recalibrate {MSnID} | R Documentation

## Post-experimental recalibration of observed mass to charge ratios

### Description

Mass spectrometry measurements like any other real-worls measurements are prone to systematic errors. Typically they are minimized by instrument calibration prior the analysis. Nonetheless, the calibration may drift over time or be affected by some adverse factors (temperature or space charge fluctuations).

This function estimates and removes the systematic error from the datasets. The side effect is the recalibrated `experimentalMassToCharge` values.

### Usage

        recalibrate(object)

### Arguments

`object` | An instance of class "MSnID".

### Details

Currently it employs a very simple method of zero-centering the histogram of mass measurement errors. In the future it will contain more sophisticated recalibration routines.

### Value

"MSnID" class instance with updated `experimentalMassToCharge`.

### Author(s)

Vladislav A Petyuk vladislav.petyuk@pnnl.gov

### See Also

`MSnID` `mass_measurement_error` `correct_peak_selection`

### Examples

    data(c_elegans)

    # first let's fix the error of picking wrong monoisotopic peak
    # otherwise the mass error range will be very large
    msnidObj <- correct_peak_selection(msnidObj)

    # original mass error in ppm
    ppm <- mass_measurement_error(msnidObj)
    hist(ppm, 200, xlim=c(-20,+20))

    # The dataset is well calibrated. So let's introduce
    # some mass measurement error.
    msnidObj$experimentalMassToCharge <-
        msnidObj$experimentalMassToCharge * (1+0.00001)

    # mass error (in ppm) after artificial de-calibration
    ppm <- mass_measurement_error(msnidObj)
    hist(ppm, 200, xlim=c(-20,+20))

    # recalibration
    msnidObj <- recalibrate(msnidObj)
    ppm <- mass_measurement_error(msnidObj)
    hist(ppm, 200, xlim=c(-20,+20))

[Package MSnID version 1.24.0 Index]