fitMuDispGene: Optim wrapper for gene-wise models other than mixture model.

Description Usage Arguments Details Value Author(s) See Also

View source: R/srcLineagePulse_fitMeanDispersion.R

Description

Given a parameter initialisation, this function performs numerical optimisation using BFGS of the likelihood function given the supplied mean and dispersion model. This is the wrapper that calls optim.

Usage

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fitMuDispGene(vecCounts, vecMuModelGuess, lsvecBatchParamGuessMu,
  lsMuModelGlobal, vecDispGuess, lsvecBatchParamGuessDisp, lsDispModelGlobal,
  matDropoutLinModel, vecPiConstPredictors, lsDropModelGlobal, vecPiParam)

Arguments

vecCounts

(count vector number of cells) Observed read counts, not observed are NA.

vecMuModelGuess

(numeric vector number of mean model parameters) Initialisation for impulse model.

lsvecBatchParamGuessMu

(list) Object containing initialisation for mean parameter batch correction model.

lsMuModelGlobal

(list) Object containing meta-data of gene-wise mean parameter models.

vecDispGuess

(numeric vector number of dispersion model parameters) Initialisation for dispersion model.

lsvecBatchParamGuessDisp

(list) Object containing initialisation for dispersion parameter batch correction model.

lsDispModelGlobal

(list) Object containing meta-data of gene-wise dispersion parameter models.

matDropoutLinModel

(matrix number of cells x number of predictors) Logistic linear model parameters of the dropout rate as a function of the mean and constant gene-wise coefficients.

vecPiConstPredictors

(numeric vector constant gene-wise coefficients) Constant gene-wise coeffiecients, i.e. predictors which are not the offset and not the mean parameter.

lsDropModelGlobal

(list) Object containing meta-data of cell-wise drop-out parameter models.

vecPiParam

(numeric vector number of observations) Pre-evaluated drop-out model if model is not a function on the mean parameter to be fit.

Details

This function performs error handling of the numerical fitting procedure. This function corrects for the likelihood sensitivity bounds used in the cost function.

Value

list

Author(s)

David Sebastian Fischer

See Also

Called once for each gene by fitZINBMuDisp or within wrapper fitZINBImpulse once for each initalisation of each gene. Calls fitting likelihood functions: evalLogLikContinuousZINB_comp.


LineagePulse documentation built on Nov. 8, 2020, 7:01 p.m.