Geniml
원문: geniml
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
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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: For ML dependencies (PyTorch, etc.): Development version from GitHub: Core Capabilities Geniml provides five primary capabilities, each detailed in dedicated reference files: 1. Region2Vec: Genomic Region Embeddings Train unsupervised embeddings of genomic regions using word2vec style learning. Use for: Dimensionality reducti…
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