shiftCor: shiftCor for GUI

Description Usage Arguments Value Examples

View source: R/shiftCor_v2.R

Description

shiftCor provides the QC based signal correction for large scale metabolomics and targeted proteomics.

Usage

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shiftCor(samPeno, samFile, Frule = 0.8, MLmethod = "QCRFSC",
  ntree = 500, QCspan = 0, degree = 2, imputeM = "KNN",
  coCV = 30, plot = FALSE)

Arguments

samPeno

The file with the meta information including the sample name, batches, class and order.

samFile

The file with the expression information.

Frule

Modified n precent rule function. A variable will be kept if it has a non-zero value for at least n precent of samples in any one group. (Default: 0.8)

MLmethod

The machine learning method for QC based signal correction. i.e. QC based random forest signal correction (QC-RFSC) and QC based LOESS signal correction (QC-RLSC).

ntree

Number of trees to grow in random forest model.

QCspan

The smoothing parameter for QC-RLSC which controls the bias-variance tradeoff in QC-RLSC method 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) for QC-RLSC.

imputeM

The parameter for imputation method i.e., nearest neighbor averaging, 'KNN'; minimum values, 'min'; Half of minimum values, 'minHalf'; median values, 'median'.

coCV

Define the cutoff value (0-100) of CV for controlling the number of features.

plot

Defines if images of feature quality should be generated (TRUE) or not (FALSE). Defaults to FALSE.

Value

the shiftCor files. See the details at https://stattarget.github.io

Examples

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datpath <- system.file('extdata',package = 'statTarget')
samPeno <- paste(datpath,'MTBLS79_sampleList.csv', sep='/')
samFile <- paste(datpath,'MTBLS79.csv', sep='/')
shiftCor(samPeno,samFile, MLmethod = 'QCRFSC', imputeM = 'KNN',coCV = 30)

statTarget documentation built on Nov. 8, 2020, 8:27 p.m.