plotBar: Bar plot of canonical loadings from SCCA using PMD

In YunhuiQi/TestPMD: Post Selection Inference on Results from Penalized Matrix Decomposition (SCCA only)

Bar plot of canonical loadings from SCCA using PMD

Description

This function generates the bar plot of canonical loadings.

Usage

plotBar(data, loadings, qvalues, feature_groups = NULL, alpha = 0.05)

Arguments

data	Data matrix corresponding to the canonical loadings, samples are in rows, variables are in columns.
loadings	A named vector containing the estimated loadings.
qvalues	A vector containing qvalues for the canonical loadings.
feature_groups	A vector indicating the group information of variables.
alpha	Significance level, 0.05 by default.

Value

A bar plot of canonical loadings, colored by significance, if group is not NULL, background is colored by group.

Examples

library(TestPMD)
data("covid")
out <- PMA::CCA(standsdmu(covid$metabolite), standsdmu(covid$protein),
typex = "standard", typez="standard",
penaltyx = 0.9, penaltyz = 0.9, K = 3, standardize = FALSE, trace = FALSE)
pvalue <- CPTloading(X = covid$metabolite, Y = covid$protein, side = "X", K = 1, r = 10,
penalty = "Fixed", rho_x = 0.9, rho_y = 0.9, permutation_no = 100)
p_bar <- plotBar(data = covid$metabolite, loadings = out$u[,1], qvalues = pvalue,
feature_groups = NULL, alpha = 0.1)
p_bar

YunhuiQi/TestPMD documentation built on May 5, 2022, 8:23 p.m.