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Run Correlation Analysis

Source: R/run_correlation.R
run_correlation.Rd

Computes correlations between exposures and feature types including DEGs, omics, latent factors, top factor features, or principal components (PCs). Optionally computes feature–feature correlations to support network analysis.

Usage

run_correlation(
  expomicset,
  feature_type = c("degs", "omics", "factors", "factor_features", "exposures", "pcs"),
  exposure_cols = NULL,
  variable_map = NULL,
  n_pcs = NULL,
  feature_cors = FALSE,
  robust = FALSE,
  score_col = "stability_score",
  score_thresh = NULL,
  correlation_method = "spearman",
  correlation_cutoff = 0.3,
  cor_pval_column = "p.value",
  pval_cutoff = 0.05,
  deg_pval_col = "adj.P.Val",
  deg_logfc_col = "logFC",
  deg_pval_thresh = 0.05,
  deg_logfc_thresh = log2(1.5),
  batch_size = 1500,
  action = c("add", "get")
)

Arguments

expomicset

A MultiAssayExperiment object.

feature_type

Type of features to correlate. One of "degs", "omics", "factors", "factor_features", "exposures", or "pcs".

exposure_cols

Optional vector of exposure column names (from colData) to use.

variable_map

Optional mapping of features to include by assay for omics mode.

n_pcs

Number of PCs to use when feature_type = "pcs".

feature_cors

Logical; if TRUE, compute correlations between features rather than with exposures.

robust

Logical; restrict DEGs to those passing sensitivity threshold.

score_col

Column name in sensitivity analysis with feature stability score.

score_thresh

Threshold for filtering robust features.

correlation_method

One of "pearson", "spearman", or "kendall".

correlation_cutoff

Minimum absolute correlation to retain.

cor_pval_column

Column in output to filter by p-value (default: "p.value").

pval_cutoff

Maximum p-value or FDR threshold to retain a correlation.

deg_pval_col

Column with DEG adjusted p-values.

deg_logfc_col

Column with DEG log fold-changes.

deg_pval_thresh

P-value cutoff for DEGs.

deg_logfc_thresh

Log fold-change cutoff for DEGs.

batch_size

Number of features to process per batch (default: 1500).

action

Whether to "add" results to metadata or "get" as a data frame.

Value

If action = "add", returns updated MultiAssayExperiment with results added to metadata. If action = "get", returns a tidy data.frame of correlations.

Examples

if (FALSE) { # \dontrun{
run_correlation(expomicset, feature_type = "omics", correlation_method = "spearman")
run_correlation(expomicset, feature_type = "degs", feature_cors = TRUE)
} # }