medianPrecursorMz: MS2 precursor median m/z of identified quantification data...

In tnaake/msQC: MsQuality - Quality metric calculation from Spectra and MsExperiment objects

MS2 precursor median m/z of identified quantification data points (MS:4000152)

Description

MS:4000152
"Median m/z value for MS2 precursors of all quantification data points after user-defined acceptance criteria are applied. These data points may be for example XIC profiles, isotopic pattern areas, or reporter ions (see MS:1001805). The used type should be noted in the metadata or analysis methods section of the recording file for the respective run. In case of multiple acceptance criteria (FDR) available in proteomics, PSM-level FDR should be used for better comparability." [PSI:MS]

The metric is calculated as follows:
(1) the Spectra object is filtered according to the MS level,
(2) the precursor m/z values are obtained,
(3) the median value is returned (NAs are removed).

Usage

medianPrecursorMz(
  spectra,
  msLevel = 1L,
  identificationLevel = c("all", "identified", "unidentified"),
  ...
)

Arguments

spectra	Spectra object
msLevel	integer
identificationLevel	character(1), one of "all", "identified", or "unidentified"
...	not used here

Details

MS:4000152
is_a: MS:4000003 ! single value
is_a: MS:4000008 ! ID based
is_a: MS:4000020 ! ion source metric
relationship: has_metric_category MS:4000022 ! MS2 metric
relationship: has_units MS:1000040 ! m/z

An attribute containing the PSI:MS term will only be returned if identificationLevel is "identified" and msLevel is 1.

Value

numeric(1)

Note

medianPrecursorMz will calculate the *precursor* median m/z of all Spectra within spectra. If the calculation needs be done according to *MS:4000152*, the Spectra object should be prepared accordingly, i.e. filtered with e.g. [filterPrecursorMz()] or subsetted to spectra with identification data.

Author(s)

Thomas Naake

Examples

library(S4Vectors)
library(Spectra)

spd <- DataFrame(
    msLevel = c(2L, 2L, 2L),
    polarity = c(1L, 1L, 1L),
    id = c("HMDB0000001", "HMDB0000001", "HMDB0001847"),
    name = c("1-Methylhistidine", "1-Methylhistidine", "Caffeine"))
## Assign m/z and intensity values
spd$mz <- list(
    c(109.2, 124.2, 124.5, 170.16, 170.52),
    c(83.1, 96.12, 97.14, 109.14, 124.08, 125.1, 170.16),
    c(56.0494, 69.0447, 83.0603, 109.0395, 110.0712,
        111.0551, 123.0429, 138.0662, 195.0876))
spd$intensity <- list(
    c(3.407, 47.494, 3.094, 100.0, 13.240),
    c(6.685, 4.381, 3.022, 16.708, 100.0, 4.565, 40.643),
    c(0.459, 2.585, 2.446, 0.508, 8.968, 0.524, 0.974, 100.0, 40.994))
spd$precursorMz <- c(170.16, 170.16, 195.0876)
sps <- Spectra(spd)
medianPrecursorMz(spectra = sps, msLevel = 2L)

tnaake/msQC documentation built on Oct. 31, 2024, 2:41 a.m.