Module norm 

Between-array normalization of single-channel matrices. Port of limma’s normalizeBetweenArrays matrix path and its constituents normalizeQuantiles (quantile), normalizeMedianValues (scale) and normalizeCyclicLoess (cyclicloess). Two-colour (RGList/MAList) and vsn methods are out of scope for the pure-Rust statistical port.

Enums

CyclicMethod

Cyclic-loess variant.

NormalizeMethod

Between-array normalization method for a single-channel matrix.

Functions

normalize_between_arrays

normalizeBetweenArrays(object, method) for a single-channel matrix (n_genes x n_samples). CyclicLoess uses the default fast method with adaptive span and three iterations.

normalize_cyclic_loess

normalizeCyclicLoess: iteratively detrend each column’s deviation from the row means (fast) or pairwise MA differences (pairs/affy) with a LOWESS fit (loessFit, weights = NULL). With adaptive_span the span is chosen by chooseLowessSpan(nrow, 50, 0.3, 1/3).

normalize_median_abs_values

normalizeMedianAbsValues: scale each column to a common median absolute value. Identical to normalize_median_values except the per-column median is taken over abs(x) (matching limma’s apply(abs(x), 2, median)).

normalize_median_values

normalizeMedianValues: scale each column to a common median. Columns are divided by exp(log(median_j) - mean_j log(median)).

normalize_quantiles

normalizeQuantiles(A, ties): give every column the same quantiles, the average of the sorted columns. Missing values are allowed (a column’s observed values are stretched to the full grid before averaging, and only its observed entries are re-mapped).