initDropModel: Initialise drop-out model container object

Description Usage Arguments Value Author(s) See Also

View source: R/srcLineagePulse_initialiseDropModel.R

Description

Either use supplied fits from previous fitting or initialise from count data.

Usage

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initDropModel(matCounts, matPiConstPredictors, lsDropModel, strDropModel,
  strDropFitGroup, MAXIT_BFGS_Pi, RELTOL_BFGS_Pi)

Arguments

matCounts

(matrix genes x cells) Count data of all cells, unobserved entries are NA.

matPiConstPredictors

(numeric matrix genes x number of constant gene-wise drop-out predictors) [Default NULL] Predictors for logistic drop-out fit other than offset and mean parameter (i.e. parameters which are constant for all observations in a gene and externally supplied.) Is null if no constant predictors are supplied.

lsDropModel

(list) [Default NULL]

strDropModel

(str) "logistic_ofMu", "logistic", "none" [Default "logistic_ofMu"] Definition of drop-out model. "logistic_ofMu" - include the fitted mean in the linear model of the drop-out rate and use offset and matPiConstPredictors. "logistic" - only use offset and matPiConstPredictors. "none" - negative binomial noise model without zero-inflation.

strDropFitGroup

(str) "PerCell", "AllCells" [Defaul "PerCell"] Definition of groups on cells on which separate drop-out model parameterisations are fit. "PerCell" - one parametersiation (fit) per cell "ForAllCells" - one parametersiation (fit) for all cells

MAXIT_BFGS_Pi

(sca) Maximum number of iterations in BFGS estimation of dropout models. This is a control parameter to optim().

RELTOL_BFGS_Pi

(sca) Relative tolerance of BFGS estimation of dropout models. This is a control parameter to optim().

Value

lsDropModel (list) Initialisation of drop-out model object.

Author(s)

David Sebastian Fischer

See Also

Called by fitModel.


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