Calculate Eigengenes for CoReMo modules — cor_module_coremo

This function will calculate the eigengene values for the modules on a per sample basis and add correlations of the gene expression of a given gene within the module to its eigengene.

Usage

cor_module_coremo_eigengene(object, min_stability = NULL, .verbose = TRUE)

Arguments

object: The class, see BulkCoExp().
min_stability: Optional float. The minimum stability for the gene you wish to filter for based on the leave-one-out resampling. If NULL, no filtering will be applied.
.verbose: Boolean. Controls verbosity of the function.

Value

The class with added correlations to the modules and the values for a given eigengene per sample as a data.table.

References

Srivastava, et al., Nat. Commun., 2018; Francois, Romagnolo, et al., Nat. Commun., 2024.

Examples

# eigengenes per module and the gene to eigengene correlations
mat <- t(synthetic_signal_matrix()$mat)
obj <- BulkCoExp(mat, data.table::data.table(sample_id = rownames(mat)))
obj <- preprocess_bulk_coexp(obj, hvg = 0.3, .verbose = FALSE)
obj <- cor_module_processing(obj, cor_method = "spearman", .verbose = FALSE)
obj <- cor_module_coremo_clustering(obj, .verbose = FALSE)
obj <- cor_module_coremo_eigengene(obj, .verbose = FALSE)
head(get_modules(get_results(obj)))
#> Key: <gene>
#>       gene module_id eigengene_cor
#>     <char>    <char>         <num>
#> 1:  gene10         1     0.7968888
#> 2: gene100         1     0.7727678
#> 3: gene101         2     0.5837753
#> 4: gene102         2     0.7664666
#> 5: gene103         2     0.7334704
#> 6: gene107         2     0.5509239