Robust Linear Regression with Median Adjustment and Cyclic Normalization

This method is based on robust linear regression with median adjustment and cyclic normalization. The method is applied iteratively to each pair of samples. For each pair of samples, the median of the differences between the two samples is calculated. A robust linear regression model is fitted to the differences against the averages of the two samples. The fitted model is then used to normalize the two samples. The process is repeated for a number of iterations.

Usage

normalize_rlrmacyc(x, n_iter = 3, by = NULL)

Arguments

x

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

n_iter

The number of iterations to perform. Default is 3.

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.