create_read_numbers {polyester} | R Documentation

## Generate a simulated data set based on known model parameters

### Description

Generate a simulated data set based on known model parameters

### Usage

    create_read_numbers(mu, fit, p0, m = NULL, n = NULL, mod = NULL,
      beta = NULL, seed = NULL)

### Arguments

`mu` | Baseline mean expression for negative binomial model
`fit` | Fitted relationship between log mean and log size
`p0` | A vector of the probabilities a count is zero
`m` | Number of genes/transcripts to simulate (not necessary if mod, beta are specified)
`n` | Number of samples to simulate (not necessary if mod, beta are specified)
`mod` | Model matrix you would like to simulate from without an intercept
`beta` | set of coefficients for the model matrix (must have same number of columns as mod)
`seed` | optional seed to set (for reproducibility)

### Value

counts Data matrix with counts for genes in rows and samples in columns

### Author(s)

Jeff Leek

### Examples

      library(ballgown)
      data(bg)
      countmat = fpkm_to_counts(bg, mean_rps=400000)
      params = get_params(countmat)
      Ntranscripts = 50
      Nsamples = 10
      custom_readmat = create_read_numbers(mu=params$mu, fit=params$fit,
        p0=params$p0, m=Ntranscripts, n=Nsamples, seed=103)

[Package polyester version 1.26.0 Index]