scReplicate: Create replicate matrix for scMerge algorithm
In SydneyBioX/scMerge: scMerge: Merging multiple batches of scRNA-seq data

scReplicate

R Documentation

Create replicate matrix for scMerge algorithm

Description

Create replicate matrix for scMerge algorithm using un-/semi-/supervised approaches.

Usage

scReplicate(
  sce_combine,
  batch = NULL,
  kmeansK = NULL,
  exprs = "logcounts",
  hvg_exprs = "counts",
  marker = NULL,
  marker_list = NULL,
  replicate_prop = 1,
  cell_type = NULL,
  cell_type_match = FALSE,
  cell_type_inc = NULL,
  dist = "cor",
  WV = NULL,
  WV_marker = NULL,
  BPPARAM = SerialParam(),
  return_all = FALSE,
  BSPARAM = ExactParam(),
  plot_igraph = TRUE,
  verbose = FALSE
)

Arguments

`sce_combine`	A `SingleCellExperiment` object contains the batch-combined matrix with batch info in colData
`batch`	A vector indicates the batch information for each cell in the batch-combined matrix.
`kmeansK`	A vector indicates the kmeans's K for each batch, length of kmeansK needs to be the same as the number of batch.
`exprs`	A string indicates the assay that are used for batch correction, default is logcounts
`hvg_exprs`	A string indicates the assay that are used for highly variable genes identification, default is counts
`marker`	A vector of markers, which will be used in calculation of mutual nearest cluster. If no markers input, highly variable genes will be used instead
`marker_list`	A list of markers for each batch, which will be used in calculation of mutual nearest cluster.
`replicate_prop`	A number indicating the ratio of cells that are included in pseudo-replicates, ranges from 0 to 1. Default to 1.
`cell_type`	A vector indicates the cell type information for each cell in the batch-combined matrix. If it is `NULL`, pseudo-replicate procedure will be run to identify cell type.
`cell_type_match`	Whether find mutual nearest cluster using cell type information
`cell_type_inc`	A vector indicates the indices of the cells that will be used to supervise the pseudo-replicate procedure
`dist`	The distance metrics that are used in the calculation of the mutual nearest cluster, default is Pearson correlation.
`WV`	A vector indicates the wanted variation factor other than cell type info, such as cell stages.
`WV_marker`	A vector indicates the markers of the wanted variation.
`BPPARAM`	A `BiocParallelParam` class object from the `BiocParallel` package is used. Default is SerialParam().
`return_all`	If `FALSE`, only return the replicate matrix.
`BSPARAM`	A `BiocSingularParam` class object from the `BiocSingular` package is used. Default is ExactParam().
`plot_igraph`	If `TRUE`, then during the un/semi-supervised scMErge, igraph plot will be displayed
`verbose`	If `TRUE`, then all intermediate steps will be shown. Default to `FALSE`.

Value

If return_all is FALSE, return a replicate matrix. If return_sce is TRUE, return the followings

`repMat`	replicate matrix
`mnc`	mutual nearest cluster
`replicate vector`	replicate vector
`HVG`	highly variable genes used in scReplicate

A cell-replicates mapping matrix. Each row correspond to a cell from the input expression matrix, and each column correspond to a cell-cluster/cell-type. An element of the mapping matrix is 1 if the scReplicate algorithm determines that this cell should belong to that cell cluster and 0 otherwise.

Author(s)

Yingxin Lin, Kevin Wang

Examples

## Loading example data
set.seed(1)
data('example_sce', package = 'scMerge')
scRep_result = scReplicate(
  sce_combine = example_sce,
  batch = example_sce$batch,
  kmeansK = c(3,3))

SydneyBioX/scMerge documentation built on April 14, 2024, 3:22 a.m.