External Tutorials & Communities

A curated set of external tutorials, best-practices books, framework documentation, and communities to lean on during the workshop and long after it.

Living best-practices books

Long-form, opinionated guides written by working practitioners. Read at least one cover-to-cover during the workshop.

• Single-cell best practices (Heumos et al.) — the canonical online textbook for the field. Strong on rationale, comparisons, and pitfalls. Source for the workshop glossary.
• Orchestrating Single-Cell Analysis with Bioconductor (OSCA) — Amezquita, Lun, Bays, Hicks et al. The Bioconductor / SingleCellExperiment perspective, with running examples.
• Analysis of single-cell RNA-seq data (Sanger / EBI course) — a complete course-style book, free and updated regularly.
• scNotebooks — Integrative Bioinformatics for Single-cell and Spatial Genomics — a notebook-driven companion that walks the same canonical scRNA-seq workflow plus spatial / multi-omic chapters. We borrow pedagogical pacing (multi-step QC, integration diagnostics) from this resource and credit it in each tutorial that does so.

Framework documentation & tutorials

• Seurat tutorials — the workshop’s primary R framework. Start with the PBMC 3k guided clustering tutorial, then look at integration and reference mapping.
• Scanpy tutorials — the Python equivalent. The PBMC tutorial mirrors Seurat’s so you can compare side-by-side.
• scverse — the Python single-cell ecosystem (AnnData, Scanpy, Muon, scvi-tools, squidpy).
• Signac — scATAC-seq in R, Seurat-compatible.
• ArchR — scATAC-seq in R, alternative to Signac; strong visualization.
• squidpy — spatial transcriptomics in Python.

Pipelines & raw-data processing

For the raw-reads → counts step (workshop Modules 11–12) and scaling beyond shell scripts.

• Cell Ranger documentation and Cell Ranger ATAC — the official 10x guides for turning raw FASTQs into counts / peaks.
• nf-core/scrnaseq and the broader nf-core / Nextflow project — reproducible, portable pipelines for processing single-cell data at scale.
• Snakemake — a Python-based workflow manager, a natural next step from the workshop’s numbered SLURM scripts.
• STARsolo and alevin-fry / salmon — fast open-source alternatives to Cell Ranger for read quantification.

Communities & courses

• scverse Discourse — the friendliest place to ask Python single-cell questions.
• Bioconductor support — for R / Bioconductor questions.
• Single Cell Genomics Day (NYGC) — annual recap of tools and methods.
• Sanger Single-Cell Course — self-paced, free.