plotRespFun: Plot the non-parametric response functions

Description Usage Arguments Value See Also Examples

View source: R/F_plotRespFun.R

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

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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

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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.

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