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preprocessing

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Quality control, ambient-RNA handling, normalization, and feature selection for single-cell RNA-seq using Scanpy (Python) and Seurat (R). Use when filtering low-quality cells with MAD-adaptive thresholds, setting tissue-aware mito cutoffs, removing ambient RNA (SoupX/CellBender/DecontX), choosing a normalization (shifted-log vs scran vs sctransform vs Pearson residuals), selecting highly variable genes, or deciding whether to scale and regress out covariates.

When to use

• filtering low-quality cells with MAD-adaptive thresholds
• setting tissue-aware mito cutoffs
• removing ambient RNA
• choosing a normalization method
• selecting highly variable genes
• deciding whether to scale and regress out covariates
• empty-droplet calling
• doublet detection

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