imspy-search

Database search functionality for timsTOF proteomics data using sagepy.

Installation

pip install imspy-search

Features

• Database Search: SAGE-based database search for timsTOF DDA data
• PSM Rescoring: Machine learning-based rescoring of peptide-spectrum matches
• FDR Control: Target-decoy competition and q-value estimation
• MGF Support: Parse and search Bruker DataAnalysis MGF files
• CLI Tools: Command-line interfaces for common workflows

Quick Start

from imspy_search import (
    extract_timstof_dda_data,
    get_searchable_spec,
    generate_balanced_rt_dataset,
    generate_balanced_im_dataset,
)

# Extract DDA data for database search
fragments = extract_timstof_dda_data(
    path="path/to/data.d",
    num_threads=16,
)

CLI Tools

imspy-dda

Full DDA search pipeline with intensity prediction and rescoring:

imspy-dda /path/to/data /path/to/fasta.fasta --config config.toml

imspy-ccs

Extract CCS values from DDA data for machine learning:

imspy-ccs --raw_data_path /path/to/data --fasta_path /path/to/fasta.fasta

imspy-rescore-sage

Rescore SAGE search results with deep learning features:

imspy-rescore-sage results.tsv fragments.tsv /output/path

Submodules

• utility: Core utility functions for database search
• sage_output_utility: SAGE output processing and rescoring
• mgf: MGF file parsing for sagepy queries
• rescoring: PSM rescoring with deep learning features
• dda_extensions: TimsDatasetDDA extensions for sagepy
• cli/: Command-line interface tools

Dependencies

• imspy-core: Core data structures (required)
• imspy-predictors: ML predictors for CCS, RT, intensity (required)
• sagepy: SAGE database search framework (required)
• mokapot: Machine learning for PSM scoring (required)

Related Packages

• imspy-core: Core data structures and timsTOF readers
• imspy-predictors: ML-based predictors
• imspy-simulation: Simulation tools for timsTOF data
• imspy-vis: Visualization tools

License

MIT License - see LICENSE file for details.