imspy-predictors
ML-based predictors for CCS, retention time, and fragment intensity in mass spectrometry.
Installation
pip install imspy-predictors
For remote model access via Koina servers:
pip install imspy-predictors[koina]
Features
- CCS Prediction: Deep learning models for collision cross section / ion mobility prediction
- Retention Time Prediction: GRU-based retention time predictors
- Fragment Intensity Prediction: Prosit 2023 timsTOF intensity predictor
- Charge State Prediction: Binomial and deep learning charge state distribution models
- Koina Integration: Access remote prediction models via Koina servers (optional)
Available Koina Remote Models
When using pip install imspy-predictors[koina], remote models can be configured in TimSim's [models] TOML section:
| Task | Model Name |
|---|---|
| RT | Deeplc_hela_hf, Chronologer_RT, AlphaPeptDeep_rt_generic, Prosit_2019_irt |
| CCS | AlphaPeptDeep_ccs_generic, IM2Deep |
| Intensity | prosit, alphapeptdeep, ms2pip |
[models]
rt_model = "AlphaPeptDeep_rt_generic"
ccs_model = "" # "" = local PyTorch model
intensity_model = "prosit"
Quick Start
from imspy_predictors import (
load_deep_ccs_predictor,
load_deep_retention_time_predictor,
Prosit2023TimsTofWrapper,
)
# Load CCS predictor
ccs_model = load_deep_ccs_predictor()
# Load RT predictor
rt_model = load_deep_retention_time_predictor()
# Load intensity predictor
intensity_model = Prosit2023TimsTofWrapper()
Submodules
- ccs/: CCS / ion mobility prediction
- rt/: Retention time prediction
- intensity/: Fragment intensity prediction (Prosit)
- ionization/: Charge state distribution prediction
- koina_models/: Koina remote model access (requires
koinapy) - utilities/: Tokenizers for ML models
Dependencies
- imspy-core: Core data structures (required)
- PyTorch: Deep learning framework (required)
- koinapy: Koina API client (optional, for remote models)
Optional Dependencies
Some functionality requires additional packages:
- imspy-search: For PSM-based predictions using sagepy
- imspy-simulation: For simulation utilities (e.g., flatten_prosit_array)
Related Packages
- imspy-core: Core data structures and timsTOF readers
- imspy-search: Database search functionality
- imspy-simulation: Simulation tools for timsTOF data
- imspy-vis: Visualization tools
License
MIT License - see LICENSE file for details.
Metadata
Release files for imspy-predictors 0.5.2
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Total release size: 218.7 kB
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