lobster-proteomics
Unified proteomics analysis for mass spectrometry (DDA/DIA) and affinity platforms (Olink, SomaScan).
Installation
pip install lobster-proteomics
Agents
| Agent | Description |
|---|---|
proteomics_expert |
Full proteomics workflow orchestration with auto-detection of platform type and appropriate preprocessing. |
Services
| Service | Purpose |
|---|---|
| ProteomicsAnalysisService | Core analysis workflows for protein quantification |
| ProteomicsDifferentialService | Differential protein expression between conditions |
| ProteomicsSurvivalService | Survival analysis with protein biomarkers |
| ProteomicsNetworkService | Protein-protein interaction network analysis |
| ProteomicsQualityService | Quality control and missing value assessment |
| ProteomicsPreprocessingService | MNAR/MAR-aware imputation and normalization |
| ProteomicsVisualizationService | Volcano plots, heatmaps, and network graphs |
| MaxQuantParser | Parse MaxQuant proteinGroups.txt output |
| DIANNParser | Parse DIA-NN report.tsv output |
| SpectronautParser | Parse Spectronaut report output |
| OlinkParser | Parse Olink NPX export files |
Features
- Auto-detection of platform type from data characteristics
- Missing value handling optimized for MNAR (mass spec) vs MAR (affinity) patterns
- Platform-appropriate quality control with batch effect detection
- Median and quantile normalization with log2 transformation
- Multiple imputation strategies (MinDet, KNN, zero, median)
- Differential protein analysis with multiple testing correction
- Volcano plots and MA plots for results visualization
- Protein-protein interaction network construction and visualization
- Survival analysis integration for clinical proteomics studies
- Support for multi-plex affinity platforms (Olink, SomaScan, Luminex)
Platform Support
| Platform | Missing Values | Normalization | Notes |
|---|---|---|---|
| Mass Spectrometry (DDA/DIA) | 30-70% (MNAR) | Median + log2 | Peptide mapping support |
| Affinity (Olink) | <30% (MAR) | Quantile | Plate effect correction |
| Affinity (SomaScan) | <30% (MAR) | Quantile | Antibody validation |
Requirements
- Python 3.12+
- lobster-ai >= 1.0.0
Tier Requirement
This is a free agent. Access is controlled at runtime via Lobster AI's tier system.
Documentation
Full documentation: docs.omics-os.com/docs/agents/proteomics
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for lobster-proteomics 1.1.425
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| lobster_proteomics-1.1.425.tar.gz | 198.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| lobster_proteomics-1.1.425-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 414.9 kB
Release files / lobster_proteomics-1.1.425.tar.gz
| Download URL | lobster_proteomics-1.1.425.tar.gz |
|---|---|
| Size | 198.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
e6c08a99ff4a0a72563e237f363f2bb6e20755e2687b57d9643f50279b61a0b1
|
|
BLAKE2b-256 checksum How to use checksums |
90fa1bc6e40a87d7889f1bc7050e80aa5645fb0a59da4c4f59423770bc87b568
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency logRelease files / lobster_proteomics-1.1.425-py3-none-any.whl
| Download URL | lobster_proteomics-1.1.425-py3-none-any.whl |
|---|---|
| Size | 216.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
408a27fec4ea98d41f4a15aa29dbe44b75e5162e1dc7d1a7e1a07abfc3ffc1dd
|
|
BLAKE2b-256 checksum How to use checksums |
33c64afbed1e0a5badd88863062099d8536796f5c4fb1885e87be3c62932c721
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency log
