diff --git a/cami_src/cami_suite.py b/cami_src/cami_suite.py
index 91958a63aef68664b6a2823cef623cbf8d53dea8..0b4b7b5249666d6c2650f329357421bc2608b130 100644
--- a/cami_src/cami_suite.py
+++ b/cami_src/cami_suite.py
@@ -181,9 +181,9 @@ class cami():
:rtype: set()
"""
tool.create_tmp_output_dir(self.tmp_dir) # creates the temporary input directory
- print(f"preparing {tool.name} input...")
+ if self.debug: print(f"preparing {tool.name} input...")
inputparams = tool.prepare_input()
- print(f'running {tool.name}...')
+ if self.debug: print(f'running {tool.name}...')
preds = set(tool.run_algorithm(inputparams))
if self.debug:
print(f'{tool.name} predicted {len(preds)} active vertices (seeds not excluded):')
@@ -225,7 +225,8 @@ class cami():
to the corresponding tool
:rtype: dict(AlgorithmWrapper():set(Graph.vertex()))
"""
- print(f'Creating result sets of all {self.nof_tools} tools...')
+ if self.debug:
+ print(f'Creating result sets of all {self.nof_tools} tools...')
pred_sets = {tool:None for tool in self.tool_wrappers}
if self.threaded:
@@ -338,18 +339,23 @@ class cami():
}},
}
+ # transform all vertex indices to their corresponding gene names in a result set
+ for tool in result_sets:
+ self.result_gene_sets[tool.name] = set([gene_name_map[vertex] for vertex in result_sets[tool]])
+
# create integer codes for cami_versions (needed for predicted_by vertex property)
recursion_limit = sys.getrecursionlimit()
for cami_method_name, cami_params in camis.items():
- print("Running " + cami_method_name)
+ if self.debug:
+ print("Running " + cami_method_name)
+ # create integer codes for cami_versions (needed for predicted_by vertex property)
tool_code = max(list(tool_name_map.keys())) + 1
tool_name_map[tool_code] = cami_method_name
cami_vertices, putative_vertices, codes2tools = cami_params['function'](result_sets, ppi_graph, seed_list,
- predicted_by, cami_scores,
- tool_name_map, tool_code,
- cami_params['params'])
-
+ predicted_by, cami_scores,
+ tool_name_map, tool_code,
+ cami_params['params'])
# sort the resulting vertices according to their cami_score
cami_vlist = sorted(cami_vertices, key=lambda v: cami_scores[v], reverse=True)
@@ -363,31 +369,31 @@ class cami():
for vertex in cami_vlist:
print(f'{gene_name_map[vertex]}\t{cami_scores[vertex]}\t{codes2tools[vertex]}')
else:
- print(f'With the {len(seed_genes)} seed genes CAMI ({cami_method_name}) proposes {len(cami_vlist)} to add to the Active Module')
-
+ print(f'With the {len(seed_genes)} seed genes CAMI ({cami_method_name}) proposes {len(cami_vlist)} genes to add to the Active Module')
+
# for visualization with nvenn
- self.result_gene_sets[cami_method_name] = cami_genes
-
+ self.result_gene_sets[cami_method_name] = set(cami_genes)
+
+
# transform all vertex indices to their corresponding gene names in a result set
for tool in result_sets:
self.result_gene_sets[tool.name] = set([gene_name_map[vertex] for vertex in result_sets[tool]])
# add seeds to result sets for drugstone and digest
- for tool in result_sets:
- self.result_module_sets[tool.name] = set(gene_name_map[vertex] for vertex in set(result_sets[tool]).union(self.seed_lst))
-
- assert(self.code2toolname == tool_name_map)
+ for toolname in self.result_gene_sets:
+ self.result_module_sets[toolname] = self.result_gene_sets[toolname].union(set([gene_name_map[svertex] for svertex in self.seed_lst]))
+ print(f'With the {len(seed_genes)} seed genes CAMI ({cami_method_name}) proposes {len(cami_vlist)} to add to the Active Module')
sys.setrecursionlimit(recursion_limit)
# save the results in outputfiles
self.generate_output(cami_method_name, seed_genes, cami_vlist, cami_vertices, putative_vertices, cami_genes,
gene_name_map, codes2tools, cami_scores)
-
def generate_output(self, cami_method, seed_genes, cami_vlist, cami_vertices, putative_vertices, cami_genes,
gene_name_map, codes2tools, cami_scores):
# save all predictions by all tools
- print('Saving the results...')
+ if self.debug:
+ print('Saving the results...')
with open(f'{self.output_dir}/all_predictions_{self.uid}.tsv', 'w') as outputfile:
outputfile.write(f'CAMI predictions with {len(self.seed_lst)} of initially {len(self.initial_seed_lst)} seeds: {seed_genes},\n'+
f'initially: {self.initial_seed_lst}\n')
@@ -401,7 +407,7 @@ class cami():
ncbi_url = ('\tncbi_url' if self.ncbi else '')
ncbi_summary = ('\tncbi_summary' if self.ncbi else '')
- with open(f'{self.output_dir}/CAMI_output_{self.uid}.tsv', 'w') as outputfile:
+ with open(f'{self.output_dir}/{cami_method}_output_{self.uid}.tsv', 'w') as outputfile:
outputfile.write(f'gene\tindex_in_graph\tcami_score\tdegree_in_graph{ncbi_url}{ncbi_summary}\n')
for vertex in cami_vlist:
if self.ncbi:
@@ -415,32 +421,28 @@ class cami():
url, summary = '',''
outputfile.write(f'{gene_name_map[vertex]}\t{str(vertex)}\t{cami_scores[vertex]}\t{vertex.out_degree()}{url}{summary}\n')
- # save the whole module
- whole_module = []
- with open(f'{self.output_dir}/CAMI_module_{cami_method}_{self.uid}.txt', 'w') as modfile:
- for vertex in seed_genes:
- modfile.write(f'{vertex}\n')
- whole_module.append(vertex)
- for vertex in cami_genes:
- modfile.write(f'{vertex}\n')
- whole_module.append(vertex)
-
- print(f'saved cami output in: {self.output_dir}/CAMI_output_{self.uid}.tsv')
- print(f'saved the Consensus Active Module by CAMI in: {self.output_dir}/CAMI_nodes_{cami_method}_{self.uid}.txt')
+ # # save the whole module
+ # whole_module = []
+ # with open(f'{self.output_dir}/{cami_method}_module_{self.uid}.txt', 'w') as modfile:
+ # for vertex in seed_genes:
+ # modfile.write(f'{vertex}\n')
+ # whole_module.append(vertex)
+ # for vertex in cami_genes:
+ # modfile.write(f'{vertex}\n')
+ # whole_module.append(vertex)
+
+ # print(f'saved {cami_method} output in: {cami_method}_output_{self.uid}.tsv')
+ # print(f'saved the Consensus Active Module by CAMI in: {self.output_dir}/{cami_method}_module_{self.uid}.txt')
- # save predictions by the other tools
- for tool in self.result_gene_sets:
+ # save predicted modules by all other tools
+ for tool in self.result_module_sets:
with open(f'{self.output_dir}/{tool}_output_{self.uid}.tsv', 'w') as outputfile:
outputfile.write('gene\n')
for gene in self.result_gene_sets[tool]:
outputfile.write(f'{gene}\n')
- print(f'saved {tool} output in: {self.output_dir}/{tool}_output_{self.uid}.tsv')
-
- # return values
- consensus = {}
- consensus['module'] = whole_module
- consensus['seeds'] = self.seed_lst
+ if self.debug:
+ print(f'saved {tool} output in: {self.output_dir}/{tool}_output_{self.uid}.tsv')
def use_nvenn(self):
@@ -489,7 +491,6 @@ class cami():
#print(list(set(cami_symbol_edges)))
url = drugstone.send_request(cami_symbols, cami_symbol_edges)
print(f'You can find a network visualization of the CAMI module via: {url}')
- print('The link was also saved in the outputfolder for later.')
with open(f'{self.output_dir}/drugstone_link_{self.uid}.txt', 'w') as f:
f.write(url)
return url