def _get_mq(self):
"""
Return the current connection to the message queue
:return: A ReactomeMQ object
"""
if not self._mq:
try:
self._mq = reactome_mq.ReactomeMQ(queue_name=reactome_mq.DATASET_QUEUE)
except Exception as e:
LOGGER.error("Failed to connect to MQ service: " + str(e))
raise Exception("Failed to connect to MQ service.", e)
return self._mq
def test_fetch_sc_expression_atlas(self):
dataset_id = "E-MTAB-7078"
k = "3"
resource_id = "ebi_sc_gxa"
loading_id = "loading_sc_gxa_1"
# set the data directory
os.environ["EXAMPLE_DIRECTORY"] = os.path.join(
os.path.dirname(__file__), "testfiles")
fetcher = reactome_analysis_dataset_fetcher.ReactomeAnalysisDatasetFetcher(
)
# post one analysis request
mq = reactome_mq.ReactomeMQ(queue_name=reactome_mq.DATASET_QUEUE)
storage = reactome_storage.ReactomeStorage()
mq.post_analysis(models.dataset_request.DatasetRequest(
loading_id=loading_id,
resource_id=resource_id,
parameters=[
models.dataset_request.DatasetRequestParameter(
name="dataset_id", value=dataset_id),
models.dataset_request.DatasetRequestParameter(name="k",
value=k)
]).to_json(),
method="test")
# process the message
fetcher.process_single_message()
# make sure the status is complete
status = storage.get_status(analysis_identifier=loading_id,
data_type="dataset")
self.assertIsNotNone(status)
status_obj = json.loads(status)
self.assertEqual("complete", status_obj["status"])
dataset_id = status_obj["dataset_id"]
# get the summary
summary_string = storage.get_request_data_summary(dataset_id)
self.assertIsNotNone(summary_string)
# get the data
data_string = storage.get_request_data(dataset_id)
self.assertIsNotNone(data_string)
def test_fetch_proteomics(self):
os.environ["EXAMPLE_DIRECTORY"] = os.path.join(
os.path.dirname(__file__), "../example_datasets")
fetcher = reactome_analysis_dataset_fetcher.ReactomeAnalysisDatasetFetcher(
)
# post one analysis request
mq = reactome_mq.ReactomeMQ(queue_name=reactome_mq.DATASET_QUEUE)
storage = reactome_storage.ReactomeStorage()
mq.post_analysis(models.dataset_request.DatasetRequest(
loading_id="loading_2",
resource_id="example_datasets",
parameters=[
models.dataset_request.DatasetRequestParameter(
name="dataset_id", value="EXAMPLE_MEL_PROT")
]).to_json(),
method="test")
# process the message
fetcher.process_single_message()
# make sure the status is complete
status = storage.get_status(analysis_identifier="loading_2",
data_type="dataset")
self.assertIsNotNone(status)
status_obj = json.loads(status)
self.assertEqual("complete", status_obj["status"])
# get the summary
summary_string = storage.get_request_data_summary("EXAMPLE_MEL_PROT")
self.assertIsNotNone(summary_string)
# get the data
data_string = storage.get_request_data("EXAMPLE_MEL_PROT")
self.assertIsNotNone(data_string)
def test_additional_parameter_analysis(self):
"""
Tests an analysis request that contains multiple blocking factors
"""
request_json = """
{
"analysisId": "test_01",
"datasets": [
{
"data": "\\tSample 1\\tSample2\\tSample 3\\nCD19\\t10\\t2\\t20\\nCD20\\t10\\t20\\t2\\nMITF\\t40\\t20\\t10\\n",
"design": {
"analysisGroup": [
"Treatment",
"Control",
"Treatment"
],
"comparison": {
"group1": "Control",
"group2": "Treatment"
},
"samples": [
"Sample 1",
"Sample 2",
"Sample 3"
]
},
"name": "First experiment",
"type": "rnaseq_counts"
}
],
"methodName": "camera",
"parametes": [
{
"name": "permutations",
"value": "10"
},
{
"name": "permutations",
"value": "10"
}
]
}
"""
# make sure the JSON is valid
obj = json.loads(request_json)
self.assertIsNotNone(obj)
# submit the request
mq = reactome_mq.ReactomeMQ()
mq.post_analysis(request_json, "camera")
# download the gene sets
if not os.path.isfile("/tmp/reactome_homo_sapiens.pkl"):
geneset = self._get_gene_set()
geneset.save("/tmp/reactome_homo_sapiens.pkl")
# enable debug mode
os.environ["REACTOME_WORKER_DEBUG"] = "True"
# start to listen to analyses
worker = reactome_analysis_worker.ReactomeAnalysisWorker()
worker.process_single_message()
# fetch the result
storage = reactome_storage.ReactomeStorage()
result_text = storage.get_result("test_01")
self.assertIsNotNone(result_text, "Result was not saved in redis")
json_obj = json.loads(result_text)
result = AnalysisResult.from_dict(json_obj)
self.assertIsNotNone(result)
self.assertIsNotNone(result.mappings)
self.assertIsNotNone(result.results)
self.assertEqual("68", result.release)
self.assertEqual(1, len(result.results))
self.assertIsNotNone(result.results[0].pathways)
self.assertIsNotNone(result.results[0].fold_changes)
pathway_lines = result.results[0].pathways.split("\n")
self.assertEqual(23, len(pathway_lines))
gene_lines = result.results[0].fold_changes.split("\n")
self.assertEqual(4, len(gene_lines))
def test_incorrect_genes(self):
json_request = """
{
"analysisId": "test_02",
"datasets": [
{
"data": "\\tSample 1\\tSample2\\tSample3\\nCD19\\t10\\t20\\t5\\nCD20\\t10\\t49\\t2\\nMITF\\t56\\t14\\t24\\n",
"design": {
"analysisGroup": [
"Treatment",
"Control",
"Treatment"
],
"comparison": {
"group1": "Control",
"group2": "Treatment"
},
"samples": [
"Sample 1",
"Sample 2",
"Sample 3"
]
},
"name": "First experiment",
"type": "rnaseq_counts"
},
{
"data": "\\tSample 1\\tSample2\\tGene 1\\t10\\t20\\n",
"design": {
"analysisGroup": [
"Treatment",
"Control",
"Treatment"
],
"comparison": {
"group1": "Control",
"group2": "Treatment"
},
"samples": [
"Sample 1",
"Sample 2",
"Sample 3"
]
},
"name": "First experiment",
"type": "rnaseq_counts"
}
],
"methodName": "Camera",
"parameters": [
{
"name": "permutations",
"value": "10"
},
{
"name": "permutations",
"value": "10"
}
]
}
"""
# make sure the JSON is valid
obj = json.loads(json_request)
self.assertIsNotNone(obj)
# submit the request
mq = reactome_mq.ReactomeMQ()
mq.post_analysis(json_request, "camera")
# download the gene sets
if not os.path.isfile("/tmp/reactome_homo_sapiens.pkl"):
geneset = self._get_gene_set()
geneset.save("/tmp/reactome_homo_sapiens.pkl")
# enable debug mode
os.environ["REACTOME_WORKER_DEBUG"] = "True"
# start to listen to analyses
worker = reactome_analysis_worker.ReactomeAnalysisWorker()
worker.process_single_message()
# fetch the result
storage = reactome_storage.ReactomeStorage()
status = storage.get_status("test_02")
status_obj = json.loads(status)
self.assertEqual("failed", status_obj["status"])
result_text = storage.get_result("test_02")
self.assertIsNone(result_text)