mbecPCAPlot: PCA plotting function

In buschlab/MBECS: Evaluation and correction of batch effects in microbiome data-sets

Description

Takes data.frame from mbecPCA and produces a ggplot2 object.

Usage

mbecPCAPlot(plot.df, metric.df, model.vars, pca.axes)

Arguments

plot.df	Data.frame containing principal component data.
metric.df	Data.frame containing covariate data.
model.vars	two covariates of interest to select by first variable selects panels and second one determines coloring.
pca.axes	NMumerical two-piece vector that selects PCs to plot.

Value

ggplot2 object

Examples

# This will return a paneled plot that shows results for the variance
# assessment.
pca.df <- mbecPCA(input.obj=dummy.mbec,
model.vars=c('group','batch'), pca.axes=c(1,2), return.data=TRUE)
plot.pca <- mbecPCAPlot(plot.df=pca.df[[1]], metric.df=pca.df[[2]],
model.vars=c('group','batch'), pca.axes=c(1,2))

buschlab/MBECS documentation built on Jan. 21, 2022, 1:27 a.m.