Robust Linear Regression Normalization

This method is based on robust linear regression. The reference sample is calculated as the median value of each variable's abundance across all measured samples. For each sample, a robust linear regression model is fitted to the sample's abundance values against the reference sample's abundance values. The fitted model is then used to normalize the sample's abundance values. The underlying assumption is that the different intensities observed across individuals are imputable to different amounts of the biological material in the collected samples.

Usage

normalize_rlr(x, by = NULL)

Arguments

x

Either a glyexp_experiment object or a matrix. If a matrix, rows should be variables and columns should be samples.

by

Either a column name in sample_info (string) or a factor/vector specifying group assignments for each sample. Optional. If provided, the normalization will be performed within each group.

Value

Returns the same type as the input. If x is a glyexp_experiment, returns a glyexp_experiment with normalized expression matrix. If x is a matrix, returns a normalized matrix.