plot_shift_count: Shift Count Plot
In rpolicastro/tsrexplorer: TSS and TSR Analysis

Description Usage Arguments Details Value See Also Examples

Generate a stacked barplot for the number of TSRs with significant upstream and/or downstream shifts for each comparison.

plot_shift_count(
  experiment,
  samples = "all",
  ncol = 3,
  return_table = FALSE,
  ...
)

`experiment`	TSRexploreR object.
`samples`	A vector of sample names to analyze.
`ncol`	Integer specifying the number of columns to arrange multiple plots.
`return_table`	Return a table of results instead of a plot.
`...`	Arguments passed to geom_col.

The 'tss_shifting' function uses the earth mover's score (EMS) to assess shifts in TSS distribution in consensus TSRs between two samples. This function generates a stacked barplot of the number of upstream and downstream shifts in each comparison.

If 'return_table' is TRUE, a data.frame is returned that provides the underlying counts for each sample.

ggplot2 of stacked barplot of shifted TSS clusters. If 'return_table' is TRUE, a data.frame of underlying counts is returned instead.

tss_shift For TSS cluster shifting calculation.

data(TSSs)
assembly <- system.file("extdata", "S288C_Assembly.fasta", package = "TSRexploreR")
samples <- data.frame(
  sample_name=c(sprintf("S288C_D_%s", seq_len(3)), sprintf("S288C_WT_%s", seq_len(3))),
  file_1=rep(NA, 6), file_2=rep(NA, 6),
  condition=c(rep("Diamide", 3), rep("Untreated", 3))
)

exp <- TSSs %>%
  tsr_explorer(sample_sheet=samples, genome_assembly=assembly) %>%
  format_counts(data_type="tss") %>%
  tss_clustering(threshold=3) %>%
  merge_samples(data_type="tss", merge_group="condition") %>%
  merge_samples(data_type="tsr", merge_group="condition") %>%
  tss_shift(
    sample_1=c(TSS="S288C_WT_1", TSR="S288C_WT_1"),
    sample_2=c(TSS="S288C_D_1", TSR="S288C_D_1"),
    comparison_name="Untreated_vs_Diamide",
    max_distance = 100, min_threshold = 10, n_resamples = 1000L
  )
  
p <- plot_shift_count(exp)