This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building co…
---
name: geniml
description: This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
license: BSD-2-Clause license
metadata: {"version": "1.0", "skill-author": "K-Dense Inc."}
---
# Geniml: Genomic Interval Machine Learning
## Overview
Geniml is a Python package for building machine learning models on genomic interval data from BED files. It provides unsupervised methods for learning embeddings of genomic regions, single cells, and metadata labels, enabling similarity searches, clustering, and downstream ML tasks.
## Installation
Install geniml using uv:
```bash
uv pip install geniml
```
For ML dependencies (PyTorch, etc.):
```bash
uv pip install 'geniml[ml]'… load the full skill through Skill Me