scde.failure.probability: Calculate drop-out probabilities given a set of counts or... In hms-dbmi/scde: Single Cell Differential Expression

Description

Returns estimated drop-out probability for each cell (row of `models` matrix), given either an expression magnitude

Usage

 `1` ```scde.failure.probability(models, magnitudes = NULL, counts = NULL) ```

Arguments

 `models` models determined by `scde.error.models` `magnitudes` a vector (`length(counts) == nrows(models)`) or a matrix (columns correspond to cells) of expression magnitudes, given on a log scale `counts` a vector (`length(counts) == nrows(models)`) or a matrix (columns correspond to cells) of read counts from which the expression magnitude should be estimated

Value

a vector or a matrix of drop-out probabilities

Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```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 probability of observing a drop out at a given set of magnitudes in different cells mags <- c(1.0, 1.5, 2.0) p <- scde.failure.probability(o.ifm, magnitudes = mags) # calculate probability of observing the dropout at a magnitude corresponding to the # number of reads actually observed in each cell self.p <- scde.failure.probability(o.ifm, counts = cd) ```

hms-dbmi/scde documentation built on March 29, 2018, 1:23 p.m.