Automate single-cell sequencing data annotation with Python scripts.
npx skills add https://github.com/cas-bigdatalab/piflow --skill bdbe-cellanno
Please help me install this Agent Skill. Skill: bdbe_cellanno Source: https://github.com/cas-bigdatalab/piflow/tree/main/workspace/skills/bdbe_cellanno Command: npx skills add https://github.com/cas-bigdatalab/piflow --skill bdbe-cellanno
This Skill automates the annotation of single-cell sequencing data, simplifying the complex process of assigning biological function tags to each cell.
Annotate your single-cell sequencing data using the bdbe_cellanno skill. Upload your data file and specify the species.
High-intent search queries and answers about installing and using this skill.
Single-cell data annotation assigns biological function tags to individual cells within sequencing datasets. This process is necessary when researchers need to identify cell types across large-scale biological research workflows efficiently.
You can use this single-cell data annotation skill by uploading your sequencing data file and specifying the target species. The Python script then processes the dataset automatically to retrieve cell type annotation results.
Yes, you can use this skill for large single-cell datasets by uploading your sequencing data file. It is specifically designed for biological research workflows to significantly reduce the time and effort required for cell type annotation.
This skill requires the requests Python dependency to run. It uses script components to automate single-cell data upload, processing, and result retrieval without requiring additional complex environment setups.
Automated Python scripts provide an efficient way to handle gene mapping, data standardization, and dimensionality reduction for single-cell data. This approach streamlines the complex process of assigning biological function tags to each cell.
omicverseInfer gene regulatory networks from single-cell RNA sequencing data.
anthropicsFilter low-quality cells from single-cell RNA-seq data using MAD-based QC.
galeepAutomates scRNA-seq analysis including QC, normalization, clustering, and visualization with AnnData and scanpy.
jaechang-hitsGuide cell type annotation strategy selection for single-cell RNA-seq analysis.
