newBASiCS_Data: Creates a SingleCellExperiment object from a matrix of...
In catavallejos/BASiCS: Bayesian Analysis of Single-Cell Sequencing data

newBASiCS_Data

R Documentation

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

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

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

`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).

An object of class SingleCellExperiment.

Catalina A. Vallejos cnvallej@uc.cl