fitMuDisp: Coordinate mean and dispersion parameter co-estimation step

In YosefLab/LineagePulse: Differential expression analysis and model fitting for single-cell RNA-seq data

Description

Auxillary function that calls the estimation functions for the different mean and dispersion models according to their needs. Note that one function has to be coded for each combination of mean and dispersion models.

Usage

fitMuDisp(matCountsProc, vecNormConst, lsMuModel, lsDispModel, lsDropModel,
  matWeights)

Arguments

matCountsProc	(matrix genes x cells) Observed read counts, not observed are NA.
vecNormConst	(numeric vector number of cells) Model scaling factors, one per cell.
lsMuModel	(list) Object containing description of gene-wise mean parameter models.
lsDispModel	(list) Object containing description of gene-wise dispersion parameter models.
lsDropModel	(list) Object containing description of cell-wise drop-out parameter models.
matWeights	(numeric matrix cells x mixtures) [Default NULL] Assignments of cells to mixtures (for strMuModel="MM").

Value

list

• matMuModel (numeric matrix genes x mu model parameters) Contains the mean model parameters according to the used model.

• lsmatBatchModelMu (list) Fit of batch correction models for mean parameter.

• matDispModel (numeric matrix genes x disp model parameters) Contains the dispersion model parameters according to the used model.

• lsmatBatchModelDisp (list) Fit of batch correction models for dispersion parameter.

• vecConvergence (numeric vector number of genes) Convergence status of optim for each gene.

• vecLL (numeric vector number of genes) Likelihood of model fit.

Author(s)

David Sebastian Fischer

See Also

Called by fitModel. Calls fitting wrappers: fitImpulseZINB, fitContinuousZINB.

YosefLab/LineagePulse documentation built on May 6, 2019, 2:19 p.m.