integrateWithScRNASeq: Integration with single-cell RNA sequencing data

In beyondpie/pureRUtils: Commonly used R functions with pure R codes

Integration with single-cell RNA sequencing data

Description

Integration with single-cell RNA sequencing data

Usage

integrateWithScRNASeq(
  snapSeurat,
  rnaSeurat,
  eigDims = NULL,
  snapAssay = "GeneScore",
  preprocessSnap = TRUE,
  preprocessRNA = TRUE,
  rnaTypeColnm = "ClusterName",
  reso = 0.5,
  reduction = "cca",
  nVariableFeature = 3000
)

Arguments

snapSeurat	Seurat object transformed from snap object Assume meta.data has no column named ClusterName
rnaSeurat	Seurat obejct, reference scRNA sequencing ddta Assume meta.data has a column for rnaType
eigDims	dims used for snapSeurat pca, if NULL (default), use all the dims.
snapAssay	characters, snapSeurat assay name, default "GeneScore"
preprocessSnap	bool, if need to normalize and scale snap, default TRUE
preprocessRNA	bool, if need to normalize, scale rnaSeurat, default TRUE
rnaTypeColnm	characters, colname for rnaSeurat's type, default "ClusterName"
reso	numeric, clustering resolution parameter, default 0.5
reduction	characters, method used in FindTransferAnchors,
nVariableFeature	integer, default is 3000 default "cca".

Value

Seurat object, merge snapSeurat and rnaSeurat Add predictId and predictMaxScore from rnaSeurat for snapSeurat on metaData, Add imputed gene expression from rnaSeurat for snapSeurat with Assay: "RNA" Add tech as either ATAC or RNA in the meta.data Clustering on the merged Seurat object as Co-Embedding Seurat object

beyondpie/pureRUtils documentation built on Jan. 10, 2023, 3:22 a.m.