Description Usage Arguments Value Slots
View source: R/NormalyzerDataset.R
Takes a job name, a data matrix, a design matrix as well as specification of the group and sample columns in the design matrix. Provides the basic representation of a dataset in the NormalyzerDE normalization part.
1 2 3 4 5 | NormalyzerDataset(jobName, designMatrix, rawData, annotationData,
sampleNameCol, groupNameCol, tinyRunThres = 50, quiet = FALSE)
NormalyzerDataset(jobName, designMatrix, rawData, annotationData,
sampleNameCol, groupNameCol, tinyRunThres = 50, quiet = FALSE)
|
jobName |
Name of the NormalyzerDE processing run |
designMatrix |
Matrix containing sample conditions |
rawData |
Matrix containing raw input data |
annotationData |
Matrix containing annotation information for each input feature. Is expected to contain the same number of rows as the data but can contain any number of features |
sampleNameCol |
Name of column in design matrix containing sample information |
groupNameCol |
Name of column in design matrix containing condition information |
tinyRunThres |
If fewer features than this is present in the input a limited run will be performed to avoid some steps requiring a more extensive number of features. |
quiet |
If set to TRUE no information messages will be printed |
nds Generated NormalyzerDataset instance
jobNameName of the job represented by the dataset.
rawDataMatrix with raw values.
sampleNameColName column for sample.
groupNameColName column for groups.
designMatrixData frame containing design.
sampleNamesVector containing sample names.
filterrawdataReduced raw data matrix where low abundance rows are removed
sampleReplicateGroupsVector with sample replicate information
samplesGroupsWithReplicatesVector with replicated sample replicate information
annotationValuesAnnotation part of original dataframe.
retentionTimesVector of retention time values.
singleReplicateRunConditional whether run is single replicate.
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