shiftCor: shiftCor provide the QC-RLS correction for large scale...
In idrblab/NOREVA2020: R Package for Assessing Normalization for Metabolomic Data

shiftCor provide the QC-RLS correction for large scale metabolomics.

shiftCor(
  samPeno,
  samFile,
  Frule = 0.8,
  QCspan = 0.75,
  degree = 2,
  imputeM = "KNN"
)

`samPeno`	a file with the meta information.
`samFile`	a file with the expression information.
`Frule`	The cut-off value for missing value filter function.
`QCspan`	The smoothing parameter which controls the bias-variance tradeoff. if the QCspan is set at '0', the generalised cross-validation will be performed to avoid overfitting the observed data.
`degree`	Lets you specify local constant regression (i.e., the Nadaraya-Watson estimator, degree=0), local linear regression (degree=1), or local polynomial fits (degree=2, the default).
`imputeM`	The parameter for imputation method.(i.e., nearest neighbor averaging, "KNN"; minimum values for imputed variables, "min", median values for imputed variables (Group dependent) "median"). examples library(statTarget) datpath <- system.file("extdata",package = "statTarget") samPeno <- paste(datpath,"MTBLS79_sampleList.csv", sep="/") samFile <- paste(datpath,"MTBLS79.csv", sep="/") shiftCor(samPeno,samFile,Frule = 0.8,QCspan = 0.75, degree = 2,imputeM = "KNN") export