sce_norm_hvg_fn: Find highly variable genes (HVGs).

In bioinfocz/scdrake: A pipeline for droplet-based single-cell RNA-seq data secondary analysis implemented in the drake Make-like toolkit for R language

Find highly variable genes (HVGs).

Description

Prior to HVG selection, cell cycle-related gene can be removed. For more details see the HVG selection section in ⁠02_norm_clustering.yaml⁠ config.

Usage

sce_norm_hvg_fn(
  sce_norm,
  hvg_selection_value,
  hvg_metric = c("gene_var", "gene_cv2", "sctransform"),
  hvg_selection = c("top", "significance", "threshold"),
  hvg_rm_cc_genes = FALSE,
  hvg_cc_genes_var_expl_threshold = 5,
  spatial = FALSE,
  BSPARAM = BiocSingular::IrlbaParam(),
  BPPARAM = BiocParallel::SerialParam()
)

Arguments

sce_norm	(input target) A SingleCellExperiment object.
hvg_selection_value, hvg_metric, hvg_selection	Passed to get_top_hvgs() - see its help page.
hvg_rm_cc_genes	A logical scalar: if TRUE, remove cell cycle-related genes exceeding the hvg_cc_genes_var_expl_threshold prior to HVG selection.
hvg_cc_genes_var_expl_threshold	A numeric scalar: threshold for variance explained. Genes exceeding this threshold will be marked as CC-related.
spatial	A logical scalar: if TRUE, add spatially variable genes extension
BSPARAM	A BiocSingular::BiocSingularParam object.
BPPARAM	A BiocParallel::BiocParallelParam object.

Value

A modified sce_norm object with added HVG data in metadata(). Output target: sce_norm_hvg

The following items of metadata(sce_norm) are added or modified:

• hvg_metric, hvg_selection, hvg_selection_value, hvg_rm_cc_genes, hvg_cc_genes_var_expl_threshold: values passed to the function.

• hvg_metric_fit: either DataFrame returned from scran::modelGeneVar() or scran::modelGeneCV2(), or feature.attributes dataframe returned from Seurat::SCTransform().

• Values added by sce_remove_cc_genes().

• hvg_ids: a character vector of HVG ENSEMBL IDs.

bioinfocz/scdrake documentation built on Sept. 19, 2024, 4:43 p.m.