Created script to represent the data as a graph

phyloTree/dataset_to_tree.py

+import os
+from collections import OrderedDict
+
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import networkx as nx
+
+taxonomy_ranks = OrderedDict()
+taxonomy_ranks['k__'] = 'kingdom'
+taxonomy_ranks['p__'] = 'phylum'
+taxonomy_ranks['c__'] = 'class'
+taxonomy_ranks['o__'] = 'order'
+taxonomy_ranks['f__'] = 'family'
+taxonomy_ranks['g__'] = 'genus'
+
+
+def empty_taxonomy():
+    taxonomy = OrderedDict()
+
+    taxonomy['kingdom'] = None
+    taxonomy['phylum'] = None
+    taxonomy['class'] = None
+    taxonomy['order'] = None
+    taxonomy['family'] = None
+    taxonomy['genus'] = None
+
+    return taxonomy
+
+
+def split_taxonomy(bacteria):
+    splited_taxonomy = bacteria.split('.')
+    fixed_taxonomy = []
+
+    for element in splited_taxonomy:
+        if element.startswith('__', 1) or element == 'Other':
+            fixed_taxonomy.append(element)
+        else:
+            fixed_taxonomy[-1] = '.'.join([fixed_taxonomy[-1], element])
+
+    return fixed_taxonomy
+
+
+def extract_taxonomy(bacteria):
+
+    list_taxonomy_ranks = split_taxonomy(bacteria)
+    taxonomy = empty_taxonomy()
+    for rank in list_taxonomy_ranks:
+        if not rank == 'Other':
+            correnct_rank = taxonomy_ranks[rank[0:3]]
+            if not rank[3:] == '':
+                taxonomy[correnct_rank] = rank[3:]
+
+    return taxonomy
+
+DISEASE = 'CDf'
+DATA_DIR = 'true_data'
+
+# ============================================
+# -- DATA loading section
+# ============================================
+
+DISEASE_FOLDER = ''.join(['HS_', DISEASE])
+
+TRAINING_DATA_FILEPATH = os.path.join(DATA_DIR, DISEASE_FOLDER,
+                                      ''.join(['Sokol_16S_taxa_HS_', DISEASE, '_commsamp_training.txt']))
+COORDINATES_FILEPATH = os.path.join(DATA_DIR, 'coordinates',
+                                    ''.join(['coordinates_', DISEASE.lower(), '.txt']))
+TRAINING_LABELS_FILEPATH = os.path.join(DATA_DIR, DISEASE_FOLDER,
+                                        ''.join(['Sokol_16S_taxa_HS_', DISEASE, '_commsamp_training_lab.txt']))
+TEST_DATA_FILEPATH = os.path.join(DATA_DIR, DISEASE_FOLDER,
+                                  ''.join(['Sokol_16S_taxa_HS_', DISEASE, '_commsamp_test.txt']))
+TEST_LABELS_FILEPATH = os.path.join(DATA_DIR, DISEASE_FOLDER,
+                                    ''.join(['Sokol_16S_taxa_HS_', DISEASE, '_commsamp_test_lab.txt']))
+
+training = pd.read_csv(TRAINING_DATA_FILEPATH, sep='\t', index_col=0,)
+training_lab = pd.read_csv(TRAINING_LABELS_FILEPATH, sep='\t',dtype=np.int, names=' ')
+test = pd.read_csv(TEST_DATA_FILEPATH, sep='\t', index_col=0)
+test_lab = pd.read_csv(TEST_LABELS_FILEPATH, sep='\t',dtype=np.int, names=' ')
+
+# ============================================
+# -- Process samples to extract taxonomy
+# ============================================
+
+# G = nx.DiGraph()
+G = nx.Graph()
+
+bacterias = training.columns
+
+for bacteria in bacterias:
+    taxonomy = extract_taxonomy(bacteria)
+    previous_name = None
+    for n, (rank, name) in enumerate(taxonomy.items()):
+        if name is not None:
+            G.add_node(name)
+            if not n == 0 and previous_name is not None:
+                G.add_edge(previous_name, name)
+
+        previous_name = name
+
+a = nx.adjacency_matrix(G)
+print(a)
+plt.spy(a, precision=0.01, markersize=1)
+plt.show()
+# pos=nx.nx.nx_pydot.graphviz_layout(G, prog='dot')
+# nx.draw(G, pos, with_labels=True, arrows=False)
+figure = plt.gcf()
+figure.set_size_inches(4, 3)
+# plt.show()
+plt.savefig('2.jpg')
+

phyloTree/true_data/HS_CDf/Sokol_16S_taxa_HS_CDf_commsamp_test_lab.txt

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phyloTree/true_data/HS_CDf/Sokol_16S_taxa_HS_CDf_commsamp_training_lab.txt

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phyloTree/true_data/HS_CDr/Sokol_16S_taxa_HS_CDr_commsamp_test_lab.txt

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phyloTree/true_data/HS_CDr/Sokol_16S_taxa_HS_CDr_commsamp_training_lab.txt

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phyloTree/true_data/HS_UCf/Sokol_16S_taxa_HS_UCf_commsamp_test_lab.txt

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phyloTree/true_data/HS_UCf/Sokol_16S_taxa_HS_UCf_commsamp_training_lab.txt

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phyloTree/true_data/HS_UCr/Sokol_16S_taxa_HS_UCr_commsamp_test_lab.txt

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phyloTree/true_data/HS_iCDf/Sokol_16S_taxa_HS_iCDf_commsamp_test_lab.txt

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