SpatiaBio Pack 1 — Squidpy Foundations

16 ready-to-run Jupyter notebooks covering the complete Squidpy spatial transcriptomics pipeline — with all cell outputs already included.What's included:00. Environment setup — conda env, package versions, Space Ranger structure01. Data loading — AnnData format, QC metrics, spatial coordinate validation02. Clustering — normalization → PCA → Leiden → marker genes03. Spatial neighbors — Delaunay vs kNN vs radius graphs03b. Large dataset memory — chunked processing, sparse matrices04. Neighborhood enrichment — z-score interpretation, n_perms guide05. Co-occurrence — distance decay analysis06. Spatial autocorrelation — Moran's I, spatially variable genes06b. Batch correction — Harmony, BBKNN07. Ligand-receptor — sq.gr.ligrec, CellPhoneDB v408. SVG visualization — custom colormaps, multi-panel figures09. Squidpy vs Seurat — side-by-side comparison, benchmarks10. Complete workflow — full pipeline in one notebook11. Result interpretation — biological interpretation guide12. Common errors — diagnosis and fixes for all common failures13. Publication figures — Nature-style 3-panel figuresWho it's for: Researchers learning Squidpy, bioinformaticians switching from Seurat, anyone running spatial transcriptomics on IMC, Visium, or MERFISH data.Requirements: pip install squidpy scanpy leidenalg · Python 3.10+ · No data download needed (uses built-in Squidpy datasets)

Found on Devadex — the discovery index for independent software the big search engines bury. More from gumroad.

Report this listing