pvca.plot: Generate a Principal Variance Components Analysis (PVCA) plot

In msuprun/bbeaR: an R package and framework for epitope-specific antibody profiling

Description

Plotting the results of the pvcaBarcgAssess.bbea()

Usage

pvca.plot(pvcaObj, cex.percentage = 1, 
fname = NULL, ht = 4, wd = 5, 
title = fname,ylim=c(0,1), order=labels)

Arguments

pvcaObj

PVCA data

Author(s)

Maria Suprun, Randall J. Ellis, Mayte Suárez-Fariñas

Examples

data(Milk)
bbeaN <- MFI2nMFI(bbea, offset = 0.5, rmNeg = TRUE) 
eset <- nMFI2Eset(nMFI.object = bbeaN)
pvca.obj<-pvcaBatchAssess.bbea(eset,
threshold=0.8,
batch.factors=c('Plate','Treatment','Visit',"SUBJECT.ID"),  
include.inter='Treatment:Visit') 
pvca.plot(pvca.obj, fname='PVCA.Plate.Covariates', ht=4, wd=5.5,
          order=c('Plate','Treatment','Visit',
          'Treatment x Visit',"SUBJECT.ID",'resid'))

msuprun/bbeaR documentation built on Jan. 31, 2021, 6:49 p.m.