Mass Spectrometry Data Constraint Validation

mass-spectrometry-data-constraint-validation

Summary

Enforce data integrity constraints on m/z values, intensity values, and peak data when implementing or modifying writable MsBackend instances in the Spectra package. This skill ensures that replacement methods maintain critical invariants: length matching, data type validation, peak-count preservation, and m/z ordering.

When to use

Apply this skill when implementing replacement methods ($<-, [<-, spectraData<-, mz<-, intensity<-, peaksData<-) for a writable MsBackend subclass, or when modifying peak data in an existing backend. Trigger conditions include: (1) adding write capability to a read-only backend, (2) validating user-provided replacement values before assignment, (3) ensuring that m/z and intensity vectors remain consistent after modification, or (4) verifying that m/z values remain sorted increasingly within each spectrum after update.

When NOT to use

• Backend is purely read-only (e.g., MsBackendMzR retrieving data on-the-fly from raw files) — implement only accessor methods (mz(), intensity(), peaksData()), not replacement methods.
• Input is raw mzML/mzXML/CDF file data being imported for the first time — use backendInitialize() instead to load and structure initial data.
• m/z values are not expected to be increasingly sorted (e.g., in synthetic or reordered spectral data where sort order is intentionally violated) — this skill enforces the Spectra design assumption that m/z values must be ordered.

Inputs

• S4 MsBackend subclass instance (writable or partially writable)
• Replacement vector or list (m/z values, intensity values, or peak data as NumericList or matrix)
• Index or spectra variable name (for $<- or [<- replacement)
• Integer or logical vector (for subsetting via extractByIndex)

Outputs

• Modified MsBackend instance with validated replacement data
• Internal DataFrame or list-of-matrices structure updated with new peak or spectra data
• Boolean validation status or error message if constraints violated

How to apply

Define replacement method signatures using S4 method definitions in R (e.g., setReplaceMethod('[<-', ...) for index-based replacement). For each replacement method, implement a four-stage validation pipeline: (1) Match length validation using .match_length() to ensure the replacement vector's length equals either the spectrum count (for full backend replacement) or individual spectrum peak counts (for per-spectrum replacement); (2) Data type validation to confirm that m/z and intensity values are NumericList objects and other spectra variables conform to expected types (e.g., numeric, character); (3) Peak-count preservation checks to ensure that replacement values maintain the same number of peaks per spectrum; (4) m/z ordering validation using is.unsorted() to verify that m/z values are increasingly sorted within each spectrum after replacement, and confirm that no NA values appear in m/z vectors. After validation passes, update the internal data structure (DataFrame, list of matrices, or on-disk storage) and return the modified backend. Test all replacement methods on a concrete backend instance to confirm writable functionality and constraint enforcement.

Related tools

• Spectra (R package providing the MsBackend virtual class and S4 infrastructure for defining replacement method signatures and validating replacement operations on backend instances) — https://github.com/RforMassSpectrometry/Spectra
• S4Vectors (R package providing DataFrame class and NumericList container for storing and validating structured spectra data (m/z, intensity, other variables))
• IRanges (R package providing base infrastructure for length and index validation operations used in replacement method implementations)

Examples

setReplaceMethod('mz<-', 'MsBackendMemory', function(object, value) { if (length(value) != length(object)) stop('Length mismatch'); if (!is(value, 'NumericList')) stop('m/z must be NumericList'); if (any(is.na(unlist(value)))) stop('NA values not allowed in m/z'); object@mz <- value; object })

Evaluation signals

• Replacement method successfully rejects input vectors with length not matching spectrum count or individual spectrum peak count (via .match_length() validation).
• Replacement method rejects non-NumericList m/z or intensity values and non-matching data types for other spectra variables.
• After successful replacement, peak-count per spectrum remains identical to pre-replacement state (invariant preservation).
• m/z values post-replacement remain increasingly sorted within each spectrum; is.unsorted() returns FALSE for all modified spectra.
• m/z replacement vectors contain no NA values; all replacement operations succeed without introducing missing values in critical peak data.
• Concrete backend instance (e.g., MsBackendMemory) passes all unit tests confirming writable functionality and constraint enforcement.

Limitations

• Replacement methods are only available for writable backends (e.g., MsBackendMemory, MsBackendDataFrame); partially read-only backends like MsBackendMzR do not support peak data replacement, only spectra variable modification.
• m/z ordering constraint assumes increasingly sorted order within each spectrum; data with unsorted or reversed m/z values will fail validation and cannot be stored.
• Length matching constraint requires exact correspondence between replacement vector length and spectrum count or peak count; subsetting and reordering must be handled separately via extractByIndex() or other subsetting operations.
• No support for sparse or variable-length peak data structures; all spectra must maintain consistent peak-count relationships (if present).
• NA values are not permitted in m/z vectors; spectra with missing m/z measurements cannot be represented in this framework.

Evidence

• [other] length matching via .match_length() to ensure value length equals spectrum count: "length matching via .match_length() to ensure value length equals spectrum count"
• [other] data type validation checking that m/z and intensity are NumericList objects: "data type validation checking that m/z and intensity are NumericList objects"
• [other] peak-count preservation requiring that replacement values maintain the same number of peaks per spectrum: "peak-count preservation requiring that replacement values maintain the same number of peaks per spectrum"
• [other] m/z ordering validation using is.unsorted() to verify m/z values are increasingly sorted within each spectrum: "m/z ordering validation using is.unsorted() to verify m/z values are increasingly sorted within each spectrum"
• [intro] m/z values within each spectrum are expected to be sorted increasingly. Missing values (NA) for m/z values are not supported.: "m/z values within each spectrum are expected to be sorted increasingly. Missing values (NA) for m/z values are not supported."
• [intro] MsBackend implementations can also represent purely read-only data resources. In this case only data accessor methods need to be implemented but not data replacement methods.: "MsBackend implementations can also represent purely read-only data resources. In this case only data accessor methods need to be implemented but not data replacement methods."
• [other] Implement input validation in each replacement method to check that replacement vectors match the length of the backend (number of spectra) or individual spectrum peak counts.: "Implement input validation in each replacement method to check that replacement vectors match the length of the backend (number of spectra) or individual spectrum peak counts."
• [other] For peak data replacement, verify that m/z values remain sorted in increasing order within each spectrum and that intensity vector length equals m/z vector length.: "For peak data replacement, verify that m/z values remain sorted in increasing order within each spectrum and that intensity vector length equals m/z vector length."