scde.expression.prior {scde} | R Documentation

## Estimate prior distribution for gene expression magnitudes

### Description

Use existing count data to determine a prior distribution of genes in the dataset

### Usage

    scde.expression.prior(models, counts, length.out = 400, show.plot = FALSE,
      pseudo.count = 1, bw = 0.1, max.quantile = 1 - 0.001,
      max.value = NULL)

### Arguments

`models` | models determined by `scde.error.models`
`counts` | count matrix
`length.out` | number of points (resolution) of the expression magnitude grid (default: 400). Note: larger numbers will linearly increase memory/CPU demands.
`show.plot` | show the estimate posterior
`pseudo.count` | pseudo-count value to use (default 1)
`bw` | smoothing bandwidth to use in estimating the prior (default: 0.1)
`max.quantile` | determine the maximum expression magnitude based on a quantile (default : 0.999)
`max.value` | alternatively, specify the exact maximum expression magnitude value

### Value

a structure describing expression magnitude grid ($x, on log10 scale) and prior ($y)

### 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)

[Package scde version 2.16.0 Index]