precursorIntensitySd: MS2 precursor intensity distribution sigma (MS:4000118),...

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

MS2 precursor intensity distribution sigma (MS:4000118), identified MS2 precursor intensity distribution sigma (MS:4000165), or unidentified MS2 precursor intensity distribution sigma (MS:4000166)

Description

MS:4000118
"From the distribution of MS2 precursor intensities, the sigma value. The intensity distribution of the precursors informs about the dynamic range of the acquisition." [PSI:MS]

MS:4000165
"From the distribution of identified MS2 precursor intensities, the sigma value. 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]

MS:4000166
"From the distribution of unidentified MS2 precursor intensities, the sigma value. 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 standard deviation of precursor intensity values is obtained (NA values are removed) and returned.

Usage

precursorIntensitySd(
  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:4000118
is_a: MS:4000003 ! single value
relationship: has_metric_category MS:4000009 ! ID free metric
relationship: has_metric_category MS:4000022 ! MS2 metric
relationship: has_value_concept STATO:0000237 ! standard deviation
relationship: has_value_type xsd:float ! The allowed value-type for this CV term
relationship: has_units MS:1000043 ! intensity unit

MS:4000165
is_a: MS:4000003 ! single value
relationship: has_metric_category MS:4000008 ! ID based
relationship: has_metric_category MS:4000022 ! MS2 metric
relationship: has_value_concept STATO:0000237 ! standard deviation
relationship: has_value_type xsd:float ! The allowed value-type for this CV term
relationship: has_units MS:1000043 ! intensity unit

MS:4000166
is_a: MS:4000003 ! single value
relationship: has_metric_category MS:4000008 ! ID based
relationship: has_metric_category MS:4000022 ! MS2 metric
relationship: has_value_concept STATO:0000237 ! standard deviation
relationship: has_value_type xsd:float ! The allowed value-type for this CV term
relationship: has_units MS:1000043 ! intensity unit

Value

numeric(1)

Note

The Spectra object might contain features that were (not) identified. If the calculation needs to be done according to *MS:4000165*/*MS:4000166*, 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)
precursorIntensitySd(spectra = sps, msLevel = 2L)

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