center_normalise_to_ref: Center-median normalise the expression matrix in an MSnSet...

In CambridgeCentreForProteomics/camprotR: Processing, analysing and visualising CCP proteomics data

Center-median normalise the expression matrix in an MSnSet using medians from a reference dataset

Description

Center-median normalisation is a simple normalisation method that is appropriate for relative abundance proteomics such as isobaric tagging. This can be achieved with MSnbase::normalise(method='diff.median'). However, for some experimental designs, the normalisation should be against the medians in another dataset. For example, for PTM studies, one may wish to isobaric tag samples, pool, and then PTM-enriched, with the enriched sample quantified in a separate run to the non-enriched (total) sample. In this case, it may make more sense to center-median normalise the PTM-enriched samples using the median from the total samaples.

Usage

center_normalise_to_ref(
  obj,
  medians,
  center_to_zero = FALSE,
  on_log_scale = FALSE
)

Arguments

obj	MSnSet. Contains PSMs.
medians	⁠vector, numeric⁠. Sample medians from reference dataset
center_to_zero	logical. Centre the data range on zero. If FALSE, normalisation retains original data range.
on_log_scale	logical. Input data is log-transformed

Value

Returns an MSnSet with the expression matrix column center-median normalised

CambridgeCentreForProteomics/camprotR documentation built on July 7, 2024, 2:13 a.m.