flag_remove: Flag and remove unwanted peaks

In computational-metabolomics/msPurity: Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics

Flag and remove unwanted peaks

Description

Filter, flag and remove unwanted peaks from xcms object (xcmsObj) of class XCMSnExp, xcmsSet or xsAnnotate. When the peaks are removed, the xcmsObj object can be regrouped (originally using xcms::group, now using xcms::groupChromPeaks). The function then checks if any blank peaks are still present and the process is repeated.

The output is a list object containing: 1) the updated xcms object, 2) the grouped peaklist and 3) the blank removed peaks

Usage

flag_remove(
  xcmsObj,
  pol = NA,
  rsd_i_blank = NA,
  minfrac_blank = 0.5,
  rsd_rt_blank = NA,
  ithres_blank = NA,
  s2b = 10,
  ref.class = "blank",
  egauss_thr = NA,
  rsd_i_sample = NA,
  minfrac_sample = 0.7,
  rsd_rt_sample = NA,
  ithres_sample = NA,
  minfrac_xcms = 0.7,
  mzwid = 0.017,
  bw = 5,
  out_dir = ".",
  temp_save = FALSE,
  remove_spectra_bool = TRUE,
  grp_rm_ids = NA,
  xset = NA
)

Arguments

xcmsObj	object; XCMSnExp, xcmsSet or xsAnnotate object
pol	str; polarity (just used for naming purpose for files being saved) [positive, negative, NA]
rsd_i_blank	numeric; RSD threshold for the blank
minfrac_blank	numeric; minimum fraction of files for features needed for the blank
rsd_rt_blank	numeric; RSD threshold for the RT of the blank
ithres_blank	numeric; Intensity threshold for the blank
s2b	numeric; fold change (sample/blank) needed for sample peak to be allowed. e.g. if s2b set to 10 and the recorded sample 'intensity' value was 100 and blank = 10. 1000/10 = 100 so sample has fold change higher than the threshold and the peak is not considered a blank
ref.class	str; A string representing the class that will be used for the blank.
egauss_thr	numeric; Threshold for filtering out non gaussian shaped peaks. Note this only works if the verbose option was set for XCMS;
rsd_i_sample	numeric; RSD threshold for the sample
minfrac_sample	numeric; minimum fraction of files for features needed for the sample
rsd_rt_sample	numeric; RSD threshold for the RT of the sample
ithres_sample	numeric; Intensity threshold for the sample
minfrac_xcms	numeric; minfrac for xcms grouping
mzwid	numeric; xcms grouping parameter (corresponds to variable 'binSize' in XCMS3)
bw	numeric; xcms grouping parameter
out_dir	str; out directory
temp_save	boolean; Assign True if files for each step saved (for testing purpsoses)
remove_spectra_bool	bool; TRUE if flagged spectra is to be removed
grp_rm_ids	vector; vector of grouped_xcms peaks to remove (corresponds to the row from xcms::group output)
xset	object, DEPRECATED; xcmsSet object

Value

list(xset, grp_peaklist, removed_peaks)

Examples

library(xcms)
library(MSnbase)
library(magrittr)
#read in files and data
msPths <-list.files(system.file("extdata", "lcms", "mzML", package="msPurityData"), full.names = TRUE)
ms_data = readMSData(msPths, mode = 'onDisk', msLevel. = 1)

#subset the data to focus on retention times 30-90 seconds and m/z values between 100 and 200 m/z.
rtr = c(30, 90)
mzr = c(100, 200)
ms_data = ms_data %>%  filterRt(rt = rtr) %>%  filterMz(mz = mzr)

##### perform feature detection in individual files
cwp <- CentWaveParam(snthresh = 3, noise = 100, ppm = 10, peakwidth = c(3, 30))
xcmsObj <- findChromPeaks(ms_data, param = cwp)
xcmsObj@phenoData@data$class = c('blank', 'blank', 'sample', 'sample')
xcmsObj@phenoData@varMetadata = data.frame('labelDescription' = 'sampleNames', 'class')
pdp <- PeakDensityParam(sampleGroups = xcmsObj@phenoData@data$class, minFraction = 0, bw = 5, binSize = 0.017)
xcmsObj <- groupChromPeaks(xcmsObj, param = pdp)

#### flag, filter and remove peaks, returning an updated xcmsObj (XCMSnExp or xcmsSet class), grouped_peaklist (data.frame) and removed_peaks (data.frame)
fr <- flag_remove(xcmsObj)

##### load from existing data
xcmsObj = readRDS(system.file("extdata", "tests", "purityA", "10_input_filterflagremove.rds", package="msPurity"))

computational-metabolomics/msPurity documentation built on Sept. 8, 2023, 8:04 p.m.