seurat_pipeline: Run standardized 'Seurat' pipeline

In neurogenomics/scNLP: NLP for Single-cell Omics.

Run standardized Seurat pipeline

Description

Run Seurat pipeline on Seurat object or raw counts and meta.data.
Automatically performs

FindVariableFeatures

Variable feature selection

NormalizeData

Data normalization

RunPCA

PCA

RunUMAP

UMAP

FindNeighbors

K-nearest neighbors

FindClusters

Clustering

Usage

seurat_pipeline(...)

Arguments

...

Arguments passed on to scKirby::process_seurat obj A single-cell object supported by scKirby. See converters for a table of all supported conversions. meta.data Additional cell-level metadata to add to the Seurat object. Should be a data.frame where the rows are cell names and the columns are additional metadata fields. Row names in the metadata need to match the column names of the counts matrix. nfeatures Number of features to select as top variable features; only used when selection.method is set to 'dispersion' or 'vst' vars.to.regress Variables to regress out (previously latent.vars in RegressOut). For example, nUMI, or percent.mito. dims Which dimensions to use as input features, used only if features is NULL add_specificity Add a new assay called "specificity" by deriving specificity scores from the input data. default_assay Default assay to set with DefaultAssay. n.components The dimension of the space to embed into. cluster_reduction Recompute neighbors graph based on UMAP to get clusters that best reflect UMAP space. For this same reason, only cluster in two dimensions, because this is the view we most often use. That said, this may reduce the generalisability of these clusters/graph. workers Number of workers (threads) to parallelise processes across using future. max_mem Max limit on memory usage, to be passed to environmental variable future.globals.maxSize. seed Random seed to set. verbose Print messages.

Value

A preprocessed Seurat object.

Examples

X <- scNLP::pseudo_sce@assays@data$raw@seed[,seq_len(100)]
obj <- seurat_pipeline(obj = X)

neurogenomics/scNLP documentation built on Oct. 8, 2024, 5:30 p.m.