Run spot-level quality control

Calculate common spot-level QC metrics for spatial transcriptomics data and label failed spots without running single-cell-specific checks such as doublet calling or ambient RNA decontamination.

Usage

RunSpotQC(
  srt,
  assay = NULL,
  return_filtered = FALSE,
  qc_metrics = c("outlier", "umi", "gene", "mito"),
  outlier_threshold = c("log10_nCount:lower:3", "log10_nFeature:lower:3",
    "spot_featurecount_dist:lower:3"),
  outlier_n = 1,
  UMI_threshold = 500,
  gene_threshold = 200,
  mito_threshold = 20,
  mito_pattern = c("MT-", "Mt-", "mt-"),
  mito_gene = NULL,
  verbose = TRUE,
  seed = 11
)

Arguments

srt

A Seurat object.

assay

Assay to use. NULL uses the default assay.

return_filtered

Whether to return a spot-filtered Seurat object.

qc_metrics

QC metrics to apply. Available metrics are "outlier", "umi", "gene", and "mito".

outlier_threshold

Character vector specifying outlier thresholds as "metric:direction:nmads". Available default metrics are "log10_nCount", "log10_nFeature", and "spot_featurecount_dist".

outlier_n

Minimum number of outlier metrics required to fail a spot.

UMI_threshold

Minimum UMI count required to pass "umi" QC.

gene_threshold

Minimum detected gene count required to pass "gene" QC.

mito_threshold

Maximum mitochondrial percentage allowed by "mito" QC.

mito_pattern

Regex patterns used to identify mitochondrial genes.

mito_gene

Optional explicit mitochondrial gene vector. When provided, mito_pattern is ignored.

verbose

Whether to print the message. Default is TRUE.

seed

Random seed for reproducibility.

Value

A Seurat object with spot QC metadata columns.

Examples

data(visium_human_pancreas_sub)
spatial <- RunSpotQC(
  visium_human_pancreas_sub,
  assay = "Spatial"
)
#> ◌ [2026-08-30 05:42:36] Running spot-level quality control
#> ✔ [2026-08-30 05:42:36] 1907 spots passed QC and 79 spots failed QC
SpatialSpotPlot(spatial, group.by = "SpotQC")