networkplot: Correlation network from spectral similarity data

In tdepke/CluMSID: Clustering of MS2 Spectra for Metabolite Identification

Correlation network from spectral similarity data

Description

networkplot() is used to generate correlation networks from spectral similarity data. An interactive visualisation can be produced using plotly.

Usage

networkplot(distmat, interactive = FALSE, show_labels = FALSE,
    label_size = 1.5, highlight_annotated = FALSE,
    min_similarity = 0.1, exclude_singletons = FALSE)

Arguments

distmat	A distance matrix as generated by distanceMatrix.
interactive	Logical, defaults to FALSE. If TRUE, an interactive visualisation is generated using plotly.
show_labels	Logical, defaults to FALSE. If TRUE, feature IDs are printed as labels in the network plot. Argument has no effect if interactive is TRUE (because in this case, labels are displayed on mouse-over).
label_size	Numeric, defaults to 1.5. If show_labels is TRUE and interactive is FALSE, label_size defines the size of labels in the plot.
highlight_annotated	Logical, defaults to FALSE. If TRUE, points for features for which an annotation was added before using distanceMatrix are highlighted by red colour, while other points are grey in the network plot.
min_similarity	Numeric, defaults to 0.1. The minimum spectral contrast angle (seecossim) that is considered a spectral similarity and hence a connection in the network.
exclude_singletons	Logical, defaults to FALSE. If TRUE, features that have no connection to any other feature will not be displayed in the network plot.

Value

A network plot generated with the help of network, ggnet2 and, if interactive, ggplotly. Edge weights correspond to spectral similarities.

Examples

load(file = system.file("extdata",
    "distmat.RData",
    package = "CluMSIDdata"))

networkplot(distmat[1:50,1:50], show_labels = TRUE,
                exclude_singletons = TRUE)

tdepke/CluMSID documentation built on April 10, 2022, noon