minFragCart2Polar: Calculate the nearest feature in polar coordinates given...

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

Description

Calculates the nearest feature in polar coordinates given cartesian coordinates.

Usage

minFragCart2Polar(x, y, degreeOfFeatures)

Arguments

x	cartesian x coordinate
y	cartesian y coordinate
degreeOfFeatures	'list' of positions of features

Details

'minFragCart2Polar' is employed to find the feature with the smallest distance from given cartesian coordinates.

Value

'minFragCart2Polar' returns the index of the feature that has the smallest distance to the given coordinates. As 'minFragCart2Polar' is used in 'shinyCircos' for the track 1 only polar r coordinates between 0.8 and 1 will be used to find the feature with smallest distance.

Author(s)

Thomas Naake, [e-mail]

Examples

data("spectra", package = "MetCirc")
similarityMat <- compare_Spectra(spectra_tissue[1:10], 
    fun = normalizeddotproduct, binSize = 0.01)
linkDf <- createLinkDf(similarityMatrix = similarityMat, 
    spectra = spectra_tissue[1:10], 
    condition = c("SPL", "LIM", "ANT", "STY"), lower = 0.5, upper = 1) 
## cut link data.frame (here: only display links between groups)
linkDf_cut <- cutLinkDf(linkDf, type = "inter")
groupname <- c(as.character(linkDf_cut[, "spectrum1"]), 
                as.character(linkDf_cut[, "spectrum2"]))
groupname <- unique(groupname)
## set circlize parameters
circos.clear()
circos.par(gap.degree = 0, cell.padding = c(0.0, 0, 0.0, 0),
    track.margin = c(0.0, 0))
plotCircos(groupname, NULL, initialize = TRUE, featureNames = FALSE, 
    groupName = FALSE, groupSector = FALSE, links = FALSE, highlight = FALSE)
x <- 1
y <- 0
degreeFeatures <- lapply(groupname, 
 function(x) mean(circlize:::get.sector.data(x)[c("start.degree", "end.degree")]))
minFragCart2Polar(x, y, degreeOfFeatures = degreeFeatures)

MetCirc documentation built on Nov. 8, 2020, 8:26 p.m.