normalyzerDE {NormalyzerDE} | R Documentation |
Performs differential expression analysis on a normalization matrix. This command executes a pipeline processing the data and generates an annotated normalization matrix and a report containing p-value histograms for each of the performed comparisons.
normalyzerDE(jobName, comparisons, designPath = NULL, dataPath = NULL, experimentObj = NULL, outputDir = ".", logTrans = FALSE, type = "limma", sampleCol = "sample", condCol = "group", batchCol = NULL, techRepCol = NULL, leastRepCount = 1, quiet = FALSE)
jobName |
Name of job |
comparisons |
Character vector containing target contrasts. If comparing condA with condB, then the vector would be c("condA-condB") |
designPath |
File path to design matrix |
dataPath |
File path to normalized matrix |
experimentObj |
SummarizedExperiment object, can be provided as input as alternative to 'designPath' and 'dataPath' |
outputDir |
Path to output directory |
logTrans |
Log transform the input (needed if providing non-logged input) |
type |
Type of statistical comparison, "limma" or "welch" |
sampleCol |
Design matrix column header for column containing sample IDs |
condCol |
Design matrix column header for column containing sample conditions |
batchCol |
Provide an optional column for inclusion of possible batch variance in the model |
techRepCol |
Design matrix column header for column containing technical replicates |
leastRepCount |
Minimum required replicate count |
quiet |
Omit status messages printed during run |
When executed, it performs the following steps:
1: Read the data and the design matrices into dataframes. 2: Generate an instance of the NormalyzerStatistics class representing the data and their statistical comparisons. 3: Optionally reduce technical replicates in both the data matrix and the design matrix 4: Calculate statistical contrats between supplied groups 5: Generate an annotated version of the original dataframe where columns containing statistical key measures have been added 6: Write the table to file 7: Generate a PDF report displaying p-value histograms for each calculated contrast
None
data_path <- system.file(package="NormalyzerDE", "extdata", "tiny_data.tsv") design_path <- system.file(package="NormalyzerDE", "extdata", "tiny_design.tsv") out_dir <- tempdir() normalyzerDE( jobName="my_jobname", comparisons=c("4-5"), designPath=design_path, dataPath=data_path, outputDir=out_dir, condCol="group")