esm_manhattan_plot | R Documentation |
Manhattan plot of feature-cluster association p-values
esm_manhattan_plot(
esm,
neg_log_pval_thresh = 5,
threshold = NULL,
point_size = 5,
jitter_width = 0.1,
jitter_height = 0.1,
text_size = 15,
plot_title = NULL,
hide_x_labels = FALSE,
bonferroni_line = FALSE
)
esm |
Extended solutions data frame storing associations between features
and cluster assignments. See |
neg_log_pval_thresh |
Threshold for negative log p-values. |
threshold |
P-value threshold to plot dashed line at. |
point_size |
Size of points in the plot. |
jitter_width |
Width of jitter. |
jitter_height |
Height of jitter. |
text_size |
Size of text in the plot. |
plot_title |
Title of the plot. |
hide_x_labels |
If TRUE, hides x-axis labels. |
bonferroni_line |
If TRUE, plots a dashed black line at the Bonferroni-corrected equivalent of the p-value threshold. |
A Manhattan plot (class "gg", "ggplot") showing the association p-values of features against each solution in the provided solutions data frame.
# full_dl <- data_list(
# list(subc_v, "subcortical_volume", "neuroimaging", "continuous"),
# list(income, "household_income", "demographics", "continuous"),
# list(pubertal, "pubertal_status", "demographics", "continuous"),
# list(anxiety, "anxiety", "behaviour", "ordinal"),
# list(depress, "depressed", "behaviour", "ordinal"),
# uid = "unique_id"
# )
#
# dl <- full_dl[1:3]
# target_dl <- full_dl[4:5]
#
# set.seed(42)
# sc <- snf_config(
# dl = dl,
# n_solutions = 20,
# min_k = 20,
# max_k = 50
# )
#
# sol_df <- batch_snf(dl, sc)
#
# ext_sol_df <- extend_solutions(
# sol_df,
# dl = dl,
# target = target_dl,
# min_pval = 1e-10 # p-values below 1e-10 will be thresholded to 1e-10
# )
#
# esm_manhattan <- esm_manhattan_plot(
# ext_sol_df[1:5, ],
# neg_log_pval_thresh = 5,
# threshold = 0.05,
# point_size = 3,
# jitter_width = 0.1,
# jitter_height = 0.1,
# plot_title = "Feature-Solution Associations",
# text_size = 14,
# bonferroni_line = TRUE
# )
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