mbecPVCAStatsPlot: Plot Proportion of Variance for PVCA

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

Description

Covariate-Variances as modeled by PVCA will be displayed as box-plots. It works with the output of 'mbecVarianceStats()' for the method 'pvca'. Format of this output is a data.frame that contains a column for every model variable and as many rows as there are features (OTUs, Genes, ..). Multiple frames may be used as input by putting them into a list - IF the data.frames contain a column named 'type', this function will use 'facet_grid()' to display side-by-side panels to enable easy comparison.

Usage

mbecPVCAStatsPlot(pvca.obj)

Arguments

pvca.obj,

output of 'mbecVarianceStats' with method pvca

Value

A ggplot2 box-plot object.

Examples

# This will return a paneled plot that shows results for the variance
# assessment.
df.var.pvca <- mbecModelVariance(input.obj=dummy.mbec,
model.vars=c('batch','group'), method='pvca', type='clr')
plot.pvca <- mbecPVCAStatsPlot(pvca.obj=df.var.pvca)

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