Plots for SHM based on MIXCR output generated using the VDJ_call_MIXCR function and appended to the VDJ.GEX.matrix.output
VDJ_plot_SHM(
VDJ.mixcr.matrix,
group.by,
quantile.label,
point.size,
mean.line.color,
stats.to.console,
platypus.version
)Output dataframe from the VDJ_call_MIXCR function or a dataframe generated using the VDJ_GEX_matrix function and supplemented with MIXCR information
Character. Defaults to "sample_id". Column name of VDJ.matrix to split VDJ.matrix by. For each unique entry in that column a set of plots will be generated. This can be useful to plot SHM by expansion or by transcriptomics-derived clusters
Numeric. Defaults to 0.9. Which points to label in the SHM scatterplot. If set to 0.9, the top 10% of cells by SHM number will be labelled. If ggrepel throws a warning, concerning overlap it is recommended to attempt to lable less points to avoid cluttering
Size of points in plots. Passed to geom_jitter()
Color of mean bar in dotplots. Passed to geom_errorbar()
Boolean. Defaults to FALSE. Prints basic statistics (AOV \+ post hoc test) to console
Character. Only "v3" available.
Returns a list of ggplot objects. out\[\[1\]\] is a boxplot comparing SHM by group.by. out\[\[2\]\] to out\[\[n\]\] are plots for each group that visualize VDJ and VJ SHM distribution for each group. Data for any plot can be accessed via out \[\[any\]\]$data
#Simulating SHM data
small_vgm <- Platypus::small_vgm
small_vgm[[1]]$VDJ_SHM <- as.integer(rnorm(nrow(small_vgm[[1]]), mean = 5, sd = 3))
small_vgm[[1]]$VJ_SHM <- as.integer(rnorm(nrow(small_vgm[[1]]), mean = 5, sd = 3))
#Standard plots
SHM_plots <- VDJ_plot_SHM(VDJ = small_vgm[[1]]
, group.by = "sample_id", quantile.label = 0.9)
#Group by transcriptional cluster and label only top 1\%
SHM_plots <- VDJ_plot_SHM(VDJ = small_vgm[[1]]
, group.by = "seurat_clusters", quantile.label = 0.99)