feat: Refactor co-occurrence analysis functions

Author: aadimator

src/cooccur.jl

@@ -50,15 +50,6 @@ This function creates a species by species matrix of potential co-occurring site
 
 # Returns
 A species by species matrix where the upper triangle contains N for each species pair.
-
-# Examples
-```julia
-# Define a binary species by site matrix
-# species_matrix = rand(Bool, num_species, num_sites)
-
-# Calculate the co-occurrence matrix N
-# cooccurrence_matrix = create_N_matrix(species_matrix)
-```
 """
 function calculate_cooccurrence_matrix(mat::Matrix{Int})
     num_species = size(mat, 1)

src/lr_enrichment.jl

@@ -122,11 +122,6 @@ Find LR (Ligand Receptor) pairs that are significantly co-occurring in one group
 
 # Returns
 List of LR pairs enriched in Group 1 and not in Group 2.
-
-# Example
-```julia
-result = find_differentially_cooccurring_LR_pairs(cooc_df_1, cooc_df_2, 0.05, 0.1)
-```
 """
 function find_differentially_cooccurring_LR_pairs(
 	cooc_df_1::DataFrame,
@@ -177,11 +172,6 @@ Find LR (Ligand Receptor) pairs that are significantly co-occurring in one group
 
 # Returns
 List of LR pairs enriched in Group 1 and not in Group 2.
-
-# Example
-```julia
-result = find_differentially_cooccurring_LR_pairs(group1_results, group2_results, 0.05, 0.1)
-```
 """
 function find_differentially_cooccurring_LR_pairs(
 	group1_results::Dict{String, Any},

src/utils.jl

@@ -9,11 +9,6 @@ Calculate effect sizes for co-occurrence analysis results.
 
 # Returns
 Effect sizes as a data frame.
-
-# Example
-```julia
-effect_sizes(cooccur_object)
-```
 """
 function effect_sizes(cooccur; standardized=true)
     cooccur_results = cooccur[:results]
@@ -62,11 +57,6 @@ Summarize the results of a co-occurrence analysis.
 
 # Returns
 A summary of the co-occurrence analysis results as a dictionary.
-
-# Example
-```julia
-summary = summarize_cooccur(cooccur_object)
-```
 """
 function summarize_cooccur(cooccur::CooccurOutput)
     # Print basic analysis information