normulticlassqcall: Multi-class (N>1) Metabolomic Study with dataset with Quality...

In idrblab/NOREVA: R Package for Systematic Optimization of Metabolomic Data Processing

Multi-class (N>1) Metabolomic Study with dataset with Quality Control Samples (QCSs)

Description

This function enables the performance assessment of metabolomic data processing for multi-class dataset (with quality control sample but without internal standard) using four criteria, and can scan thousands of processing workflows and rank them based on their performances.

Usage

normulticlassqcall(fileName, SAalpha="Y", SAbeta="Y", SAgamma="Y")

Arguments

fileName	Allows the user to indicate the NAME of peak table resulted from PrepareInuputFiles() (default = null).
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).

Examples

library(NOREVA)
multi_qc_data <- PrepareInuputFiles(dataformat = 1,
rawdata = "Multiclass_with_QCS.csv")
normulticlassqcall(fileName = multi_qc_data,
SAalpha="Y", SAbeta="Y", SAgamma="N")

idrblab/NOREVA documentation built on April 17, 2025, 2:04 p.m.