Use when you have extracted a centroided MS/MS spectrum from a Thermo Orbitrap raw file (via rawrr::readSpectrum or equivalent) and need to verify that the observed y-ion fragments for a known peptide precursor exhibit signal-to-noise ratios consistent with high-quality fragmentation.
Scanned 9/12/2026
Install to Claude Code
npx -y skills add HolobiomicsLab/asb-skill-collections --skill y-ion-signal-detection-and-noise-assessment --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Y Ion Signal Detection And Noise Assessment?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/holobiomicslab-y-ion-signal-detection-and-noise-assessment)More formats (shields.io, HTML) on the badges page.
---
name: y-ion-signal-detection-and-noise-assessment
description: Use when you have extracted a centroided MS/MS spectrum from a Thermo Orbitrap raw file (via rawrr::readSpectrum or equivalent) and need to verify that the observed y-ion fragments for a known peptide precursor exhibit signal-to-noise ratios consistent with high-quality fragmentation.
license: CC-BY-4.0
metadata:
edam_operation: http://edamontology.org/operation_3636
edam_topics:
- http://edamontology.org/topic_0121
- http://edamontology.org/topic_3520
tools:
- rawrr
- RawFileReader
- Spectra
derived_from:
- doi: 10.1021/acs.jproteome.0c00866
title: rawrr
evidence_spans:
- rawrr::readSpectrum
- Our .NET 8.0 [@dotnet] precompiled wrapper methods are bundled, including the runtime, in the `r BiocStyle::Biocpkg('rawrr')` executable file
- The extracted information is written to a temporary location on the harddrive, read back into memory and parsed into `R` objects using RawFileReader API
- 'ThermoFisher.CommonCore dlls can be obtained through: https://github.com/thermofisherlsms/RawFileReader'
claims: []
provenance:
collection: https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v1
assembled_by: scripts/collect_metabolomics_collection.py
sources:
- build: coll_rawrr
doi: 10.1021/acs.jproteome.0c00866
title: rawrr
dedup_kept_from: coll_rawrr
schema_version: 0.2.0
---
# y-ion signal detection and noise assessment
## Summary
Detects and validates y-ion fragment signals in centroided tandem MS spectra by comparing peak intensities to local baseline noise, ensuring peptide fragmentation quality meets analytical thresholds. Applied to high-resolution Orbitrap data to verify that observed ion signals are tens to hundreds of times above the noise floor.
## When to use
You have extracted a centroided MS/MS spectrum from a Thermo Orbitrap raw file (via rawrr::readSpectrum or equivalent) and need to verify that the observed y-ion fragments for a known peptide precursor exhibit signal-to-noise ratios consistent with high-quality fragmentation. Use this skill when evaluating spectral quality, validating peptide identification confidence, or assessing whether an LC-MS run meets performance benchmarks for a targeted peptide.
## When NOT to use
- Input spectrum is profile-mode (not centroided); baseline noise estimation and peak matching will be unreliable without centroiding preprocessing.
- Peptide sequence is unknown or ambiguous; theoretical y-fragment m/z calculation depends on accurate sequence annotation.
- Raw file is from a non-Orbitrap or non-high-resolution instrument where baseline noise characteristics differ substantially from Orbitrap noise profiles.
## Inputs
- centroided MS/MS spectrum (m/z and intensity arrays) from rawrr::readSpectrum or equivalent
- peptide sequence (e.g., LGGNEQVTR)
- precursor m/z and charge state
- instrument metadata (resolving power, AGC target, injection time)
- mass tolerance threshold (e.g., 10 ppm)
## Outputs
- identified y-ion peak positions and intensities
- signal-to-noise ratios for each y-ion
- local baseline noise estimates
- spectral quality assessment (pass/fail based on S/N thresholds)
- AGC injection efficiency metric (actual / maximum injection time %)
## How to apply
Extract the m/z and intensity arrays from the centroided spectrum object returned by rawrr::readSpectrum. Calculate theoretical y-fragment m/z values for the peptide sequence (e.g., LGGNEQVTR as doubly charged 487.2567 m/z). Identify observed y-ion signals by matching experimental m/z to theoretical m/z with appropriate tolerance (e.g., 10 ppm for Orbitrap resolving power 30,000 at 200 m/z). For each y-ion peak, measure the signal intensity and estimate local baseline noise from adjacent spectral regions. Calculate the signal-to-noise ratio as peak intensity divided by local noise floor. Verify that all y-ions exceed tens to hundreds counts above the noise level to confirm high spectral quality. Document the AGC injection time (e.g., 2.8 ms of 55 ms maximum) as a metric of ion accumulation efficiency.
## Related tools
- **rawrr** (extracts centroided m/z and intensity arrays from Thermo Orbitrap .raw files via readSpectrum() and provides instrument metadata (resolving power, AGC injection time)) — https://github.com/fgcz/rawrr
- **RawFileReader** (underlying .NET assembly wrapped by rawrr; provides direct access to binary Orbitrap spectral data and instrument parameters) — https://github.com/thermofisherlsms/RawFileReader
- **Spectra** (Bioconductor package that can be used with MsBackendRawFileReader to access raw Orbitrap data via standardized accessor functions) — https://bioconductor.org/packages/Spectra/
## Examples
```
S <- rawrr::readSpectrum(rawfile = '20181113_010_autoQC01.raw', scan = 9594); y_ions <- c(175.119, 288.203, 403.230); observed_mz <- S[[1]]$mz; observed_int <- S[[1]]$intensity; sapply(y_ions, function(y) min(abs(observed_mz - y)) < 0.01)
```
## Evaluation signals
- All identified y-ions have signal intensity ≥ tens to hundreds counts above measured local baseline noise (quantitative S/N assessment).
- Observed y-ion m/z values match theoretical m/z within specified tolerance (e.g., 10 ppm) and fragment ladder is continuous or mostly continuous.
- AGC injection time is ≤ 55 ms maximum for Orbitrap and represents typical efficiency (e.g., ~5% in the example indicates rapid ion accumulation).
- Absence of unexplained gaps in the y-ion series; missing y-ions are rare or attributable to known loss patterns (e.g., loss of ammonia or water).
- Baseline noise floor is stable across the m/z range and does not show artifacts (e.g., electronic noise spikes) that would inflate apparent S/N.
## Limitations
- Noise estimation depends on the definition of 'local baseline'; adjacent spectral regions must be carefully selected to avoid contamination from nearby peaks or spectral artifacts.
- Signal-to-noise assessment assumes centroided data; profile-mode spectra require peak-picking preprocessing and may yield different noise estimates.
- Theoretical y-fragment m/z calculation assumes the peptide sequence is correct and charge state is known; sequence ambiguity or charge miscalculation will cause false negatives.
- Windows systems require decimal symbol configured as '.' for proper rawrr data extraction; misconfiguration will cause data parsing failures.
- The skill does not account for variable ionization efficiency across different y-ion m/z ranges; hydrophobic or highly charged fragments may show anomalously low or high intensities independent of instrumental performance.
## Evidence
- [other] Identify y-ion signals by matching observed m/z values to theoretical y-fragment m/z of the precursor peptide (LGGNEQVTR/2). Calculate signal-to-noise ratio for each y-ion by comparing peak intensity to local baseline noise and verify all y-ions exceed tens to hundreds counts above noise floor.: "Identify y-ion signals by matching observed m/z values to theoretical y-fragment m/z of the precursor peptide (LGGNEQVTR/2). Calculate signal-to-noise ratio for each y-ion by comparing peak intensity"
- [other] all y-ion signals for LGGNEQVTR++ peptide are several tens to hundreds of times above the noise level, demonstrating high spectral quality.: "all y-ion signals for LGGNEQVTR++ peptide are several tens to hundreds of times above the noise level, demonstrating high spectral quality."
- [methods] Specifically, `R` functions requesting access to data stored in binary raw files (reader family functions listed in Table 1) invoke compiled `C#` wrapper methods using a system call: "invoke compiled `C#` wrapper methods using a system call"
- [results] the C-trap managed to collect the defined 100,000 charges within 2.8 ms, corresponding to only ~`r format((2.8/55)*100, digits = 1)`% of the maximum injection time of 55 ms: "the C-trap managed to collect the defined 100,000 charges within 2.8 ms, corresponding to only ~5% of the maximum injection time of 55 ms"
- [methods] The example file `20181113_010_autoQC01.raw` used throughout this manuscript contains Fourier-transformed Orbitrap spectra (FTMS) recorded on a Thermo Fisher Scientific Q Exactive HF: "Fourier-transformed Orbitrap spectra (FTMS) recorded on a Thermo Fisher Scientific Q Exactive HF"
- [readme] rawrr wraps the functionality of the RawFileReader .NET assembly: "rawrr wraps the functionality of the RawFileReader .NET assembly"
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!