extentIdentifiedPrecursorIntensity: extent of identified MS2 precursor intensity (MS:4000157)

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

extent of identified MS2 precursor intensity (MS:4000157)

Description

MS:4000157
"Ratio of 95th over 5th percentile of MS2 precursor intensity for all quantification data points after user-defined acceptance criteria are applied. Can be used to approximate the dynamic range of signal. The used type of identification 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 intensities of the precursor ions are obtained,
(3) the 5% and 95% quantile of these intensities are obtained (NA values are removed),
(4) the ratio between the 95% and the 5% intensity quantile is calculated and returned.

Usage

extentIdentifiedPrecursorIntensity(
  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:4000157
is_a: MS:4000001 ! QC metric
is_a: MS:4000003 ! single value
is_a: MS:4000008 ! ID based
relationship: has_metric_category MS:4000022 ! MS2 metric
synonym: "MS1-3A" RELATED [PMID:19837981]

Precursor intensity values that are NA are removed.

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

Value

numeric(1)

Note

The Spectra object might contain features that were not identified. If the calculation needs to be done according to *MS:4000157*, the Spectra object should be prepared accordingly, i.e. being 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$precursorIntensity <- c(100, 100, 100)
sps <- Spectra(spd)
extentIdentifiedPrecursorIntensity(spectra = sps, msLevel = 2L)

tnaake/msQC documentation built on Feb. 25, 2024, 7:33 p.m.