| name | quality-control |
| description | Compute QC metrics, filter cells, detect doublets for single-cell RNA-seq data. |
| allowed-tools | Read, Bash |
| compatibility | scRNA-seq, snRNA-seq |
Quality Control
When to Use
Before clustering to remove low-quality cells and doublets.
Functions
compute_qc_metrics(adata) -> dict
Computes standard QC metrics:
n_genes: number of detected genes per celltotal_counts: total UMI counts per cellpct_mito: percentage of mitochondrial genespct_ribo: percentage of ribosomal genes
Returns metrics added to adata.obs: n_genes, total_counts, pct_mito, pct_ribo
Mitochondrial genes detected by prefix "MT-" (human) or "mt-" (mouse).
Ribo genes by prefixes "RPS", "RPL" (ribo protein) and "RPSA".
filter_cells(adata, min_genes=200, max_genes=5000, min_counts=500, max_counts=50000, max_mito_pct=20) -> AnnData
Filters cells based on QC thresholds. Returns subsetted AnnData.
- Cells with too few genes = likely empty droplets
- Cells with too many genes = likely doublets
- High mito percentage = dying cells
detect_doublets(adata, expected_cells=None) -> list[int]
Heuristic doublet detection based on gene count outliers.
Cells with n_genes > Q3 + 1.5*IQR flagged as potential doublets.
Returns list of cell indices flagged as doublets.
