| pair_dis_plot {hilldiv} | R Documentation |
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. |
Details
Pairwise dissimilarity plot
Value
An NMDS or network plot.
Author(s)
Antton Alberdi, anttonalberdi@gmail.com
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.
See Also
Examples
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)