Line plot of clone read fraction across multiple samples

This function creates a line plot of clone read fraction for the specified clones across multiple samples. The function can color the lines by groups of clones. If sum_readFraction is TRUE, the read fraction for each group will be summed and presented in one line.

Usage

plot_clone_size_across_samples(
  data,
  clones,
  chain = c("beta", "alpha"),
  pseudo = 1e-06,
  group_vec = NULL,
  sum_readFraction = TRUE,
  samples = NULL,
  return_data = FALSE,
  label_zero = FALSE,
  show_legend = TRUE,
  log_scale = TRUE,
  x_var = NULL
)

Arguments

data

a TIRTLseqDataSet object

clones

a list of nucleotide sequences of TCR clones

chain

the TCR chain used (default is "beta")

pseudo

the value of the pseudocount added to all read fractions (default is 10^-6)

group_vec

(optional) a vector of "groups" for the clones

sum_readFraction

if TRUE, plot the sum of read fractions of clones in each group. If FALSE, plot each clone with a separate line.

samples

(optional) which samples to use in the plot (default is all samples)

return_data

whether to return the data used for plotting (default is FALSE)

label_zero

whether to label zero on the y-axis (default is FALSE)

show_legend

whether to show the legend (default is TRUE)

log_scale

(optional) if TRUE, use log-scale for the y-axis (default is FALSE)

x_var

a column of metadata for grouping samples in the plot. The default is NULL, which considers each sample its own group.

Value

a ggplot object with a line plot of clone read fractions across samples.

See also

Other longitudinal: plot_sample_vs_sample()

Examples

folder = system.file("extdata/SJTRC_TIRTL_seq_longitudinal",
  package = "TIRTLtools")
sjtrc = load_tirtlseq(folder,
  meta_columns = c("marker", "timepoint", "version"), sep = "_",
  verbose = FALSE)

top_clones1 = sjtrc$data$cd8_tp1_v2$beta %>%
  dplyr::arrange(desc(readFraction)) %>%
  head(5) %>%
  magrittr::extract2("targetSequences") %>% as.character()
top_clones2 = sjtrc$data$cd8_tp2_v2$beta %>%
  dplyr::arrange(desc(readFraction)) %>%
  head(5) %>%
  magrittr::extract2("targetSequences") %>% as.character()

plot_clone_size_across_samples(sjtrc,
  clones = c(top_clones1, top_clones2), chain = "beta")