adding additional documentation to the code

conekt/controllers/graph_comparison.py

@@ -12,9 +12,9 @@
 
 
 # TODO placeholder for the search function
-@graph_comparison.route('/')
-def graph_comparison_overview():
-    return "TEST"
+# @graph_comparison.route('/')
+# def graph_comparison_overview():
+#     return "TEST"
 
 
 @graph_comparison.route('/cluster/<int:one>/<int:two>')

conekt/helpers/cytoscape.py

@@ -254,6 +254,14 @@ def add_depth_data_nodes(network):
 
     @staticmethod
     def connect_homologs(network):
+        """
+        Connects homologous (or orthologous) genes using a dashed edge. Requires a cytoscape.js compatible network as
+        input and will return a network with homologs connected. Note that gene families need to be present in the
+        network *before* applying this function. (e.g. using add_family_data_nodes in this class)
+
+        :param network:
+        :return:
+        """
         connected_network = deepcopy(network)
         """
         Add edges between homologous genes from different targets, family_id needs to be specified !
@@ -411,7 +419,9 @@ def add_depth_data_edges(network):
     @staticmethod
     def prune_unique_lc(network):
         """
-        Remove genes from network that have an lc that occurs only once
+        Remove genes from network that have a unique label (label co-occ.). Requires a Cytoscape.js compatible network
+        and will return a purned copy in the same format. Note that label co-occ. need to be present in the
+        network *before* applying this function. (e.g. using add_lc_data_nodes in this class)
 
         :param network: dict containing the network
         :return: Cytoscape.js compatible network with the pruned network

conekt/models/relationships/sequence_sequence_ecc.py

@@ -46,6 +46,15 @@ class SequenceSequenceECCAssociation(db.Model):
 
     @staticmethod
     def get_ecc_network(sequence, network, family):
+        """
+        Get network connecting a specific sequence to all genes with significant Expression Context Conservation.
+
+
+        :param sequence: internal ID of sequence
+        :param network: network method ID to consider
+        :param family: kind of gene families used to detect ECC
+        :return: network dict (can be made compatible using CytoscapeHelper)
+        """
         data = SequenceSequenceECCAssociation.query.filter(and_(
                 SequenceSequenceECCAssociation.query_id == sequence,
                 SequenceSequenceECCAssociation.query_network_method_id == network,
@@ -112,8 +121,8 @@ def get_ecc_network(sequence, network, family):
     @staticmethod
     def get_ecc_pair_network(ecc_id):
         """
-        Get all data for an SequenceSequenceECCAssociation to make a ECC graph
-
+        Get all data for an SequenceSequenceECCAssociation to make a ECC graph, similar to the pairwise comparisons in
+        Movahedi et al.
 
         :param ecc_id: interal id of the SequenceSequenceECCAssociation
         :return: ecc pair with neighborhood as graph dict
@@ -203,6 +212,15 @@ def get_ecc_pair_network(ecc_id):
 
     @staticmethod
     def get_ecc_multi_network(gf_method_id, sequence_ids):
+        """
+        Creates an ECC network for multiple genes, the resulting network will contain all ECC partners of the input
+        genes. Pruning this network keeping only genes with non-unique label co-occurances is recommended !
+
+
+        :param gf_method_id: gene family method used to detect ECC
+        :param sequence_ids: sequences to include as the core of the network
+        :return: network dict
+        """
         associations = SequenceSequenceECCAssociation.query.\
             filter(SequenceSequenceECCAssociation.gene_family_method_id == gf_method_id).\
             filter(and_(SequenceSequenceECCAssociation.query_id.in_(sequence_ids),