Correlation Analysis for Glycomics and Glycoproteomics Data

Perform pairwise correlation analysis on variables or samples in the expression data. The function calculates correlation coefficients and p-values for all pairs, with optional multiple testing correction.

Usage

gly_cor(exp, on = "variable", method = "pearson", p_adj_method = "BH", ...)

gly_cor_(
  expr_mat,
  on = "variable",
  method = "pearson",
  p_adj_method = "BH",
  ...
)

Arguments

exp: A glyexp::experiment() object containing expression matrix and sample information.
on: A character string specifying what to correlate. Either "variable" (default) to correlate variables/features, or "sample" to correlate samples/observations.
method: A character string indicating which correlation coefficient is to be computed. One of "pearson" (default) or "spearman". Note: "kendall" is not supported by Hmisc::rcorr.
p_adj_method: A character string specifying the method to adjust p-values. See p.adjust.methods for available methods. Default is "BH". If NULL, no adjustment is performed.
...: Additional arguments passed to Hmisc::rcorr().
expr_mat: A numeric matrix with variables as rows and samples as columns.

Value

A list with two elements:

tidy_result: A tibble with correlation results containing the following columns:
- variable1 or sample1: First element of the pair (depending on on parameter)
- variable2 or sample2: Second element of the pair (depending on on parameter)
- cor: Correlation coefficient
- p_value: Raw p-value from correlation test
- p_adj: Adjusted p-value (if p_adj_method is not NULL)
raw_result: The raw rcorr object from Hmisc::rcorr() The list has classes glystats_cor_res and glystats_res.

Details

The function performs log2 transformation on the expression data (log2(x + 1)) before correlation analysis. When on = "variable" (default), correlations are calculated between variables across samples. When on = "sample", correlations are calculated between samples across variables.

gly_cor() is the top-level API that works with glyexp::experiment() objects。

gly_cor_() is the underlying API that works with matrices directly, providing more flexibility for users who don't use the glyexp package.

Correlation Calculation: Correlation coefficients and p-values are calculated using Hmisc::rcorr() which is more efficient than pairwise stats::cor.test() calls.

Multiple Testing Correction: P-values are adjusted for multiple testing using the method specified by p_adj_method.

Required packages

This function requires the Hmisc package for efficient correlation calculation.