metcalcs: calculate variance in network level metrics caused by MOTU...

In hemprichbennett/lOTUs: Showing the effects of clustering on bipartite network data

Description

Acts as a wrapper for bipartite's networklevel and computeModules functions, calculating the difference between your given network-level metrics for a series of networks and clustering thresholds

Usage

metcalcs(networks, indices, network_level = "both",
  list_format = "clust_net")

Arguments

networks	A list of networks
indices	A vector of indices to be calculated. See the functions networklevel and computeModules in package bipartite for details
network_level	The network level to analyse
list_format	The input must be a list of networks. It can be a nested list with the levels either being clustering, then network identity ('clust_net'), or network identity, then clustering ('net_clust'), or alternatively a list of only one network origin, with the names of the list items corresponding to the clustering levels used ('clust_only').

Value

Produces a dataframe showing which metrics are robust in your dataset to clustering-level effects

See Also

line_plot for visualisation of the resulting data

Examples

metcalcs(networks= batnets, indices =c('functional complementarity','web asymmetry', 'Fisher alpha'), network_level = 'higher')

hemprichbennett/lOTUs documentation built on Jan. 22, 2021, 8:54 p.m.