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Normalize expression data

Source: R/preprocessing.R
normalize_data.Rd

Applies quantile normalization or z-score normalization to expression matrices. Designed for gene expression data (rows = samples, columns = genes).

Usage

normalize_data(data, method = c("zscore", "rank", "minmax", "quantile"), ...)

Arguments

data

Numeric matrix or data.frame (samples x variables).

method

Normalization method:

  • "zscore" (default): Center and scale each column to mean 0, sd 1.

  • "rank": Transform to normal scores via rank-based inverse normal.

  • "minmax": Scale each column to [0, 1].

  • "quantile": Quantile normalize across columns (samples must be aligned; i.e., rows are matched observations).

...

Additional arguments (currently unused).

Value

Normalized matrix with same dimensions.

Examples

set.seed(42)
dat <- matrix(rexp(200), nrow = 20, ncol = 10)
colnames(dat) <- paste0("Gene", 1:10)
norm_z <- normalize_data(dat, "zscore")
norm_r <- normalize_data(dat, "rank")
norm_q <- normalize_data(dat, "quantile")