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.
Examples
if (FALSE) { # \dontrun{
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")
} # }