scde.posteriors: Calculate joint expression magnitude posteriors across a set...

In hms-dbmi/scde: Single Cell Differential Expression

Calculate joint expression magnitude posteriors across a set of cells

Description

Calculates expression magnitude posteriors for the individual cells, and then uses bootstrap resampling to calculate a joint expression posterior for all the specified cells. Alternatively during batch-effect correction procedure, the joint posterior can be calculated for a random composition of cells of different groups (see batch and composition parameters).

Usage

scde.posteriors(models, counts, prior, n.randomizations = 100, batch = NULL,
  composition = NULL, return.individual.posteriors = FALSE,
  return.individual.posterior.modes = FALSE, ensemble.posterior = FALSE,
  n.cores = 20)

Arguments

models	models models determined by scde.error.models
counts	read count matrix
prior	gene expression prior as determined by scde.expression.prior
n.randomizations	number of bootstrap iterations to perform
batch	a factor describing which batch group each cell (i.e. each row of models matrix) belongs to
composition	a vector describing the batch composition of a group to be sampled
return.individual.posteriors	whether expression posteriors of each cell should be returned
return.individual.posterior.modes	whether modes of expression posteriors of each cell should be returned
ensemble.posterior	Boolean of whether to calculate the ensemble posterior (sum of individual posteriors) instead of a joint (product) posterior. (default: FALSE)
n.cores	number of cores to utilize

Value

default

a posterior probability matrix, with rows corresponding to genes, and columns to expression levels (as defined by prior$x)

return.individual.posterior.modes

a list is returned, with the $jp slot giving the joint posterior matrix, as described above. The $modes slot gives a matrix of individual expression posterior mode values on log scale (rows - genes, columns -cells)

return.individual.posteriors

a list is returned, with the $post slot giving a list of individual posterior matrices, in a form analogous to the joint posterior matrix, but reported on log scale

Examples

data(es.mef.small)
cd <- clean.counts(es.mef.small, min.lib.size=1000, min.reads = 1, min.detected = 1)
data(o.ifm)  # Load precomputed model. Use ?scde.error.models to see how o.ifm was generated
o.prior <- scde.expression.prior(models = o.ifm, counts = cd, length.out = 400, show.plot = FALSE)
# calculate joint posteriors
jp <- scde.posteriors(o.ifm, cd, o.prior, n.cores = 1)

hms-dbmi/scde documentation built on April 19, 2023, 10:21 p.m.