Irt Peptide Calibration And Scoring

iRT-peptide-calibration-and-scoring

Summary

Validates retention time (RT) linearity and instrument calibration by fitting a linear regression model to extracted ion chromatograms (XICs) of known iRT peptide standards, using their annotated iRT scores as the independent variable. The R-squared value (target ≥0.99) quantifies the degree of linear RT behavior across the peptide set.

When to use

When you need to assess whether retention times measured on a given LC-MS run follow the expected linear relationship defined by iRT peptide standards (e.g., Pierce or Biognosys iRT peptides). This is appropriate when you have extracted XICs for 11+ known iRT peptides from a raw mass spectrometry file and want to validate instrument RT calibration quality or establish a RT prediction model for peptide identification.

When NOT to use

• When the input raw file does not contain iRT peptide standards or the peptides were not ionized/detected (XICs are empty or sparse).
• When fewer than 5–6 iRT peptides are confidently detected; the regression requires sufficient degrees of freedom and coverage of the RT range.
• When you are analyzing a non-Orbitrap or non-Thermo instrument; the rawrr package is specific to Thermo Fisher Scientific .NET assemblies and .raw files.

Inputs

• Thermo Fisher Scientific .raw file (Orbitrap instrument data)
• List of known iRT peptide precursor m/z values
• Annotated iRT reference scores (e.g., Pierce iRT standard peptides)
• Mass tolerance parameter (e.g., 10 ppm)

Outputs

• rawrrChromatogram object (fitted intensity traces)
• Vector of rtFittedAPEX values (observed RT at peak maximum for each peptide)
• Linear regression model object (lm class in R)
• R-squared value quantifying RT linearity
• Residual plot or diagnostic statistics

How to apply

Extract precursor m/z values and measured retention times for each iRT peptide standard using the rawrr::readChromatogram() function with mass tolerance ~10 ppm and XIC filter type. Fit intensity traces stored in rawrrChromatogram objects to identify the retention time at maximum intensity (rtFittedAPEX) for each peptide. Construct a linear regression model lm(rtFittedAPEX ~ iRTscore) where iRTscore is the annotated reference score for each peptide. Report the resulting R-squared value; values ≥0.99 indicate highly linear RT behavior and good instrument calibration. Lower R-squared values may suggest drift, temperature variation, or column degradation.

Related tools

• rawrr (R package providing direct access to Thermo Orbitrap .raw file data; used to read file headers, extract XICs, and retrieve spectrum metadata) — https://github.com/fgcz/rawrr
• RawFileReader (.NET assembly (C#) underlying rawrr; implements low-level chromatogram and spectrum reading from binary .raw files) — https://github.com/thermofisherlsms/RawFileReader
• R base (stats::lm) (Fits linear regression model to RT observations and iRT scores; computes R-squared and residuals)

Examples

C <- rawrr::readChromatogram(rawfile, mass = iRTmz, tol = 10, type = "xic", filter = "ms"); m <- lm(rtFittedAPEX ~ iRTscore); summary(m)$r.squared

Evaluation signals

• R-squared value is ≥0.99 for iRT regression, confirming highly linear RT behavior across the 11+ peptides.
• Residual plot shows no systematic trend (e.g., funnel or sine pattern), indicating homoscedasticity and model validity.
• All iRT peptides are detected (non-empty XICs) and rtFittedAPEX values span the full RT range of the run without outliers.
• Fitted model coefficients (intercept and slope) are stable across replicate measurements of the same raw file, indicating reproducibility.
• Root mean square error (RMSE) or mean absolute error (MAE) of predicted vs. observed RT is <0.5 min, depending on method-specific tolerance.

Limitations

• The rawrr package and RawFileReader .NET assembly are specific to Thermo Fisher Scientific Orbitrap instruments and .raw files; not applicable to other vendor formats (e.g., Bruker .d, Waters .raw, AB Sciex .wiff).
• On Windows systems, the decimal symbol must be configured as '.' for proper data extraction; regional locale settings can cause parsing errors.
• The quality of the regression depends on confident detection and annotation of iRT peptides; missing or misidentified peptides (e.g., due to ionization suppression or coelution) will reduce R-squared.
• RT linearity assumes stable column conditions and temperature; significant drift or column degradation during the run can artificially lower R-squared even with good instrument calibration.
• The choice of mass tolerance (e.g., 10 ppm) and XIC extraction filter directly affects which scans are included; too loose a tolerance may capture co-eluting interferents, biasing rtFittedAPEX.

Evidence

• [results] Extract precursor m/z and RT using rawrr::readChromatogram() with mass tolerance and XIC filter: "Extract precursor m/z values and retention times for known iRT peptide standards using rawrr::readChromatogram() with mass tolerance 10 ppm and XIC filter."
• [results] Fit intensity traces to extract rtFittedAPEX and construct linear regression model: "we extract the RTs at the maximum of the fitted intensity traces stored in the rawrrChromatogram object and fit a linear model"
• [results] R-squared of 0.9999 indicates highly linear RT behavior: "The corresponding R-squared indicates that the RTs behave highly linear"
• [intro] rawrr wraps RawFileReader .NET assembly for direct access to Orbitrap data: "rawrr wraps the functionality of the RawFileReader .NET assembly"
• [intro] Gap in R ecosystem for raw data reading; rawrr closes this for direct analysis pipelines: "A library providing raw data reading would finally close the gap and facilitate modular end-to-end analysis pipeline development in R"
• [discussion] Windows decimal symbol configuration requirement: "On Windows, the decimal symbol has to be configured as a '.'!"
• [methods] iRT regression model fitting on known peptide standards: "Fit intensity traces stored in rawrrChromatogram objects to extract retention times at maximum intensity (rtFittedAPEX)."