Variance Stabilizing Normalization

This function is a wrapper around limma::normalizeVSN(). Evidence proved that this method performs well in reducing noise and boosting differential expression detection. Log-transformation is not needed for downstream statistical analysis, for this normalization method performs a log-like transformation internally. Due to the same reason, fold change estimates will be severely distorted. Please use this method with caution. See this paper for more information.

Usage

normalize_vsn(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.

...

Additional arguments to pass to limma::normalizeVSN().

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.

Details

At least 42 variables should be provided for this method. This follows the convention of the vsn package.