BASiCS_DenoisedCounts: Calculates denoised expression expression counts

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/BASiCS_DenoisedCounts.R

Description

Calculates denoised expression counts by removing cell-specific technical variation. The latter includes global-scaling normalisation and therefore no further normalisation is required.

Usage

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BASiCS_DenoisedCounts(Data, Chain, WithSpikes = TRUE)

Arguments

Data

An object of class SingleCellExperiment

Chain

An object of class BASiCS_Chain

WithSpikes

A logical scalar specifying whether denoised spike-in genes should be generated as part of the output value. This only applies when the BASiCS_Chain object was generated with the setting WithSpikes=TRUE.

Details

See vignette browseVignettes("BASiCS")

Value

A matrix of denoised expression counts. In line with global scaling normalisation strategies, these are defined as X_{ij}/(φ_j ν_j) for biological genes and X_{ij}/(ν_j) for spike-in genes. For this calculation φ_j ν_j are estimated by their corresponding posterior medians. If spike-ins are not used, φ_j is set equal to 1.

Author(s)

Catalina A. Vallejos cnvallej@uc.cl

Nils Eling eling@ebi.ac.uk

See Also

BASiCS_Chain

Examples

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Data <- makeExampleBASiCS_Data(WithSpikes = TRUE)
## The N and Burn parameters used here are optimised for speed
## and should not be used in regular use.
## For more useful parameters,
## see the vignette (\code{browseVignettes("BASiCS")})
Chain <- BASiCS_MCMC(Data, N = 1000, Thin = 10, Burn = 500,
                     Regression = FALSE, PrintProgress = FALSE)

DC <- BASiCS_DenoisedCounts(Data, Chain)

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