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
jobName
Name of the job represented by the dataset.
rawData
Matrix with raw values.
sampleNameCol
Name column for sample.
groupNameCol
Name column for groups.
designMatrix
Data frame containing design.
sampleNames
Vector containing sample names.
filterrawdata
Reduced raw data matrix where low abundance rows are removed
sampleReplicateGroups
Vector with sample replicate information
samplesGroupsWithReplicates
Vector with replicated sample replicate information
annotationValues
Annotation part of original dataframe.
retentionTimes
Vector of retention time values.
singleReplicateRun
Conditional whether run is single replicate.
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