plot_metric {scFeatureFilter} | R Documentation |
Use the output of get_mean_median
and produce a bar chart of mean
(or median) correlation coefficient per bin of features. Correlations against the
randomised top window are shown as dot-and-whiskers, and are used to estimate a
background level.
plot_metric(metric_table, selected_metric = c("mean", "median", "score"), show_ctrl = TRUE, control_color = "blue", show_threshold = TRUE, threshold = 2, threshold_color = "red", line_size = 1, annotate_lines = TRUE)
metric_table |
A |
selected_metric |
Which column in |
show_ctrl |
A boolean. Should a dashed line indicate the estimated background level? |
control_color |
The colour of the background dashed line (default to blue). |
show_threshold |
A boolean. Should a dashed line indicate the estimated threshold level? |
threshold |
How many times the background level should be multiplies do determine a threshold? Default to 2. The higher the more stringent. |
threshold_color |
The colour of the threshold dashed line (default to blue). |
line_size |
Thickness of the dashed lines. |
annotate_lines |
A boolean. Should the dashed lines be annotated? |
A ggplot2 plot.
library(magrittr) scData_hESC %>% calculate_cvs %>% define_top_genes(window_size = 100) %>% bin_scdata(window_size = 1000) %>% correlate_windows(n_random = 3) %>% get_mean_median %>% plot_metric