runBBKNN: Integrate scRNA-seq data using batch-balanced KNN (BBKNN)

In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.

Integrate scRNA-seq data using batch-balanced KNN (BBKNN)

Description

This is a wrapper for BBKNN (https://github.com/Teichlab/bbknn). BBKNN is a fast and intuitive batch effect removal tool. It generates a BBKNN cell x cell similarity graph that can be used for clustering and UMAP embedding.

Usage

runBBKNN(
  object,
  batch,
  reduction = "pca",
  assay = DefaultAssay(object),
  do.umap = T,
  verbose = T
)

Arguments

object	Seurat object
batch	name of meta data field specifying batch groupings.
reduction	reduction used for batch correction. Default is "pca".
assay	assay name. Default is DefaultAssay(object).
do.umap	compute UMAP. Default is T.
verbose	print progress. Default is T.

Value

Seurat object with bbKNN-corrected UMAP stored in "b" reduction slot (if do.umap = T).

Author(s)

Nicholas Mikolajewicz

Examples

 object <- runBBKNN(object, batch = "sample")

NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.