pair_dis_plot: Pairwise dissimilarity plot

Description

Visualisation of pairwise dissimilarities

Usage

pair_dis_plot(distance, hierarchy, type, level, colour, magnify)

Arguments

distance

Matrix of pairwise dissimilarities, usually one of the matrices listed in the output object of the pair_dis() function.

hierarchy

The first column lists the sample names while the second lists the groups. If provided, group profiles are plotted instead of individual profiles.

type

Whether to plot a NMDS or qgraph chart. type="NMDS".

level

If '1', samples are not grouped (each sample is a different colour), while if '2', samples are coloured by groups. level=1.

colour

he number of vector items (colours, e.g. '#34k235'), must equal the number of samples or groups that are intended to plot.

magnify

Only relevant for qgraph. Whether the pairwise dissimilarity values are transformed to 0-1 scale, 0 corresponding to the minimum dissimilarity and 1 to the maximum dissimilarity value. magnify=FALSE.

Value

An NMDS or network plot.

Details

Pairwise dissimilarity plot

References

Alberdi, A., Gilbert, M.T.P. (2019). A guide to the application of Hill numbers to DNA-based diversity analyses. Molecular Ecology Resources, 19, 804-817. Chao, A., Chiu, C.H., & Hsieh, T. C. (2012). Proposing a resolution to debates on diversity partitioning. Ecology, 93, 2037-2051. Jost, L. (2007). Partitioning diversity into independent alpha and beta components. Ecology, 88, 2427-2439.

Examples

Run this code

# NOT RUN {
data(bat.diet.otutable)
data(bat.diet.tree)
data(bat.diet.hierarchy)
pairdisres <- pair_dis(bat.diet.otutable,qvalue=0,hierarchy=bat.diet.hierarchy,level="2")
pair_dis_plot(pairdisres$L2_CqN,hierarchy=bat.diet.hierarchy,type="NMDS",level=2)
pair_dis_plot(pairdisres$L2_CqN,hierarchy=bat.diet.hierarchy,type="qgraph",level=2)
# }

Run the code above in your browser using DataCamp Workspace