Intra-batch normalisation

Removes unwanted variation within batch.

rlm and loess

rlm or loess methods fits robust linear model or loess respectively to samples selected from pCtName. rlmShort and loessShort both performs robust smoother rlm and loess respectively then performs RUV-III utilising the replicates identified from intra_rep. Parameters negCtl and intra_k will be used for RUV-III.

intraNorm(
  dat_list,
  assay,
  method = c("rlm", "loess", "rlmShort", "loessShort"),
  pCtlName = NULL,
  rep = NULL,
  k,
  negCtl = NULL
)

Arguments

dat_list

A list of SummarizedExperiment data where each object represents a batch.

assay

An assay name to measure the missingness of the signals.

method

A method to use for removing signal drift and unwanted variations. See descriptions for further details.

pCtlName

A column variable name in colData of each SummarizedExperiment object which selects samples to be used to fit the robust smoother.

rep

A column variable name in colData of each SummarizedExperiment object which identifies intra-batch (short) sample replicates.

k

A RUV-III paramater k value

negCtl

A vector of row IDs for selection of stable matbolites to be used as negative control in RUV.

Value

A list of intra-batch normalized SummarizedExperiment data.