Perform Probabilistic Quotient Normalization (PQN) for sample intensities. The PQN method determines a dilution factor for each sample by comparing the distribution of quotients between samples and a reference spectrum, followed by sample normalization using this dilution factor. The reference spectrum in this method is the average lipid abundance of all samples (excluding blanks).
normalize_pqn(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:
Whether the normalized values should be log2 transformed. Default
A LipidomicsExperiment object with normalized values
Dieterle, F., Ross, A., Schlotterbeck, G., & Senn, H. (2006). Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics. Analytical chemistry, 78(13), 4281-4290.
datadir <- system.file("extdata", package = "lipidr") filelist <- list.files(datadir, "data.csv", full.names = TRUE) d <- read_skyline(filelist)#>#>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_normalized <- normalize_pqn( d_summarized, measure = "Area", exclude = "blank", log = TRUE )#> Warning: Area contains missing/non-finite values. Replacing with mimnum detected value.