refactor: documentation

docs/src/index.md

@@ -4,16 +4,14 @@ CurrentModule = ISCHIA
 
 # ISCHIA
 
-Documentation for [ISCHIA](https://github.com/aadimator/ISCHIA.jl).
+This package is a reimplementation of the ISCHIA LR interaction algorithm in Julia. The original implementation is in R and can be found [here](https://github.com/ati-lz/ISCHIA). The algorithm is described in the paper [Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA)](https://www.embopress.org/doi/full/10.1038/s44320-023-00006-5). 
+
+In the original implementation, the LR interaction part of the algorithm is very slow and can take days to run on large datasets. This package aims to speed up the LR interaction part of the algorithm by using Julia's speed and parallelism. For comparison, the original implementation took almost 3 hours to run on their toy/smaller dataset, while the same dataset took around 6 seconds to run on this package.
+
+Once the LR interactions are calculated, the rest of the plotting and analysis can be done in R using the original package.
 
 ```@contents
 Pages = ["man/basics.md",
          "man/getting_started.md"]
 Depth = 2
 ```
-
-## Index
-
-```@index
-Pages = ["library/types.md", "library/functions.md"]
-```

docs/src/library/functions.md

@@ -1,8 +1,26 @@
+```@meta
+CurrentModule = ISCHIA
+```
+
+# Functions
+
+## Index
+
 ```@index
 Pages = ["functions.md"]
 ```
 
-```@autodocs
-Modules = [ISCHIA]
-Filter = t -> typeof(t) !== CooccurOutput
+## Co-occurrence Analysis
+
+```@docs
+calculate_cooccurrence_stats
+summarize_cooccur
+
+```
+
+## LR-Enrichment Analysis
+
+```@docs
+find_enriched_LR_pairs
+find_differentially_cooccurring_LR_pairs
 ```

docs/src/library/internals.md

@@ -0,0 +1,12 @@
+```@meta
+CurrentModule = ISCHIA
+```
+
+# Utility Functions
+
+These functions are for internal use. They can be accessed by appending the package name and a dot before the function name, e.g. `ISCHIA.calculate_cooccurrence_matrix`. Keep in mind that these functions can change their signature without warnings.
+
+```@docs
+ISCHIA.calculate_cooccurrence_matrix
+ISCHIA.effect_sizes
+```

docs/src/library/types.md

@@ -1,3 +1,9 @@
+```@meta
+CurrentModule = ISCHIA
+```
+
+# Types
+
 ```@index
 Pages = ["types.md"]
 ```

src/cooccur.jl

@@ -58,7 +58,7 @@ A species by species matrix where the upper triangle contains N for each species
 
 # 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/utils.jl

@@ -13,6 +13,7 @@ Effect sizes as a data frame.
 # Example
 ```julia
 effect_sizes(cooccur_object)
+```
 """
 function effect_sizes(cooccur; standardized=true)
     cooccur_results = cooccur[:results]
@@ -65,6 +66,7 @@ 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