normalyzer: NormalyzerDE pipeline entry point

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

NormalyzerDE pipeline entry point

Description

This function is the main execution point for the normalization part of the NormalyzerDE analysis pipeline. When executed it performs the following steps:

Usage

normalyzer(
  jobName,
  designPath = NULL,
  dataPath = NULL,
  experimentObj = NULL,
  outputDir = ".",
  forceAllMethods = FALSE,
  omitLowAbundSamples = FALSE,
  sampleAbundThres = 5,
  tinyRunThres = 50,
  requireReplicates = TRUE,
  normalizeRetentionTime = TRUE,
  plotRows = 3,
  plotCols = 4,
  zeroToNA = FALSE,
  sampleColName = "sample",
  groupColName = "group",
  inputFormat = "default",
  skipAnalysis = FALSE,
  quiet = FALSE,
  noLogTransform = FALSE,
  writeReportAsPngs = FALSE,
  rtStepSizeMinutes = 1,
  rtWindowMinCount = 100,
  rtWindowShifts = 1,
  rtWindowMergeMethod = "mean"
)

Arguments

jobName	Give the current run a name.
designPath	Path to file containing design matrix.
dataPath	Specify an output directory for generated files. Defaults to current working directory.
experimentObj	SummarizedExperiment object, can be provided as input as alternative to 'designPath' and 'dataPath'
outputDir	Directory where results folder is created.
forceAllMethods	Debugging function. Run all normalizations even if they aren't in the recommended range of number of values
omitLowAbundSamples	Automatically remove samples with fewer non-NA values compared to threshold given by sampleAbundThres. Will otherwise stop with error message if such sample is encountered.
sampleAbundThres	Threshold for omitting low-abundant samples. Is by default set to 15.
tinyRunThres	If total number of features is less than this, a limited run is performed.
requireReplicates	Require multiple samples per condition to pass input validation.
normalizeRetentionTime	Perform normalizations over retention time.
plotRows	Number of plot-rows in output documentation.
plotCols	Number of plot-columns in output documentation.
zeroToNA	Convert zero values to NA.
sampleColName	Column name in design matrix containing sample IDs.
groupColName	Column name in design matrix containing condition IDs.
inputFormat	Type of input format.
skipAnalysis	Only perform normalization steps.
quiet	Omit status messages printed during run.
noLogTransform	Don't log-transform the input.
writeReportAsPngs	Output the evaluation report as PNG files instead of a single PDF
rtStepSizeMinutes	Retention time normalization window size.
rtWindowMinCount	Minimum number of datapoints in each retention-time segment.
rtWindowShifts	Number of layered retention time normalized windows.
rtWindowMergeMethod	Merge approach for layered retention time windows.

Details

1: Loads the data matrix containing expression values and optional annotations, as well as the design matrix containing the experimental setup 2: Performs input data verification to validate that the data is in correct format. This step captures many common formatting errors. It returns an instance of the NormalyzerDataset class representing the unprocessed data. 3: Calculate a range of normalizations for the dataset. The result is provided as a NormalyzerResults object containing the resulting data matrices from each normalization. 4: Analyze the normalizations and generate performance measures for each of the normalized datasets. This result is provided as a NormalyzerEvaluationResults object. 5: Output the matrices containing the normalized datasets to files. 6: Generate visualizations overviewing the performance measures and write them to a PDF report.

Value

None

Examples

## Not run: 
data_path <- system.file(package="NormalyzerDE", "extdata", "tiny_data.tsv")
design_path <- system.file(package="NormalyzerDE", "extdata", "tiny_design.tsv")
out_dir <- tempdir()
normalyzer(
    jobName="my_jobname", 
    designPath=design_path, 
    dataPath=data_path, 
    outputDir=out_dir)
normalyzer(
    "my_jobname", 
    designMatrix="design.tsv", 
    "data.tsv", 
    outputDir="path/to/output", 
    normalizeRetentionTime=TRUE, 
    retentionTimeWindow=2)
normalyzer(
    "my_jobname", 
    designMatrix="design.tsv", 
    "data.tsv", 
    outputDir="path/to/output", 
    inputFormat="maxquantprot")

## End(Not run)

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