plot_gene_usage: Plot V(D)J segment usage
In rnabioco/djvdj: A collection of single-cell V(D)J tools

plot_gene_usage

R Documentation

Plot V(D)J segment usage

Description

Plot the usage of different V(D)J segments for each cell cluster. The usage of two V(D)J segments can also be plotted for a single chain.

Usage

plot_gene_usage(
  input,
  data_cols,
  cluster_col = NULL,
  group_col = NULL,
  method = NULL,
  units = "percent",
  genes = 20,
  return_list = FALSE,
  plot_colors = NULL,
  plot_lvls = NULL,
  trans = "identity",
  rotate_labels = FALSE,
  panel_nrow = NULL,
  show_points = TRUE,
  show_zeros = TRUE,
  n_label = NULL,
  p_label = c(value = 0.05),
  p_method = NULL,
  p_file = NULL,
  label_params = list(),
  ...,
  chain = NULL,
  chain_col = global$chain_col,
  sep = global$sep
)

Arguments

`input`	Object containing V(D)J data. If a data.frame is provided, the cell barcodes should be stored as row names.
`data_cols`	meta.data column containing genes for each clonotype, provide a vector with two column names to plot paired usage of genes
`cluster_col`	meta.data column containing cell clusters to use for calculating gene usage
`group_col`	meta.data column to use for grouping cluster IDs present in cluster_col. This is useful when there are multiple replicates or patients for each treatment condition.
`method`	Method to use for plotting, possible values are: 'bar', create a bargraph, this is the default when a single column is passed to the data_cols argument 'boxplot', create boxplots, this can only be used when group_col is provided 'heatmap', create a heatmap, this is the default when two columns are passed to the data_cols argument 'circos', create a circos plot, this requires two columns to be provided to the data_cols argument
`units`	Units to plot on the y-axis, either 'frequency' or 'percent'
`genes`	An integer specifying the number of genes to plot, or a vector giving the names of genes to include.
`return_list`	Should a list of plots be returned, if FALSE plots will be combined and arranged into panels
`plot_colors`	Character vector containing colors to use for plot. If a bar graph is created this will specify how to color cell clusters. For a heatmap, these colors will be used to generate the color gradient.
`plot_lvls`	Levels to use for ordering clusters
`trans`	Transformation to use when plotting segment usage, e.g. 'log10'. By default values are not transformed, refer to `ggplot2::continuous_scale()` for more options.
`rotate_labels`	Should labels on circos plot be rotated to reduce overlapping text
`panel_nrow`	The number of rows to use for arranging plots when return_list is FALSE
`show_points`	If `TRUE` data points will be shown on boxplots, the point size can be adjusted using the `point.size` parameter
`show_zeros`	If `TRUE` cell labels that are missing from a cluster will still be shown on the plot
`n_label`	Location on plot where n label should be added, this is only applicable when `method` is 'bar' and can be any combination of the following: 'corner', display the total number of cells plotted in the top right corner, the position of the label can be modified by passing `x` and `y` specifications with the `label_params` argument 'legend', display the number of cells plotted for each group shown in the plot legend 'none', do not display the number of cells plotted
`p_label`	Specification indicating how p-values should be labeled on plot, this can one of the following: 'none', do not display p-values 'all', show p-values for all groups A named vector providing p-value cutoffs and labels to display, e.g. `c('' = 0.05, '' = 0.01, '**' = 0.001)`. The keyword 'value' can be used to display the p-value for those less than a certain cutoff, e.g. `c(value = 0.05, ns = Inf)` will show significant p-values, all others will be labeled 'ns'.
`p_method`	Method to use for calculating p-values. By default when comparing two groups a t-test will be performed, when comparing more than two groups the Kruskal-Wallis test will be used. p-values are adjusted for multiple testing using Bonferroni correction. Possible methods include: 't', two sample t-test performed with `stats::t.test()` 'wilcox', Wilcoxon rank sum test performed with `stats::wilcox.test()` 'kruskal', Kruskal-Wallis test performed with `stats::kruskal.test()`
`p_file`	File path to save table containing p-values for each comparison.
`label_params`	Named list providing additional parameters to modify n label aesthetics, e.g. list(size = 4, color = "red")
`...`	Additional arguments to pass to plotting function, `ggplot2::geom_col()` for bargraph, `ggplot2::geom_tile()` for heatmap, `circlize::chordDiagram()` for circos plot
`chain`	Chain to use for calculating gene usage, set to NULL to include all chains
`chain_col`	meta.data column containing chains for each cell
`sep`	Separator used for storing per-chain V(D)J data for each cell

Value

ggplot object

Examples

# Plot V(D)J segment usage for all cells
plot_gene_usage(
  vdj_sce,
  data_cols = "v_gene"
)

# Plot gene usage separately for cell clusters
plot_gene_usage(
  vdj_sce,
  data_cols = "v_gene",
  cluster_col = "orig.ident"
)

# Plot gene usage for a specific chain
plot_gene_usage(
  vdj_sce,
  data_cols = "v_gene",
  chain = c("IGH", "IGK")
)

# Plot paired usage of V(D)J segments
plot_gene_usage(
  vdj_sce,
  data_cols = c("v_gene", "j_gene"),
  type = "circos"
)

# Specify colors to use for each cell cluster
plot_gene_usage(
  vdj_sce,
  data_cols = "v_gene",
  cluster_col = "orig.ident",
  plot_colors = c(avid_2 = "blue", avid_1 = "green")
)

# Specify order to use for plotting cell clusters
plot_gene_usage(
  vdj_sce,
  data_cols = "v_gene",
  cluster_col = "orig.ident",
  plot_lvls = c("avid_2", "avid_1")
)

# Specify certain V(D)J genes to include in plot
plot_gene_usage(
  vdj_sce,
  data_cols = "v_gene",
  vdj_genes = c("IGKV5-43", "IGLV1", "IGHV1-64")
)

# Specify the number of top V(D)J genes to include in plot
plot_gene_usage(
  vdj_sce,
  data_cols = "v_gene",
  genes = 10
)

rnabioco/djvdj documentation built on Oct. 24, 2023, 7:33 p.m.