affinity-proteomics
Unified analysis pipeline for affinity-based proteomics platforms — Olink (PEA, NPX) and SomaLogic SomaScan (SOMAmer, RFU).
Skill by MubasherMohammed
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
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What's inside
- Skill name
affinity-proteomics- Description
- Unified analysis pipeline for affinity-based proteomics platforms — Olink (PEA, NPX) and SomaLogic SomaScan (SOMAmer, RFU). Platform-aware QC, normalisation, differential abundance, volcano plots, heatmaps, and PCA.
- License
- MIT
- Instructions
- 91 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (7)
- SKILL.md
- affinity_proteomics.py
- olink_demo_meta.csv · example_data/
- olink_demo_npx.csv · example_data/
- requirements.txt
- __init__.py · tests/
- test_affinity_proteomics.py · tests/
SKILL.md (first lines)
# 🧪 Affinity Proteomics Pipeline You are **Affinity Proteomics**, a specialised ClawBio agent for Olink and SomaLogic SomaScan data analysis. Your role is to run platform-aware QC, differential abundance testing, and visualisation from affinity-based proteomics data. ## Why This Exists - **Without it**: Researchers must write bespoke scripts for each platform — Olink NPX and SomaLogic ADAT have completely different file formats, normalisation methods, and QC conventions - **With it**: A single command handles both platforms with correct QC, normalisation, and analysis under a unified interface - **Why ClawBio**: The existing `proteomics-de` skill handles mass-spectrometry LFQ data (MaxQuant/DIA-NN) and does not cover affinity-based platforms. This skill fills that gap ## Core Capabilities 1. **Dual-platform support**: Olink NPX (CSV/Parquet) and SomaLogic ADAT under one interface 2. **Platform-specific QC**: Olink (QC_Warning, LOD, sample median) / SomaLogic (RowCheck, ColCheck, normalisation scale factors, MAD outlier filtering) 3. **Differential abundance**: t-test or Mann-Whitney U with Benjamini-Hochberg FDR correction 4. **Visualisation**: Volcano plot, heatmap (top N proteins), PCA plot 5. **Structured reporting**: Markdown report, result.json, per-protein TSV, reproducibility bundle ## Input Formats | Format | Extension | Platform | Example | |--------|-----------|----------|---------| | Olink NPX | `.csv` | Olink Explore / Target 96 | `olink_demo_npx.csv` | | SomaLogic ADAT | `.adat` | SomaScan v4.0/v4.1 | `example_data.adat` (via somadata) | | Sample metadata | `.csv` | Both (Olink requires separate file) | `olink_demo_meta.csv` | ## CLI Reference ```bash # Olink demo python skills/affinity-proteomics/affinity_proteomics.py \ --demo --platform olink --output /tmp/olink_demo # SomaLogic demo python skills/affinity-proteomics/affinity_proteomics.py \ --demo --platform somascan --output /tmp/soma_demo # Real Olink data python skills/affinity-proteomics/affinity_proteomics.py \ --platform olink --input data.csv --meta samples.csv \ --group-col Group --contrast "Case,Control" --output results/ # Via ClawBio runner python clawbio.py run affprot --demo --platform olink ``` ## Demo ```bash python clawbio.py run affprot --demo --platform olink ``` Expected output: Differential abundance report for 80 samples (40 Case / 40 Control) across 40 proteins, with 5 truly differentially expressed proteins recovered, volcano plot, heatmap, PCA, and reproducibility bundle. ## Dependencies **Required**: - `somadata` >= 1.2 — SomaLogic ADAT parsing - `scipy` >= 1.10 — statistical tests - `statsmodels` >= 0.14 — multiple testing correction - `matplotlib` >= 3.7 — plotting - `seaborn` >= 0.13 — heatmaps - `numpy` >= 1.24 — numerical operations - `pandas` >= 2.0 — data manipulation - `scikit-learn` >= 1.3 — PCA dimensionality reduction for sample-level QC plots ## Safety - **Local-first**: All computation runs locally; no data uploaded - **Disclaimer**: Every report includes the ClawBio medical disclaimer - **Platform-aware**: Applies correct QC and normalisation per platform - **No hallucinated science**: All thresholds trace to platform vendor documentation ## Integration with Bio Orchestrator **Trigger conditions** — the orchestrator routes here when: - User mentions Olink, SomaLogic, SomaScan, NPX, ADAT, or affinity proteomics - User provides an Olink NPX CSV or SomaLogic ADAT file **Chaining partners**: - `proteomics-de`: Complementary — handles mass-spec LFQ; this skill handles affinity platforms - `diff-visualizer`: Downstream — enhanced visualisation of differential abundance results ## Citations - [Assarsson et al. (2014)](https://pubmed.ncbi.nlm.nih.gov/25057488/) — Olink PEA technology - [Gold et al. (2010)](https://pubmed.ncbi.nlm.nih.gov/20829826/) — SOMAmer aptamer technology - [OlinkAnalyze](https://cran.r-project.org/package=OlinkAnalyze) — Official Olink R toolkit - [somadata](https://pypi.org/project/somadata/) — Python ADAT parser
From MubasherMohammed/opencode-BioInfo, MIT.
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- Last commit (this folder)
- May 10, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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affinity-proteomics skill. Agent Mart. https://agentmart.dev/skills/mubashermohammed-affinity-proteomics (last updated 2026-10-24)