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Bin Clones by Frequency or Proportion

Source: R/clonalBin.R
clonalBin.Rd

This function adds a clonal grouping variable (cloneSize) to the output of combineTCR(), combineBCR(), or combineExpression(). It calculates the clonal frequency and proportion, then bins clones into categories based on customizable thresholds. This is useful for categorizing clones prior to downstream analysis or visualization.

Usage

clonalBin(
  input.data,
  clone.call = NULL,
  chain = "both",
  group.by = NULL,
  proportion = TRUE,
  clone.size = NULL,
  cloneCall = NULL,
  cloneSize = NULL
)

Arguments

input.data

The product of combineTCR(), combineBCR(), or 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.

chain

The TCR/BCR chain to use. Use both to include both chains (e.g., TRA/TRB). Accepted values: TRA, TRB, TRG, TRD, IGH, IGL (for both light chains), both.

group.by

A column header in the metadata to group the analysis by (e.g., "sample", "treatment"). If NULL, data will be analyzed by list element.

proportion

Whether to use proportion (TRUE) or total frequency (FALSE) of the clone for binning.

clone.size

The bins for the grouping based on proportion or frequency. If proportion is FALSE and the clone.size values are not set high enough based on frequency, the upper limit of clone.size will be automatically updated.

cloneCall

[Deprecated] Use clone.call instead.

cloneSize

[Deprecated] Use clone.size instead.

Value

A list of data frames with clonal frequency, clonal proportion, and cloneSize columns added.

Author

Nick Borcherding

Examples

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

# Adding clonal bins with default settings (proportion-based)
combined <- clonalBin(combined)

# Adding clonal bins based on frequency
combined <- clonalBin(combined,
                      proportion = FALSE,
                      clone.size = c(Rare = 1, Small = 5, Medium = 20,
                                     Large = 100, Hyperexpanded = 500))

# Using a custom grouping variable
combined <- addVariable(combined,
                        variable.name = "Type",
                        variables = rep(c("B", "L"), 4))
combined <- clonalBin(combined, group.by = "Type")