Upstream Processing Skills

Skills and workflows for upstream data processing steps that precede standard single-cell analysis (QC, normalization, clustering, etc.). These cover technology-specific pipelines from raw sequencing data to analysis-ready count matrices with spatial coordinates.

Available Skills

OpenST

Open-ST is an open-source spatial transcriptomics technology that captures transcriptome-wide data at sub-cellular resolution. The computational pipeline covers flow cell barcode preprocessing, transcriptomic alignment via spacemake, image-to-coordinate registration, cell segmentation, and 3D reconstruction.

Skill directory: openst/

When to use:

• Processing raw Open-ST data from BCL files to spatially-resolved h5ad
• Aligning transcriptomic coordinates to H&E tissue images
• Cell segmentation and transcript-to-cell assignment
• 3D reconstruction from serial tissue sections

nf-core Pipelines

nf-core is a community-driven collection of 143+ curated Nextflow pipelines for bioinformatics. Skills cover installation, configuration, and pipeline-specific guides for transcriptomics, spatial omics, epigenomics, and variant calling.

Skill directory: nfcore/

When to use:

• Processing scRNA-seq data (10x, Drop-seq, Smart-seq) with nf-core/scrnaseq
• Processing spatial transcriptomics (Visium, Xenium, MERSCOPE) with nf-core pipelines
• Processing bulk RNA-seq, ATAC-seq, ChIP-seq, CUT&Run, or methylation data
• Variant calling from WGS/WES with nf-core/sarek
• Setting up Nextflow and nf-core on HPC clusters or cloud environments

Using Skills

1. Identify your technology: Find the relevant sub-directory for your spatial/sequencing platform
2. Load skill files: Read the full skill documents for step-by-step guidance
3. Follow the pipeline: Upstream processing is sequential; follow stages in order
4. Proceed to downstream analysis: After generating the count matrix, use the main omics skills for QC, clustering, etc.