QCRSC  R Documentation 
Implementation of Quality QCRSC algorithm for signal drift and batch effect correction within/across a multibatch direct infusion mass spectrometry (DIMS) and liquid chromatography mass spectrometry (LCMS) datasets. This version supports missing values, but requires at least 4 data point for quality control (QC) samples measured within each analytical batch. The smoothing parameter (spar) can be optimised using leaveoneout cross validation to avoid overfitting.
QCRSC(
df,
order,
batch,
classes,
spar = 0,
log = TRUE,
minQC = 5,
qc_label = "QC",
spar_lim = c(1.5, 1.5)
)
df 
A matrixlike (e.g. an ordinary matrix, a data frame) or
RangedSummarizedExperimentclass object with
all values of class 
order 

batch 

classes 

spar 

log 

minQC 

qc_label 

spar_lim 
A 2 element numeric vector containing the min and max
values of spar when searching for an optimum. Default 
Object of class SummarizedExperiment
. If input data are a
matrixlike (e.g. an ordinary matrix, a data frame) object, function returns
the same R data structure as input with all value of data type
numeric()
.
Andris Jankevics a.jankevics@bham.ac.uk
Kirwan et al, Anal. Bioanal. Chem., 405 (15), 2013 https://dx.doi.org/10.1007/s0021601368567
classes < MTBLS79$Class
batch < MTBLS79$Batch
order < c(1:ncol(MTBLS79))
out < QCRSC(df = MTBLS79[1:10, ], order = order, batch = MTBLS79$Batch,
classes = MTBLS79$Class, spar = 0, minQC = 4)
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