View source: R/pGS-Multiclass-NONE.R
normulticlassnoallgs | R Documentation |
this function enables the performance assessment of metabolomic data processing for multi-class dataset (without quality control sample and without internal standard) using five criteria, and can scan thousands of workflows and rank them based on their performances.
normulticlassnoallgs(fileName, GS, SAalpha="Y", SAbeta="Y", SAgamma="Y")
fileName |
Allows the user to indicate the NAME of peak table resulted from PrepareInuputFiles() (default = null). |
GS |
Allows the user to indicate the name of the file that contains the spike-in compounds (default = null). The file should be in a .csv format, which provides the concentrations of spike-in compounds. |
SAalpha |
Allows the user to specify whether the input peak table satisfies the study assumption Alpha (SAalpha, all metabolites are assumed to be equally important) (default = “Y”). “Y” denotes that the peak table satisfies the study assumption Alpha (SAalpha). “N” denotes that the peak table does not satisfy the study assumption Alpha (SAalpha). |
SAbeta |
Allows the user to specify whether the input peak table satisfies the study assumption Beta (SAbeta, the level of metabolite abundance is constant among all samples) (default = “Y”). “Y” denotes that the peak table satisfies the study assumption Beta (SAbeta). “N” denotes that the peak table does not satisfy the study assumption Beta (SAbeta). |
SAgamma |
Allows the user to specify whether the input table satisfies study assumption Gamma (SAγ, the intensities of most metabolites are not changed under the studied conditions) (default = “Y”). “Y” denotes that the peak table satisfies the study assumption Gamma (SAγ). “N” denotes that the peak table does not satisfy the study assumption Gamma (SAγ). |
library(NOREVA)
multi_non_data <- PrepareInuputFiles(dataformat = 1,
rawdata = "Multiclass_without_QCSIS.csv")
normulticlassnoallgs(fileName = multi_non_data,
GS = "Multiclass_without_QCSIS_GoldenStandard.csv", SAalpha="Y", SAbeta="Y", SAgamma="N")
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