estimateHyperPar {BitSeq} | R Documentation

## Estimate hyperparameters for DE model using expression samples and joint mean expression

### Description

Estimate hyperparameters for the Differential Expression model using expression samples and produced smoothed values of the hyperparameters depending on joint mean expression.

### Usage

    estimateHyperPar( outFile, conditions=NULL, paramsInFile=NULL,
          meanFile=NULL, force=TRUE, exThreshold=NULL, lambda0=NULL,
          paramsAllFile=NULL, smoothOnly=NULL, lowess_f=NULL, lowess_steps=NULL,
          verbose=NULL, veryVerbose=NULL, norm=NULL, seed=NULL, pretend=FALSE )

### Arguments

`outFile` | Name of the output file.
`conditions` | `List` of vectors, each vector containing names of files containing the expression samples from a replicate (Can be both technical and biological replicates. However, in order to get good results biological replicates for each condition are essential).
`paramsInFile` | File produced by previous run of the function using `paramsAllFile` flag.
`meanFile` | Name of the file containing joint mean and variance.
`exThreshold` | Threshold of lowest expression for which the estimation is done.
`paramsAllFile` | Name of the file to which to store all parameter values generated prior to lowess smoothing(good for later, more careful re-smoothing.)
`smoothOnly` | Input file contains previously sampled hyperparameters which should smoothed only.
`verbose` | Verbose output.

Advanced options:

`force` | Force smoothing hyperparameters, otherwise program might not produce parameters file at the end.
`lambda0` | Model parameter lambda0.
`lowess_f` | Parameter F for lowess smoothing specifying amount of smoothing.
`lowess_steps` | Parameter Nsteps for lowess smoothing specifying number of iterations.
`veryVerbose` | More verbose output.
`norm` | Vector of (multiplicative) normalization constants for library size normalization of expression samples. Number of constants has to match the number of expression samples files.
`seed` | Sets the initial random seed for repeatable experiments.
`pretend` | Do not execute, only print out command line calls for the C++ version of the program.

### Value

`.par` | file containing the smoothed hyperparameters
`.ALLpar` | file containing all hyperparameter samples prior to smoothing - optional

### Author(s)

Peter Glaus

### See Also

`estimateDE`

### Examples

    ## Not run:
    cond1Files = c("data-c0b0.rpkm","data-c0b1.rpkm")
    cond2Files = c("data-c1b0.rpkm","data-c1b1.rpkm")
    estimateHyperPar( conditions=list(cond1Files, cond2Files), outFile="data.par",
          meanFile="data.means", verbose=TRUE)

    estimateHyperPar( conditions=list(cond1Files, cond2Files), outFile="data.par",
          meanFile="data.means", paramsFile="data.ALLpar", force=FALSE)
    estimateHyperPar( outFile="data.par", paramsInFile="data.ALLpar", smoothOnly=TRUE )

    ## End(Not run)

[Package BitSeq version 1.24.0 Index]