Analyze annotated single-cell RNA-seq data stored in AnnData structures.
npx skills add https://github.com/swaruplab/operon-omp --skill ann-data
Please help me install this Agent Skill. Skill: ann-data Source: https://github.com/swaruplab/operon-omp/tree/main/src-tauri/protocols/anndata Command: npx skills add https://github.com/swaruplab/operon-omp --skill ann-data
This Skill allows computational biologists to manage and analyze annotated single-cell RNA-seq data effectively, reducing manual analysis steps and ensuring accurate and efficient analysis workflows.
Extract high-quality, highly variable genes from an AnnData object stored in 'filtered.h5ad' using AnnData features and export to a new h5ad file.
High-intent search queries and answers about installing and using this skill.
To filter and transform single-cell RNA-seq data in h5ad files, you subsetting, filtering, and transformation operations directly on AnnData objects to process large-scale sparse datasets.
Handling large-scale single-cell RNA-seq datasets is best achieved using AnnData structures, which manage sparse data formats and facilitate efficient data access, manipulation, and input/output operations across formats like h5ad and zarr.
AnnData works seamlessly with Scanpy, scvi-tools, and cellxgene-census, enabling extended data analysis, transformation, and visualization within the broader scverse ecosystem for single-cell RNA-seq workflows.
You can read and write single-cell RNA-seq data to various formats including h5ad, zarr, and CSV, allowing you to work with and export large datasets efficiently across different analysis environments.
To extract highly variable genes and perform dimensionality reduction on single-cell data, you filter high-quality cells from an AnnData object, apply transformation operations, and generate visualizations to interpret your results.
When processing sparse single-cell RNA-seq data, limitations depend on efficiently managing large-scale formats, as AnnData structures are specifically designed to handle sparse matrices and facilitate subsetting without compromising data integrity.
MubasherMohammedGenerate visualizations and reports for bulk and single-cell RNA-seq differential expression.
galeepAutomates scRNA-seq analysis including QC, normalization, clustering, and visualization with AnnData and scanpy.
tony-zhelonkinRun standard single-cell RNA-seq analysis with Scanpy on AnnData objects.
KetomihineInfer ligand-receptor interactions from single-cell and spatial omics data with LIANA+.
