bio-machine-learning-omics-classifiers
OfficialTrain omics classifiers with scalable sklearn
Data & Analytics#classification#preprocessing#pipelines#omics#machine-learning#scikit-learn#biomarkers
Authorstellaromics
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Biologists and data scientists need ready-to-use workflows to build diagnostic or prognostic classifiers from omics data, with consistent preprocessing, model selection, and evaluation.
Core Features & Use Cases
- Preprocessing pipelines for common omics data types (gene expression, variants, and multi-omics)
- Train and evaluate classifiers using RandomForest, XGBoost, and logistic regression with sklearn-compatible APIs
- End-to-end workflows for biomarker discovery, model comparison, and performance reporting
Quick Start
Provide a gene expression matrix and labels to train a classifier using the included sklearn-compatible pipeline.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
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Please help me install this Skill: Name: bio-machine-learning-omics-classifiers Download link: https://github.com/stellaromics/fast-bioinfo/archive/main.zip#bio-machine-learning-omics-classifiers Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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