metamorphr (version 0.2.0)

normalize_pqn: Normalize intensities across samples using a Probabilistic Quotient Normalization (PQN)

Description

This method was originally developed for H-NMR spectra of complex biofluids but has been adapted for other 'omics data. It aims to eliminate dilution effects by calculating the most probable dilution factor for each sample, relative to one or more reference samples. See references for more details.

Usage

normalize_pqn(
  data,
  fn = "median",
  normalize_sum = TRUE,
  reference_samples = NULL,
  ref_as_group = FALSE,
  group_column = NULL
)

Value

A tibble with intensities normalized across samples.

Arguments

data

A tidy tibble created by read_featuretable.

fn

Which function should be used to calculate the reference spectrum from the reference samples? Can be either "mean" or "median".

normalize_sum

A logical indicating whether a sum normalization (aka total area normalization) should be performed prior to PQN. It is recommended to do so and other packages (e.g., KODAMA) also perform a sum normalization prior to PQN.

reference_samples

Either NULL or a character or character vector containing the sample(s) to calculate the reference spectrum from. In the original publication, it is advised to calculate the median of control samples. If NULL, all samples will be used to calculate the reference spectrum.

ref_as_group

A logical indicating if reference_samples are the names of samples or group(s).

group_column

Only relevant if ref_as_group = TRUE. Which column should be used for grouping reference and non-reference samples? Usually group_column = Group. Uses args_data_masking.

References

• F. Dieterle, A. Ross, G. Schlotterbeck, H. Senn, Anal. Chem. 2006, 78, 4281–4290, DOI 10.1021/ac051632c.

Examples

# specify the reference samples with their sample names
toy_metaboscape %>%
  impute_lod() %>%
  normalize_pqn(reference_samples = c("QC1", "QC2", "QC3"))

# specify the reference samples with their group names
toy_metaboscape %>%
  join_metadata(toy_metaboscape_metadata) %>%
  impute_lod() %>%
  normalize_pqn(reference_samples = c("QC"), ref_as_group = TRUE, group_column = Group)