Description Usage Arguments Details Value See Also Examples
View source: R/diff_exp_plots.R
Stacked barplot of the number of differential TSSs or TSRs per comparison.
1 2 3 4 5 6 7 8 9 10 | plot_num_de(
experiment,
data_type = c("tss", "tsr"),
de_comparisons = "all",
log2fc_cutoff = 1,
fdr_cutoff = 0.05,
keep_unchanged = FALSE,
return_table = FALSE,
...
)
|
experiment |
TSRexploreR object. |
data_type |
Whether to plot numbers of differential TSSs ('tss') or TSRs ('tsr'). |
de_comparisons |
Character vector of differential expression comparisons to plot. |
log2fc_cutoff |
Differential features not meeting this |log2(fold change)| threshold will not be considered. |
fdr_cutoff |
Differential features not meeting this significance threshold will not be considered. |
keep_unchanged |
Whether to include (TRUE) unchanged features in the plot. |
return_table |
Return a table of results instead of a plot. |
... |
Additional arguments passed to geom_col. |
Generate a stacked barplot with the number of differential TSSs or TSRs per comparison.
'de_comparisons' are the names given to the comparisons from the 'comparison_name' argument of the 'differential_expression' function. 'log2fc_cutoff' and 'fdr_cutoff' are the log2(fold change) and FDR cutoffs used for determination of significance in the plot. 'keep_unchanged' controls whether non-significant feature numbers are included in the plot.
If 'keep_unchanged' is TRUE, a table with the numbers is returned instead of the ggplot. This may be useful if the exact numbers underlying the plot are required.
ggplot2 object of stacked barplot. If 'return_table' is TRUE, a data.frame with differentially expressed TSS/TSR numbers are returned.
fit_de_model
to fit a differential expression model.
differential_expression
to find differential TSSs or TSRs.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | data(TSSs)
sample_sheet <- data.frame(
sample_name=c(
sprintf("S288C_D_%s", seq_len(3)),
sprintf("S288C_WT_%s", seq_len(3))
),
file_1=NA, file_2=NA,
condition=c(rep("Diamide", 3), rep("Untreated", 3))
)
exp <- TSSs %>%
tsr_explorer(sample_sheet=sample_sheet) %>%
format_counts(data_type="tss")
diff_tss <- exp %>%
fit_de_model(data_type="tss", formula= ~condition, method="edgeR") %>%
differential_expression(
data_type="tss",
comparison_name="Diamide_vs_Untreated",
comparison_type="coef",
comparison=2)
p <- plot_num_de(diff_tss, data_type="tss")
|
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