Normalize each class by its corresponding internal standard(s). Lipid classes are normalized using corresponding internal standard(s) of the same lipid class. If no corresponding internal standard is found the average of all measured internal standards is used instead.
normalize_istd(data, measure = "Area", exclude = "blank", log = TRUE)
Which measure to use as intensity, usually Area,
Area Normalized or Height. Default is
Samples to exclude, can be either:
"blank" - automatically detected blank samples and exclude them logical vector with the same length as samples. Default.
whether the normalized values should be log2 transformed. Default
A LipidomicsExperiment object with normalized values. Each molecule is normalized against the internal standard from the same class.
datadir <- system.file("extdata", package = "lipidr") filelist <- list.files(datadir, "data.csv", full.names = TRUE) d <- read_skyline(filelist) #> Successfully read 3 methods. #> Your data contain 58 samples, 10 lipid classes, 277 lipid molecules. clinical_file <- system.file("extdata", "clin.csv", package = "lipidr") d <- add_sample_annotation(d, clinical_file) d_summarized <- summarize_transitions(d, method = "average") # Normalize data that have been summarized (single value per molecule). data_norm_istd <- normalize_istd( d_summarized, measure = "Area", exclude = "blank", log = TRUE ) #> Warning: Area contains missing/non-finite values. Replacing with mimnum detected value.