class-conditional-calibration-mapping
Summary
Compute collision cross section (CCS) values for ions stratified by biomolecular class assignment, using class-specific reference standards to calibrate drift-time-to-CCS relationships without requiring prior feature identification. This enables direct CCS calculation from TWIM-MS arrival time data conditioned on experimental class labels.
When to use
Apply this skill when you have TWIM-MS experimental data (arrival times and ion mobility parameters) paired with pre-assigned biomolecular class labels for an ion population, and you need to obtain class-conditioned CCS values without first performing feature-level identification. This is especially valuable in high-dimensional multi-omic workflows where class assignment precedes feature detection.
When NOT to use
- Input ions lack pre-assigned biomolecular class labels or class assignment is unavailable.
- Reference standard calibration sets are not available or defined for the classes present in your data.
- Raw uncalibrated TWIM data has not been processed to extract arrival times and ion mobility parameters.
Inputs
- Biomolecular class assignments (ion identifier → class label mapping)
- TWIM-MS experimental data: arrival times and ion mobility parameters
- Class-specific reference standard calibration data
Outputs
- Ion identifier table with class labels and class-conditioned CCS values
How to apply
Partition the ion population by assigned class label. For each class stratum, extract arrival time measurements and convert to drift time by subtracting the time-of-flight offset. Apply the appropriate reference standard calibration set for that biomolecular class to establish a class-specific drift-time-to-CCS mapping function. Compute CCS for each ion using its calibrated relationship. Output a table mapping ion identifiers to both their class labels and class-conditioned CCS values. The rationale is that different biomolecular classes (e.g., lipids, peptides, carbohydrates) may have different ion behavior in TWIM, so using class-matched calibration standards improves accuracy over global calibration.
Related tools
- MOCCal (Python application that implements class-specific CCS calibration workflow, partitions ions by class label, and computes class-conditioned CCS values from TWIM-MS data) — https://github.com/HinesLab/MOCCal
- DEIMoS (Dependency for MOCCal_RawDT.py; required to preprocess raw calibration files before class-conditional calibration) — http://github.com/pnnl/deimos
Evaluation signals
- Class-stratified CCS outputs have no missing or null values for ions assigned to defined classes.
- CCS values fall within expected ranges for their assigned biomolecular class (e.g., lipids typically 200–600 Ų; peptides 400–1200 Ų).
- Class-specific calibration R² or RMSE values meet acceptable thresholds (article does not specify exact cutoffs, but calibration fit should be documented).
- Ion count per class matches the input partition; no ions are dropped or misallocated during class-conditional processing.
- CCS values computed from the same drift time differ only if ions are assigned to different classes, demonstrating class-conditional differentiation.
Limitations
- Requires pre-existing biomolecular class assignments; skill cannot perform de novo class discovery or inference.
- Accuracy depends on availability and quality of class-specific reference standard calibration sets; missing or low-quality standards for a class will degrade CCS computation for that class.
- TWIM platforms record arrival time (time at detector) rather than drift time (time in TWIM cell); conversion requires accurate time-of-flight offset, which must be independently determined.
- No changelog or version history provided in the repository, making it difficult to track improvements, bug fixes, or methodological changes over time.
Evidence
- [other] MOCCal performs experimental class-specific CCS calculations as a workflow component that operates on biomolecular class assignments, enabling CCS computation without requiring prior feature identification.: "MOCCal performs experimental class-specific CCS calculations as a workflow component that operates on biomolecular class assignments, enabling CCS computation without requiring prior feature"
- [other] Partition the ion population by assigned class label. For each class stratum, extract arrival time measurements and convert to drift time by subtracting the time-of-flight offset. Apply class-specific CCS calibration using the appropriate reference standard set for that biomolecular class.: "Partition the ion population by assigned class label. For each class stratum, extract arrival time measurements and convert to drift time by subtracting the time-of-flight offset. Apply"
- [readme] TWIM platforms record the time at which the ion reaches the detector (arrival time) rather than the time an ion spends within the TWIM cell (drift time).: "TWIM platforms record the time at which the ion reaches the detector (arrival time) rather than the time an ion spends within the TWIM cell (drift time)."
- [intro] MOCCal offers class assignment and CCS calculations without need for identifying the features first.: "MOCCal offers class assignment and CCS calculations without need for identifying the features first."
- [intro] Functionality includes collision cross section (CCS) calibration, experimental data biomolecular class assignment, and experimental class-specific CCS calculations.: "Functionality includes collision cross section (CCS) calibration, experimental data biomolecular class assignment, and experimental class-specific CCS calculations."
1---2name: class-conditional-calibration-mapping3description: Use when you have TWIM-MS experimental data (arrival times and ion mobility parameters) paired with pre-assigned biomolecular class labels for an ion population, and you need to obtain class-conditioned CCS values without first performing feature-level identification.4license: CC-BY-4.05---67# class-conditional-calibration-mapping89## Summary1011Compute collision cross section (CCS) values for ions stratified by biomolecular class assignment, using class-specific reference standards to calibrate drift-time-to-CCS relationships without requiring prior feature identification. This enables direct CCS calculation from TWIM-MS arrival time data conditioned on experimental class labels.1213## When to use1415Apply this skill when you have TWIM-MS experimental data (arrival times and ion mobility parameters) paired with pre-assigned biomolecular class labels for an ion population, and you need to obtain class-conditioned CCS values without first performing feature-level identification. This is especially valuable in high-dimensional multi-omic workflows where class assignment precedes feature detection.1617## When NOT to use1819- Input ions lack pre-assigned biomolecular class labels or class assignment is unavailable.20- Reference standard calibration sets are not available or defined for the classes present in your data.21- Raw uncalibrated TWIM data has not been processed to extract arrival times and ion mobility parameters.2223## Inputs2425- Biomolecular class assignments (ion identifier → class label mapping)26- TWIM-MS experimental data: arrival times and ion mobility parameters27- Class-specific reference standard calibration data2829## Outputs3031- Ion identifier table with class labels and class-conditioned CCS values3233## How to apply3435Partition the ion population by assigned class label. For each class stratum, extract arrival time measurements and convert to drift time by subtracting the time-of-flight offset. Apply the appropriate reference standard calibration set for that biomolecular class to establish a class-specific drift-time-to-CCS mapping function. Compute CCS for each ion using its calibrated relationship. Output a table mapping ion identifiers to both their class labels and class-conditioned CCS values. The rationale is that different biomolecular classes (e.g., lipids, peptides, carbohydrates) may have different ion behavior in TWIM, so using class-matched calibration standards improves accuracy over global calibration.3637## Related tools3839- **MOCCal** (Python application that implements class-specific CCS calibration workflow, partitions ions by class label, and computes class-conditioned CCS values from TWIM-MS data) — https://github.com/HinesLab/MOCCal40- **DEIMoS** (Dependency for MOCCal_RawDT.py; required to preprocess raw calibration files before class-conditional calibration) — http://github.com/pnnl/deimos4142## Evaluation signals4344- Class-stratified CCS outputs have no missing or null values for ions assigned to defined classes.45- CCS values fall within expected ranges for their assigned biomolecular class (e.g., lipids typically 200–600 Ų; peptides 400–1200 Ų).46- Class-specific calibration R² or RMSE values meet acceptable thresholds (article does not specify exact cutoffs, but calibration fit should be documented).47- Ion count per class matches the input partition; no ions are dropped or misallocated during class-conditional processing.48- CCS values computed from the same drift time differ only if ions are assigned to different classes, demonstrating class-conditional differentiation.4950## Limitations5152- Requires pre-existing biomolecular class assignments; skill cannot perform de novo class discovery or inference.53- Accuracy depends on availability and quality of class-specific reference standard calibration sets; missing or low-quality standards for a class will degrade CCS computation for that class.54- TWIM platforms record arrival time (time at detector) rather than drift time (time in TWIM cell); conversion requires accurate time-of-flight offset, which must be independently determined.55- No changelog or version history provided in the repository, making it difficult to track improvements, bug fixes, or methodological changes over time.5657## Evidence5859- [other] MOCCal performs experimental class-specific CCS calculations as a workflow component that operates on biomolecular class assignments, enabling CCS computation without requiring prior feature identification.: "MOCCal performs experimental class-specific CCS calculations as a workflow component that operates on biomolecular class assignments, enabling CCS computation without requiring prior feature"60- [other] Partition the ion population by assigned class label. For each class stratum, extract arrival time measurements and convert to drift time by subtracting the time-of-flight offset. Apply class-specific CCS calibration using the appropriate reference standard set for that biomolecular class.: "Partition the ion population by assigned class label. For each class stratum, extract arrival time measurements and convert to drift time by subtracting the time-of-flight offset. Apply"61- [readme] TWIM platforms record the time at which the ion reaches the detector (arrival time) rather than the time an ion spends within the TWIM cell (drift time).: "TWIM platforms record the time at which the ion reaches the detector (arrival time) rather than the time an ion spends within the TWIM cell (drift time)."62- [intro] MOCCal offers class assignment and CCS calculations without need for identifying the features first.: "MOCCal offers class assignment and CCS calculations without need for identifying the features first."63- [intro] Functionality includes collision cross section (CCS) calibration, experimental data biomolecular class assignment, and experimental class-specific CCS calculations.: "Functionality includes collision cross section (CCS) calibration, experimental data biomolecular class assignment, and experimental class-specific CCS calculations."
HolobiomicsLab 