DEUsingNBID: Differential expression analysis using NBID on a data matrix

In chenlab-sj/nbid: Differential expression analysis using negative binomial with independent dispersions (NBID)

Description

Differential expression analysis using NBID on a data matrix

Usage

DEUsingNBID(data, groups, covariates = NULL, countPerCell = NULL,
  sizeFactor = NULL, singleDispersion = F, dispMethod = "poisson-ML",
  ncore = 1)

Arguments

data	the gene-cell matrix
groups	the group vector
covariates	the covariates
countPerCell	the total UMI per cell
sizeFactor	the normalization factor, the effective count used will be the countPerCell * sizeFactor. The size factor from package scran needs to be divided by countPerCell first, i.e., the size factor from scran is used as the effective count directly.
singleDispersion	whether to use one single dispersion for all cells. All groups will share this single dispersion parameter, i.e., no independent dispersions are used
dispMethod	the method to estimate dispersions
ncore	the number of cores to use for parallel running This function invokes NBID for each row of the data matrix.

Value

a matrix of columns as follows: pvalue: p value for each gene LR: likelihood ratio test statistic beta: the coefficient dispersionGroup1, dispersionGroup2: estimated dispersions log2FC: log2 fold change

Examples

## Not run: 
data(smallData)
result = DEUsingNBID(smallData$count, smallData$groupLabel)
head(result)

## End(Not run)

chenlab-sj/nbid documentation built on Nov. 4, 2019, 8:50 a.m.