sps_tissue: Example data for 'MetCirc': 'sps_tissue'

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

Example data for 'MetCirc': 'sps_tissue'

Description

'sps_tissue' is a 'Spectra' object derived from the 'idMSMStissueproject' data set. See the vignette for a workflow to reproduce the object 'spectra'.

Format

'matrix'

Value

'matrix'

Author(s)

Thomas Naake, [e-mail]

Source

data("idMSMStissueproject", package = "MetCirc") ## get all MS/MS spectra tissue <- tissue[tissue[, "id"] id_uniq <- unique(tissue[, "id"])

## obtain precursor m/z from id_uniq prec_mz <- lapply(strsplit(as.character(id_uniq), split = "_"), "[", 1) |> unlist() |> as.numeric()

## obtain m/z from fragments per precursor m/z mz_l <- lapply(id_uniq, function(id_i) tissue[tissue[, "id"] == id_i, "mz"])

## obtain corresponding intensity values int_l <- lapply(id_uniq, function(id_i) tissue[tissue[, "id"] == id_i, "intensity"])

## order mz and intensity values int_l <- lapply(seq_along(int_l), function(i) int_l[[i]][order(mz_l[[i]])]) mz_l <- lapply(seq_along(mz_l), function(i) sort(mz_l[[i]]))

## obtain retention time by averaging all retention time values rt <- lapply(id_uniq, function(id_i) tissue[tissue[, "id"] == id_i, "rt"]) |> lapply(mean) |> unlist()

## create list of Spectra objects and concatenate sps_l <- lapply(seq_len(length(mz_l)), function(i) spd <- S4Vectors::DataFrame( name = as.character(i), rtime = rt[i], msLevel = 2L, precursorMz = prec_mz[i]) spd$mz <- list(mz_l[[i]]) spd$intensity <- list(int_l[[i]]) Spectra::Spectra(spd)) sps_tissue <- Reduce(c, sps_l)

## combine list of spectrum2 objects to MSpectra object, ## use SPL, LIM, ANT, STY for further analysis sps_tissue@metadata <- data.frame( compartmentTissue[, c("SPL", "LIM", "ANT", "STY")])

save(sps_tissue, file = "spectra.RData", compress = "xz")

tnaake/MetCirc documentation built on April 23, 2023, 8:56 a.m.