chemoDivPlot {chemodiv} | R Documentation |
Plot chemodiversity
Description
Function to conveniently create basic plots of the different types of
chemodiversity measurements calculated by functions in the package.
This function exists to provide an easy way to make basic chemodiversity
plots. As functions in the package output data in standard formats,
customized plots are easily created with ggplot2
.
Usage
chemoDivPlot(
compDisMat = NULL,
divData = NULL,
divProfData = NULL,
sampDisMat = NULL,
groupData = NULL
)
Arguments
compDisMat |
Compound dissimilarity matrix, generated by
the |
divData |
Diversity/evenness data frame,
generated by the |
divProfData |
Diversity profile, generated by
the |
sampDisMat |
Sample dissimilarity matrix, generated by
the |
groupData |
Grouping data. Should be either a vector or a data frame with a single column. |
Details
The function can create four different types of plots,
(using ggplot2
) depending on which input data
is supplied:
Function argument
compDisMat
. A compound dissimilarity matrix will be plotted as a dendrogram visualizing how structurally/biosynthetically similar different compounds are to each other.Function argument
divData
. Diversity/evenness values will be plotted as a boxplot.Function argument
divProfData
. A diversity profile, plotting (Functional) Hill diversity at different values of q will be plotted as a line plot.Function argument
sampDisMat
. A sample dissimilarity matrix will be plotted as an NMDS plot.Function argument
groupData
. Grouping data (e.g. population, species etc.) may be supplied, to plot each group in different boxes/lines/colours.
Note that this function can take any combination of the four arguments
as input, and argument names should always be specified to ensure
each dataset is correctly plotted. If including the function
argument sampDisMat
, a Nonmetric Multidimensional Scaling (NMDS)
will be performed, which may take time for larger datasets.
Value
The specified chemodiversity plots.
Examples
minimalDiv <- calcDiv(minimalSampData, minimalCompDis, type = "FuncHillDiv")
groups <- c("A", "A", "B", "B")
chemoDivPlot(divData = minimalDiv, groupData = groups)
data(alpinaCompDis)
data(alpinaSampDis)
data(alpinaPopData)
alpinaDiv <- calcDiv(sampleData = alpinaSampData, compDisMat = alpinaCompDis,
type = "FuncHillDiv")
alpinaDivProf <- calcDivProf(sampleData = alpinaSampData,
compDisMat = alpinaCompDis, type = "FuncHillDiv",
qMin = 0, qMax = 2, step = 0.2)
chemoDivPlot(compDisMat = alpinaCompDis, divData = alpinaDiv,
divProfData = alpinaDivProf, sampDisMat = alpinaSampDis,
groupData = alpinaPopData)