plotRespFun: Plot the non-parametric response functions

In RCM: Fit row-column association models with the negative binomial distribution for the microbiome

Description

Plots a number of response functions over the observed range of the environmental score. If no taxa are provided those who react most strongly to the environmental score are chosen.

Usage

plotRespFun(
  RCM,
  taxa = NULL,
  type = "link",
  logTransformYAxis = FALSE,
  addSamples = TRUE,
  samSize = NULL,
  Dim = 1L,
  nPoints = 100L,
  labSize = 2.5,
  yLocVar = NULL,
  yLocSam = NULL,
  Palette = "Set3",
  addJitter = FALSE,
  nTaxa = 9L,
  angle = 90,
  legendLabSize = 15,
  legendTitleSize = 16,
  axisLabSize = 14,
  axisTitleSize = 16,
  lineSize = 0.75,
  ...
)

Arguments

RCM	an RCM object
taxa	a character vector of taxa to be plotted
type	a character string, plot the response function on the log-scale ('link') or the abundance scale 'response', similar to predict.glm().
logTransformYAxis	a boolean, should y-axis be log transformed?
addSamples	a boolean, should sample points be shown?
samSize	a sample variable name or a vector of length equal to the number of samples, for the sample sizes
Dim	An integer, the dimension to be plotted
nPoints	the number of points to be used to plot the lines
labSize	the label size for the variables
yLocVar	the y-location of the variables, recycled if necessary
yLocSam	the y-location of the samples, recycled if necessary
Palette	which color palette to use
addJitter	A boolean, should variable names be jittered to make them more readable
nTaxa	an integer, number of taxa to plot
angle	angle at which variable labels should be turned
legendLabSize	size of the legend labels
legendTitleSize	size of the legend title
axisLabSize	size of the axis labels
axisTitleSize	size of the axis title
lineSize	size of the response function lines
...	Other argumens passed on to the ggplot() function

Value

Plots a ggplot2-object to output

See Also

RCM, plot.RCM,residualPlot

Examples

data(Zeller)
require(phyloseq)
tmpPhy = prune_taxa(taxa_names(Zeller)[1:100],
prune_samples(sample_names(Zeller)[1:50], Zeller))
#Subset for a quick fit
zellerRCMnp = RCM(tmpPhy, k = 2,
covariates = c('BMI','Age','Country','Diagnosis','Gender'),
round = TRUE, responseFun = 'nonparametric')
plotRespFun(zellerRCMnp)

RCM documentation built on Nov. 8, 2020, 5:22 p.m.