Galaxy | Tool Preview

MFAssignR FindRecalSeries (version 1.1.2+galaxy1)
Recalibration series, output from RecalList

MFAssignR - FindRecalSeries

This tool is the sixth step of the MFAssignR workflow (RecalList -> FindRecalSeries -> Recal)

This function takes on input the CH2 homologous recalibration series, which are provided by the RecalList function and tries to find the most suitable series combination for recalibration based on the following criteria:

  1. Series should cover the full mass spectral range,
  2. Series should be optimally long and combined have a “Tall Peak” at least every 100 m/z,
  3. Abundance score: the higher, the better,
  4. Peak score: the closer to 0, the better,
  5. Peak Distance: the closer to 1, the better,
  6. Series Score: the closer to this value, the better.

Combinations of 5 series are assembled, scores are computed for other metrics (in case of Peak proximity and Peak distance, an inverted score is computed) and these are summed. Finally, either a series of the size of combination or top 10 unique series having the highest score are outputted.

Output:

  • Dataframe of n or 10 most suitable recalibrant series.

General Information

Overview

MFAssignR is an R package for the molecular formula (MF) assignment of ultrahigh resolution mass spectrometry measurements. It contains several functions for the noise assessment, isotope filtering, interal mass recalibration, and MF assignment.

The MFAssignR package was originally developed by Simeon Schum et al. (2020), the source code can be found on GitHub. Please submit eventual Galaxy-related bug reports as issues on the repository.

Workflow

A picture of a workflow diagram.

The recommended workflow how to run the MFAssignR package is as follows:

  1. Run KMDNoise() to determine the noise level for the data.
  2. Check effectiveness of S/N threshold using SNplot().
  3. Use IsoFiltR() to identify potential 13C and 34S isotope masses.
  4. Using the S/N threshold, and the two data frames output from IsoFiltR(), run MFAssignCHO() to assign MF with C, H, and O to assess the mass accuracy.
  5. Use RecalList() to generate a list of the potential recalibrant series.
  6. Choose the most suitable recalibrant series using FindRecalSeries().
  7. After choosing recalibrant series, use Recal() to recalibrate the mass lists.
  8. Assign MF to the recalibrated mass list using MFAssign().
  9. Check the output plots from MFAssign() to evaluate the quality of the assignments.

For detailed documentation on the individual steps please see the individual tool wrappers.