newBASiCS_Data: Creates a SingleCellExperiment object from a matrix of...

In BASiCS: Bayesian Analysis of Single-Cell Sequencing data

Description

newBASiCS_Data creates a SingleCellExperiment object from a matrix of expression counts and experimental information about spike-in genes.

Usage

newBASiCS_Data(
  Counts,
  Tech = rep(FALSE, nrow(Counts)),
  SpikeInfo = NULL,
  BatchInfo = NULL,
  SpikeType = "ERCC"
)

Arguments

Counts	Matrix of dimensions q times n whose elements contain the expression counts to be analyses (including biological and technical spike-in genes). Gene names must be stored as rownames(Counts).
Tech	Logical vector of length q. If Tech = FALSE the gene is biological; otherwise the gene is spike-in. Defaul value: Tech = rep(FALSE, nrow(Counts)).
SpikeInfo	data.frame whose first and second columns contain the gene names assigned to the spike-in genes (they must match the ones in rownames(Counts)) and the associated input number of molecules, respectively. If SpikeInfo = NULL, only the horizontal integration implementation (no spikes) can be run. Default value: SpikeInfo = NULL.
BatchInfo	Vector of length n whose elements indicate batch information. Not required if a single batch is present on the data. Default value: BatchInfo = NULL.
SpikeType	Character to indicate what type of spike-ins are in use. Default value: SpikeType = "ERCC" (parameter is no longer used).

Value

An object of class SingleCellExperiment.

Author(s)

Catalina A. Vallejos [e-mail]

Nils Eling [e-mail]

See Also

SingleCellExperiment

BASiCS documentation built on April 16, 2021, 6 p.m.