Mass Tolerance Window Filtering

mass-tolerance-window-filtering

Summary

Filter candidate molecular formulae by mass error tolerance when matching observed m/z values to database entries. This skill constrains formula lookup results to a user-defined ppm or Da window around the neutral mass, reducing false positives and focusing candidate lists on chemically plausible assignments.

When to use

Apply this skill after calculating neutral mass from observed m/z and adduct type, and before ranking candidates by chemical plausibility. Use it whenever querying a formula database (KEGG, PubChem, or custom) to retrieve all molecular formulae within a specified mass tolerance window of each neutral mass. It is essential when the database is large and you need to reduce the candidate set to interpretable size.

When NOT to use

• Input is already a feature table (annotation/compound assignment is done; use this skill earlier in the workflow)
• Mass tolerance window is unknown or unavailable from the instrument (cannot proceed without specifying ppm or Da threshold)
• Formula database is empty, unavailable, or not built in MetaboShiny (build or import database first)

Inputs

• observed m/z peak list (numeric vector or peaklist file)
• configured adduct definitions (e.g., [M+H]+, [M+Na]+, [M-H]−)
• mass tolerance threshold (numeric, in ppm or Da)
• formula database (KEGG, PubChem, or user-supplied CSV)

Outputs

• filtered candidate formula table (rows = peaks, columns = formula, observed m/z, theoretical m/z, mass error, adduct type)
• candidate ranking by mass error
• tabulated results with per-peak formula assignments and mass error metrics

How to apply

For each m/z peak in your input list, first apply the inverse of the configured adduct transformation (e.g., subtract 1.007825 for [M+H]+, subtract 22.989220 for [M+Na]+) to calculate the neutral mass. Then query the formula database with a mass tolerance window defined in parts per million (ppm) or Daltons (Da). The tolerance window is typically set during MetaboShiny project initialization (e.g., 5 ppm for high-resolution instruments). Return all candidate formulae whose theoretical m/z values fall within ±tolerance of the neutral mass. This filtering step greatly reduces computational load and prevents unlikely formulae from propagating to downstream plausibility scoring.

Related tools

• MetaboShiny (Provides configurable adduct settings, formula database integration, and mass-tolerance-filtered candidate lookup within a unified workflow UI) — https://github.com/joannawolthuis/MetaboShiny
• R (Underlying language for mass-error calculation, database querying, and candidate filtering logic)
• KEGG (Formula database source for molecular formula candidates)
• PubChem (Formula database source for molecular formula candidates)

Evaluation signals

• Candidate formulae returned have mass error (observed m/z − theoretical m/z) within the specified tolerance window (e.g., ≤5 ppm)
• No candidate formulae are returned with mass error exceeding the tolerance threshold
• Candidate count per peak is reduced by >90% relative to unfiltered database size, indicating effective filtering
• Mass error distribution is centered near zero with minimal outliers, suggesting correct neutral mass calculation and adduct inversion
• Downstream chemical plausibility scoring (element ratios, hydrogen deficiency) confirms candidates are chemically reasonable

Limitations

• Filtering is only as good as the accuracy of the mass spectrometer and the configured mass tolerance; underestimating tolerance may exclude true positives, while overestimating may re-introduce false positives.
• The skill assumes adduct definitions are correct and complete; misconfigured adduct rules will propagate incorrect neutral masses to the tolerance filter.
• Formula databases (KEGG, PubChem) may have gaps, outdated records, or biases toward certain compound classes; custom databases must be manually curated and formatted.
• When multiple adducts are configured for the same peak, tolerance filtering produces separate candidate lists per adduct; ambiguity resolution requires downstream ranking or manual curation.

Evidence

• [other] For each m/z value, calculate the neutral mass by applying the inverse of each configured adduct transformation (e.g., [M+H]+, [M+Na]+, [M-H]−).: "For each m/z value, calculate the neutral mass by applying the inverse of each configured adduct transformation (e.g., [M+H]+, [M+Na]+, [M-H]−)."
• [other] Query the formula database (KEGG, PubChem, or user-supplied) to retrieve all molecular formulae within the configured mass tolerance window (in ppm or Da) of each neutral mass.: "Query the formula database (KEGG, PubChem, or user-supplied) to retrieve all molecular formulae within the configured mass tolerance window (in ppm or Da) of each neutral mass."
• [readme] Set the error margin of your mass spectrometer in parts per million (ppm).: "Set the error margin of your mass spectrometer in parts per million (ppm)."
• [other] Rank candidate formulae by mass error and chemical plausibility rules (e.g., element ratios, hydrogen deficiency).: "Rank candidate formulae by mass error and chemical plausibility rules (e.g., element ratios, hydrogen deficiency)."
• [other] Return and tabulate the top-ranked candidates with their assigned formula, adduct type, observed m/z, theoretical m/z, and mass error for each peak.: "Return and tabulate the top-ranked candidates with their assigned formula, adduct type, observed m/z, theoretical m/z, and mass error for each peak."