scReplicate {scMerge}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, parallelParam = SerialParam(),
  return_all = FALSE, fast_svd, 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 indicates the ratio of cells that are included in pseudo-replicates, ranges from 0 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.

parallelParam

The BiocParallelParam class from the BiocParallel package is used. Default is SerialParam().

return_all

If FALSE, only return the replicate matrix.

fast_svd

If TRUE, fast algorithms will be used for singular value decomposition calculation via the irlba and rsvd packages. We recommend using this option when the number of cells is large (e.g. more than 1000 cells).

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),
  fast_svd = FALSE)


[Package scMerge version 1.0.0 Index]