getVerifiedNormalyzerObject {NormalyzerDE} | R Documentation

## Verify that input data is in correct format, and if so, return a generated NormalyzerDE data object from that input data

### Description

This function performs a number of checks on the input data and provides informative error messages if the data isn't fulfilling the required format. Checks include verifying that the design matrix matches to the data matrix, that the data matrix contains valid numbers and that samples have enough values for analysis

### Usage

    getVerifiedNormalyzerObject(jobName, summarizedExp, threshold = 15,
      omitSamples = FALSE, requireReplicates = TRUE, quiet = FALSE,
      noLogTransform = FALSE, tinyRunThres = 50)

### Arguments

`jobName` | Name of ongoing run.
`summarizedExp` | Summarized experiment input object
`threshold` | Minimum number of features.
`omitSamples` | Automatically omit invalid samples from analysis.
`requireReplicates` | Require there to be at least to samples per condition
`quiet` | Don't print output messages during processing
`noLogTransform` | Don't log-transform the provided data
`tinyRunThres` | If less features in run, a limited run is performed

### Value

Normalyzer data object representing verified input data.

### Examples

    data(example_summarized_experiment)
    normObj <- getVerifiedNormalyzerObject("job_name", example_summarized_experiment)

[Package NormalyzerDE version 1.2.0 Index]