Summarizes and Visualizes Gene Usage — percentGeneUsage • scRepertoire

This function quantifies and visualizes the usage of V, D, or J genes, or gene pairings across T or B cell clones.

percentGeneUsage(
  input.data,
  chain = "TRB",
  genes = "TRBV",
  group.by = NULL,
  order.by = NULL,
  summary.fun = c("percent", "proportion", "count"),
  plot.type = "heatmap",
  exportTable = FALSE,
  palette = "inferno",
  ...
)

vizGenes(
  input.data,
  x.axis = "TRBV",
  y.axis = NULL,
  group.by = NULL,
  plot = "heatmap",
  order.by = NULL,
  summary.fun = c("percent", "proportion", "count"),
  exportTable = FALSE,
  palette = "inferno"
)

percentGenes(
  input.data,
  chain = "TRB",
  gene = "Vgene",
  group.by = NULL,
  order.by = NULL,
  exportTable = FALSE,
  summary.fun = c("percent", "proportion", "count"),
  palette = "inferno"
)

percentVJ(
  input.data,
  chain = "TRB",
  group.by = NULL,
  order.by = NULL,
  summary.fun = c("percent", "proportion", "count"),
  exportTable = FALSE,
  palette = "inferno"
)

Arguments

input.data: The product of combineTCR(), combineBCR(), or combineExpression().
chain: The TCR/BCR chain to use. Accepted values: TRA, TRB, TRG, TRD, IGH, IGL (for both light chains)
genes: A character vector specifying the gene loci to analyze. Can be a single gene e.g., "TRBV" or "IGHJ" or a pair for genes analysis (e.g., c("TRBV", "TRAV"), or "TRBV", "TRBJ").
group.by: A column header in the metadata or lists to group the analysis by (e.g., "sample", "treatment"). If NULL, data will be analyzed as by list element or active identity in the case of single-cell objects.
order.by: A character vector defining the desired order of elements of the group.by variable. Alternatively, use alphanumeric to sort groups automatically.
summary.fun: Character string choosing the summary statistic - "percent" (default), "proportion", or "count".
plot.type: The type of plot to return: "heatmap" (default for paired loci, also available for single loci), or "barplot" (for single loci).
exportTable: 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.
...: Additional arguments passed to the ggplot theme
x.axis: Gene segments to separate the x-axis, such as TRAV, TRBD, IGKJ.
y.axis: Variable to separate the y-axis, can be both categorical or other gene gene segments, such as TRAV, TRBD, IGKJ.
plot: The type of plot to return - heatmap or barplot.
gene: Vgene, Dgene or Jgene

Value

A ggplot object displaying a heatmap or bar plot of gene usage. If exportTable = TRUE, a matrix or data frame of the raw data is returned.

Examples

# Making combined contig data
combined <- combineTCR(contig_list, 
                        samples = c("P17B", "P17L", "P18B", "P18L", 
                                    "P19B","P19L", "P20B", "P20L"))
                                    
# Visualize single gene (TRBV) usage as a heatmap, grouped by sample
percentGeneUsage(combined,
                 genes = "TRBV",
                 group.by = "sample",
                 plot.type = "heatmap",
                 summary.fun = "percent")


# Visualize single gene (TRBV) usage as a barplot, grouped by sample
percentGeneUsage(combined,
                 genes = "TRBV",
                 group.by = "sample",
                 plot.type = "barplot",
                 summary.fun = "count")


# Visualize paired gene (TRBV-TRBJ) usage as a heatmap
percentGeneUsage(combined[1:2],
                 genes = c("TRBV", "TRBJ"),
                 group.by = "sample",
                 plot.type = "heatmap",
                 summary.fun = "proportion")


# Export the raw data table for single gene usage
trbv_usage_table <- percentGeneUsage(combined,
                                     genes = "TRBV",
                                     group.by = "sample",
                                     exportTable = TRUE,
                                     summary.fun = "count")

# Export the raw data table for paired gene usage
trbv_trbj_usage_table <- percentGeneUsage(combined,
                                          genes = c("TRBV", "TRBJ"),
                                          group.by = "sample",
                                          exportTable = TRUE,
                                          summary.fun = "percent")


# Visualize paired gene (TRAV-TRAJ) usage as a heatmap
vizGenes(combined[1:2],
         x.axis = "TRAV",
         y.axis = "TRAJ",
         group.by = "sample",
         summary.fun = "count")


# Visualize cross-chain gene pairing (TRBV-TRAV)
vizGenes(combined[1:2],
         x.axis = "TRBV",
         y.axis = "TRAV",
         group.by = "sample",
         summary.fun = "percent")



# Quantify and visualize TRA V-gene usage as a heatmap
percentGenes(combined,
             chain = "TRA",
             gene = "Vgene",
             group.by = "sample",
             summary.fun = "percent")


# Quantify TRA J-gene usage and export the table
traj_usage_table <- percentGenes(combined,
                                 chain = "TRA",
                                 gene = "Jgene",
                                 group.by = "sample",
                                 exportTable = TRUE,
                                 summary.fun = "count")

# Quantify and visualize TRB V-J gene pairings as a heatmap
percentVJ(combined[1:2],
          chain = "TRB",
          group.by = "sample",
          summary.fun = "percent")


# 2. Quantify TRA V-J gene pairings and export the table
trav_traj_table <- percentVJ(combined,
                             chain = "TRA",
                             group.by = "sample",
                             exportTable = TRUE,
                             summary.fun = "proportion")