AI & LLM Engineering · UMAP

UMAP dimensionality reduction. An agent skill from davila7/claude-code-templates.

davila7/claude-code-templates

Applies UMAP-learn to nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows.

K-Dense-AI/scientific-agent-skills

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions)…

GPTomics/bioSkills

A skill your agent uses when performing sample-level dimensionality reduction and visualization on abundance or OTU-style matrices with a companion group file, generating UMAP and/or t-SNE…

aipoch/medical-research-skills

Unsupervised clustering and cell-type identification for high-dimensional flow, spectral, and mass cytometry - FlowSOM, PhenoGraph, FlowSOM-via-CATALYST, with UMAP/tSNE for visualization.

GPTomics/bioSkills

Load when building the neighbour graph, embedding (UMAP/t-SNE/diffmap/PHATE), and clustering (Leiden/Louvain) on a normalised single-cell AnnData.

TianGzlab/OmicsClaw

Load when removing batch effects from multi-batch spatial AnnData with PCA using Harmony, BBKNN, or Scanorama.

TianGzlab/OmicsClaw

UMAP dimensionality reduction for visualization, clustering prep, and feature engineering.

jaechang-hits/SciAgent-Skills