AnnData Scientific Data Management

소개

This skill provides specialized guidance for working with AnnData objects, the foundational data structure for single-cell genomics and large-scale biological measurements. It assists users in creating, manipulating, and storing complex datasets with multi-dimensional annotations (obs, var, obsm, layers), ensuring full compatibility with the scverse ecosystem tools like Scanpy and scvi-tools. Whether you are performing quality control, subsetting massive datasets in memory-efficient backed mode, or concatenating multiple experimental batches, this skill offers the implementation patterns and performance-optimized practices required for robust biological data analysis.

주요 기능

• Efficient data manipulation, subsetting, and filtering techniques
• Advanced dataset concatenation and batch integration strategies
• High-performance I/O for h5ad, zarr, loom, and 10X formats
• Memory-efficient practices including sparse matrices and backed mode
• Comprehensive AnnData object creation and metadata management
• 0 GitHub stars

사용 사례

• Integrating multiple experimental batches into unified annotated datasets
• Single-cell RNA-seq preprocessing, normalization, and quality control
• Analyzing massive genomics datasets that exceed available system memory