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Agent Skills with tag: anndata

8 skills match this tag. Use tags to discover related Agent Skills and explore similar workflows.

anndata

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

anndatasingle-cell-rna-seqh5adscanpy
ovachiever
ovachiever
81

single-cell-rna-qc

Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.

single-cell-rna-seqscanpyanndataquality-control
biocontext-ai
biocontext-ai
103

lobster-bioinformatics

Run bioinformatics analyses using Lobster AI - single-cell RNA-seq, bulk RNA-seq, literature mining, dataset discovery, quality control, and visualization. Use when analyzing genomics data, searching for papers/datasets, or working with H5AD, CSV, GEO/SRA accessions, or biological data. Requires lobster-ai package installed.

single-cell-rna-seqrna-seqanndatapublic-datasets
the-omics-os
the-omics-os
421

single-cell-rna-qc

Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.

single-cell-rna-seqanndatascanpyquality-control
anthropics
anthropics
12020

scvi-tools

This skill should be used when working with single-cell omics data analysis using scvi-tools, including scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics, and other single-cell modalities. Use this skill for probabilistic modeling, batch correction, dimensionality reduction, differential expression, cell type annotation, multimodal integration, and spatial analysis tasks.

pythonmachine-learninganndatasingle-cell-omics
K-Dense-AI
K-Dense-AI
3,233360

cellxgene-census

Query CZ CELLxGENE Census (61M+ cells). Filter by cell type/tissue/disease, retrieve expression data, integrate with scanpy/PyTorch, for population-scale single-cell analysis.

single-cell-rna-seqtranscriptomicsscanpyAPI
K-Dense-AI
K-Dense-AI
3,233360

scanpy

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

scanpypythonsingle-cell-rna-seqanndata
K-Dense-AI
K-Dense-AI
3,233360

anndata

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

pythonanndatah5adscanpy
K-Dense-AI
K-Dense-AI
3,233360