calculateProgenitorScore: Calculate progenitor scores for each sample (cell)

Description Usage Arguments Value

View source: R/RSS.r

Description

This function uses the predictive model to estimate a progenitor scores for the input samples, which can be used to determine whether the samples (cells) are progenitors or neurons.

Usage

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calculateProgenitorScore(input, nameMap = NULL, model = NULL,
  forceRetrain = FALSE, returnModel = TRUE, verbose = TRUE, ...)

Arguments

input

The input expression matrix, with rows representing genes and columns representing samples (cells)

nameMap

A matrix/data.frame showing the gene name mappings. It is expected to be of multiple columns, one of which is for gene symbols.

model

The model used for progenitor scores estimation. It is expected to be a list with at least two components: 'gene' for the list of genes to be ranked; 'coefficients' for the model coefficients. When it is NULL, the default model is used.

forceRetrain

When it is TRUE, the model will be rebuilt by only considering genes involved in the input matrix.

returnModel

Whether to return the retrained model for progenitor score estimation.

verbose

Whether to output the progress information.

...

Other arguments passed to the 'retrainProgenitorModel' function.

Value

A list with two components: 'scores' for the estimated progenitor scores; 'model' for the model predicting the scores (NULL when returnModel is FALSE).


maplesword/RefSimSpec documentation built on Nov. 23, 2018, 12:24 a.m.