getVerifiedNormalyzerObject: Verify that input data is in correct format, and if so,...

In ComputationalProteomics/NormalyzerDE: Evaluation of normalization methods and calculation of differential expression analysis statistics

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)

ComputationalProteomics/NormalyzerDE documentation built on Sept. 18, 2023, 9:15 p.m.