plotCircos: Circular plot to visualize similarity

In tnaake/MetCirc: Navigating mass spectral similarity in high-resolution MS/MS metabolomics data metabolomics data

Circular plot to visualize similarity

Description

Circular plot to visualize similarity.

Usage

plotCircos(
  groupname,
  linkDf,
  initialize = c(TRUE, FALSE),
  featureNames = c(TRUE, FALSE),
  cexFeatureNames = 0.3,
  groupSector = c(TRUE, FALSE),
  groupName = c(TRUE, FALSE),
  links = c(TRUE, FALSE),
  highlight = c(TRUE, FALSE),
  colour = NULL,
  transparency = 0.2
)

Arguments

groupname	character vector containing "group" and "name" to display that is a unique identifier of the features, "group" and "name" have to be separated by "_" where "group" is the first and "name" is the last element
linkDf	data.frame containing linked features in each row, has five columns (group1, spectrum1, group2, spectrum2, similarity)
initialize	logical, should plot be initialized?
featureNames	logical, should feature names be displayed?
cexFeatureNames	numeric size of feature names
groupSector	logical, should groups be displayed with background colours?
groupName	logical, should group names (e.g. compartment names or individual names) be displayed?
links	logical, should links be plotted?
highlight	logical, highlight is set to TRUE by default
colour	NULL or character, colour defines the colours which are used for plotting, if NULL default colours are used
transparency	numeric, defines the transparency of the colours

Details

Internal use for shinyCircos or used outside of shinyCircos to reproduce figure

Value

The function will initialize a circlize plot and/or will plot features of a circlize plot.

Author(s)

Thomas Naake, [e-mail]

Examples

library("MsCoreUtils")
data("spectra", package = "MetCirc")

## create similarity matrix
similarityMat <- Spectra::compareSpectra(sps_tissue[1:10],
    FUN = MsCoreUtils::ndotproduct, ppm = 20, m = 0.5, n = 2)
rownames(similarityMat) <- colnames(similarityMat) <- sps_tissue$name[1:10]

## order similarityMat according to retentionTime
simM <- orderSimilarityMatrix(similarityMat, sps = sps_tissue[1:10],
            type = "retentionTime")
            
## create link data.frame
linkDf <- createLinkDf(similarityMatrix = simM, sps = sps_tissue,
     condition = c("SPL", "LIM", "ANT", "STY"), lower = 0.01, upper = 1)
## cut link data.frame (here: only display links between groups)
linkDf_cut <- cutLinkDf(linkDf, type = "inter")

## set circlize paramters
circos.clear()
circos.par(gap.degree = 0, cell.padding = c(0.0, 0, 0.0, 0),
         track.margin = c(0.0, 0))
groupname <- c(as.character(linkDf_cut[, "spectrum1"]),
                as.character(linkDf_cut[, "spectrum2"]))
groupname <- unique(groupname)

## actual plotting
plotCircos(groupname, linkDf_cut, initialize = TRUE,
    featureNames = TRUE, cexFeatureNames = 0.3, groupSector = TRUE,
    groupName = FALSE, links = FALSE, highlight = FALSE, colour = NULL,
    transparency = 0.2)

tnaake/MetCirc documentation built on Dec. 7, 2022, 7:42 a.m.