numpy

• main purpose
• • fast numerical computations with arrays
• typical application
• • gene expression matrix, linear algebra

pandas

• main purpose
• • tabular data processing (like excel)
• typical application
• • cell and gene metadata

anndata

• main purpose
• • structured storage of cell & gene data
• typical application
• • container for scRNA-seq/scATAC-seq data

scanpy

• main purpose
• • complete analysis pipeline for scRNA-seq (and ATAC)
• typical application
• • normalization clustering, UMAP, marker genes

matplotlib

• main purpose
• • basic visualization package
• typical application
• • UMAPs, violin plots, axis titles, layout

seaborn

• main purpose
• • high-level statistical visualization
• typical application
• • gene expression by cell type, heatmaps

muon (optional)

• main purpose
• • multi-omics analysis (combined RNA + ATAC)
• typical application
• • simultaneous analysis of scRNA & scATAC