ZINBoptim: #This function optimises the likelihood function for a gene,...

In sam-uofl/SwarnSeq: Detection of Differentially Expressed Genes from Single Cell RNA-seq Data

Description

#This function optimises the likelihood function for a gene, supplies starting values for EM algorithm.

Usage

ZINBoptim(Count, group, CellCluster, CellAuxil, muoffset, phioffset, weights)

Arguments

Count	Vector of count expression data of a gene over the cells.
group	Vector which specifies the membership of the cells, i.e. two groups to be compared, corresponding to the cells in the count.
CellCluster	Vector which specifies the cluster memberships of the cells, i.e. each entry represents memberships of the entries of the count.
CellAuxil	Vector of cell level auxiliary information, corresponding to the entries in the counts, default is NULL.
muoffset	Offset parameter for mean (mu) parameter, default is NULL.
phioffset	Offset parameter for zero inflation (phi) parameter, default is NULL.
weights	Observation wise weights for the cells, default is unity vector.

Value

A list containing the estimates of the parameters of a gene.

Author(s)

Samarendra Das

sam-uofl/SwarnSeq documentation built on Sept. 6, 2020, 12:09 a.m.