scde (version 2.0.1)

scde.expression.difference: Test for expression differences between two sets of cells

Description

Use the individual cell error models to test for differential expression between two groups of cells.

Usage

scde.expression.difference(models, counts, prior, groups = NULL,
  batch = NULL, n.randomizations = 150, n.cores = 10,
  batch.models = models, return.posteriors = FALSE, verbose = 0)

Arguments

models

models determined by scde.error.models

counts

read count matrix

prior

gene expression prior as determined by scde.expression.prior

groups

a factor determining the two groups of cells being compared. The factor entries should correspond to the rows of the model matrix. The factor should have two levels. NAs are allowed (cells will be omitted from comparison).

batch

a factor (corresponding to rows of the model matrix) specifying batch assignment of each cell, to perform batch correction

n.randomizations

number of bootstrap randomizations to be performed

n.cores

number of cores to utilize

batch.models

(optional) separate models for the batch data (if generated using batch-specific group argument). Normally the same models are used.

return.posteriors

whether joint posterior matrices should be returned

verbose

integer verbose level (1 for verbose)

Value

• default{ a data frame with the following fields:
  • lb, mle, ub
  {lower bound, maximum likelihood estimate, and upper bound of the 95
• ce
• { conservative estimate of expression-fold change (equals to the min(abs(c(lb, ub))), or 0 if the CI crosses the 0}
• Z
• { uncorrected Z-score of expression difference}
• cZ
• {expression difference Z-score corrected for multiple hypothesis testing using Holm procedure} } If batch correction has been performed (batch has been supplied), analogous data frames are returned in slots $batch.adjusted for batch-corrected results, and $batch.effect for the differences explained by batch effects alone. }

subsection

return.posteriors = TRUE

code

joint.posteriors

Examples

data(es.mef.small)
cd <- clean.counts(es.mef.small, min.lib.size=1000, min.reads = 1, min.detected = 1)
sg <- factor(gsub("(MEF|ESC).*", "\\1", colnames(cd)), levels = c("ESC", "MEF"))
names(sg) <- colnames(cd)
o.ifm <- scde.error.models(counts = cd, groups = sg, n.cores = 10, threshold.segmentation = TRUE)
o.prior <- scde.expression.prior(models = o.ifm, counts = cd, length.out = 400, show.plot = FALSE)
# make sure groups corresponds to the models (o.ifm)
groups <- factor(gsub("(MEF|ESC).*", "\\1", rownames(o.ifm)), levels = c("ESC", "MEF"))
names(groups) <- row.names(o.ifm)
ediff <- scde.expression.difference(o.ifm, cd, o.prior, groups = groups, n.randomizations = 100, n.cores = n.cores, verbose = 1)