precursorIntensityQuartiles: MS2 precursor intensity distribution (MS:4000116), identified...

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

MS2 precursor intensity distribution (MS:4000116), identified MS2 precursor intensity distribution (MS:4000161), or unidentified MS2 precursor intensity distribution (MS:4000162)

Description

MS:4000116
"From the distribution of MS2 precursor intensities, the quantiles. E.g. a value triplet represents the quartiles Q1, Q2, Q3. The intensity distribution of the precursors informs about the dynamic range of the acquisition." [PSI:MS]

MS:40000161
From the distribution of identified MS2 precursor intensities, the quantiles. E.g. a value triplet represents the quartiles Q1, Q2, Q3. The intensity distribution of the precursors informs about the dynamic range of the acquisition in relation to identifiability. 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]"

id: MS:4000162
"From the distribution of unidentified MS2 precursor intensities, the quantiles. E.g. a value triplet represents the quartiles Q1, Q2, Q3. The intensity distribution of the precursors informs about the dynamic range of the acquisition in relation to identifiability. 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 intensity of the precursor ions within the Spectra object are obtained,
(3) the 25%, 50%, and 75% quantile of the precursor intensity values are obtained (NA values are removed) and returned.

Usage

precursorIntensityQuartiles(
  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

id: MS:4000116
is_a: MS:4000004 ! n-tuple
relationship: has_metric_category MS:4000009 ! ID free metric
relationship: has_metric_category MS:4000022 ! MS2 metric
relationship: has_value_concept STATO:0000291 ! quantile
relationship: has_value_type xsd:float ! The allowed value-type for this CV term
relationship: has_units MS:1000043 ! intensity unit

MS:4000161
is_a: MS:4000004 ! n-tuple
is_a: MS:4000008 ! ID based
relationship: has_metric_category MS:4000022 ! MS2 metric
relationship: has_value_concept STATO:0000291 ! quantile
relationship: has_value_type xsd:float ! The allowed value-type for this CV term
relationship: has_units MS:1000043 ! intensity unit

id: MS:4000162
is_a: MS:4000004 ! n-tuple
is_a: MS:4000008 ! ID based
relationship: has_metric_category MS:4000022 ! MS2 metric
relationship: has_value_concept STATO:0000291 ! quantile
relationship: has_value_type xsd:float ! The allowed value-type for this CV term
relationship: has_units MS:1000043 ! intensity unit

Value

numeric(3)

Note

The Spectra object might contain features that were (not) identified. If the calculation needs to be done according to *MS:4000161*/*MS:4000162*, the Spectra object should be prepared accordingly.

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(100.0, 100.0, 100.0)
sps <- Spectra(spd)

precursorIntensityQuartiles(spectra = sps, msLevel = 2L)

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