get_normalized: Retrieve Normalized Matrix

In scone: Single Cell Overview of Normalized Expression data

Description

Given a SconeExperiment object created by a call to scone, it will return a matrix of normalized counts (in log scale if log=TRUE).

Usage

get_normalized(x, method, ...)

## S4 method for signature 'SconeExperiment,character'
get_normalized(x, method,
  log = FALSE)

## S4 method for signature 'SconeExperiment,numeric'
get_normalized(x, method,
  log = FALSE)

Arguments

x	a SconeExperiment object containing the results of scone.
method	character or numeric. Either a string identifying the normalization scheme to be retrieved, or a numeric index with the rank of the normalization method to retrieve (according to scone ranking of normalizations).
...	additional arguments for specific methods.
log	logical. Should the data be returned in log-scale

Details

If scone was run with return_norm="in_memory", this function simply retrieves the normalized data from the assays slote of object.

If scone was run with return_norm="hdf5", this function will read the normalized matrix from the specified hdf5 file.

If scone was run with return_norm="no", this function will compute the normalized matrix on the fly.

The numeric method will always return the normalization corresponding to row method of the scone_params slot. This means that if scone was run with eval=TRUE, get_normalized(x, 1) will return the top ranked method. If scone was run with eval=FALSE, get_normalized(x,1) will return the first normalization in the order saved by scone.

Value

A matrix of normalized counts in log-scale.

Methods (by class)

• x = SconeExperiment,method = character: If method is a character, it will return the normalized matrix corresponding to the normalization scheme specified by the character string.The string must be one of the row.names of the slot scone_params.

• x = SconeExperiment,method = numeric: If method is a numeric, it will return the normalized matrix according to the scone ranking.

Examples

set.seed(42)
mat <- matrix(rpois(500, lambda = 5), ncol=10)
colnames(mat) <- paste("X", 1:ncol(mat), sep="")
obj <- SconeExperiment(mat)
res <- scone(obj, scaling=list(none=identity, uq=UQ_FN),
           evaluate=TRUE, k_ruv=0, k_qc=0, 
           eval_kclust=2, bpparam = BiocParallel::SerialParam())
top_norm = get_normalized(res,1)
           

scone documentation built on Nov. 8, 2020, 5:20 p.m.