,3)

# Using clonalBias()
clonalBias(scRep_example,
              clone.call = "aa",
              split.by = "Patient",
              group.by = "seurat_clusters",
              n.boots = 5,
              min.expand = 2)
#> Smoothing formula not specified. Using: y ~ qss(x, lambda = 3)