scde (version 2.0.1)

scde.fit.models.to.reference: Fit scde models relative to provided set of expression magnitudes

Description

If group-average expression magnitudes are available (e.g. from bulk measurement), this method can be used to fit individual cell error models relative to that reference

Usage

scde.fit.models.to.reference(counts, reference, n.cores = 10,
  zero.count.threshold = 1, nrep = 1, save.plots = FALSE,
  plot.filename = "reference.model.fits.pdf", verbose = 0, min.fpm = 1)

Arguments

counts

count matrix

reference

a vector of expression magnitudes (read counts) corresponding to the rows of the count matrix

n.cores

number of cores to use

zero.count.threshold

read count to use as an initial guess for the zero threshold

nrep

number independent of mixture fit iterations to try (default = 1)

save.plots

whether to write out a pdf file showing the model fits

plot.filename

model fit pdf filename

verbose

verbose level

min.fpm

minimum reference fpm of genes that will be used to fit the models (defaults to 1). Note: fpm is calculated from the reference count vector as reference/sum(reference)*1e6

Value

• matrix of scde models

Examples

data(es.mef.small)
cd <- clean.counts(es.mef.small, min.lib.size=1000, min.reads = 1, min.detected = 1)
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)
# calculate joint posteriors across all cells
jp <- scde.posteriors(models = o.ifm, cd, o.prior, n.cores = 10, return.individual.posterior.modes = TRUE, n.randomizations = 100)
# use expected expression magnitude for each gene
av.mag <- as.numeric(jp$jp %*% as.numeric(colnames(jp$jp)))
# translate into counts
av.mag.counts <- as.integer(round(av.mag))
# now, fit alternative models using av.mag as a reference (normally this would correspond to bulk RNA expression magnitude)
ref.models <- scde.fit.models.to.reference(cd, av.mag.counts, n.cores = 1)