def get(self, datasetId, dataType):
"""
Returns samples or metadata files for a dataset, expects: {dataset_id}/{data_type} where data_type is either 'samples' or 'metadata'.
"""
ds = datasets.Dataset(datasetId)
json_string = ds.isPrivate()
json_object = json.loads(json_string)
result = json_object[0]
if result['datasets'][0]['private'] == True:
return Response("Error: Private dataset",
mimetype="text/tsv",
headers={"Content-disposition": datasetId})
if dataType == "samples":
filename = 'attachment; filename=' + 'dataset_id_' + str(
datasetId) + '_samples' + '.csv'
json_string = ds.sampleTable().set_index("sample_id").to_csv()
result = Response(json_string,
mimetype="text/csv",
headers={"Content-disposition": filename})
return result
elif dataType == "metadata":
result = ds.metadataTable()
return result
def getTable(datasetId, dataType):
ds = datasets.Dataset(datasetId)
json_string = ds.isPrivate()
json_object = json.loads(json_string)
result = json_object[0]
if result['datasets'][0]['private'] == True:
return Response("Error: Private dataset",
mimetype="text/tsv",
headers={"Content-disposition": datasetId})
if dataType == "samples":
filename = 'attachment; filename=' + 'dataset_id_' + str(
datasetId) + '_samples' + '.csv'
json_string = ds.sampleTable().set_index("sample_id").to_csv()
result = Response(json_string,
mimetype="text/csv",
headers={"Content-disposition": filename})
elif dataType == "metadata":
result = ds.metadataTable()
elif dataType == "expression":
print("You chose expression")
return result
def summary_table_search():
data = request.get_json()
payload = data['data']
searchTerm = payload['searchTerm']
datasetId = 1000
ds = datasets.Dataset(datasetId)
summaryTableSearch = ds.summaryTableSearch(str(searchTerm))
return summaryTableSearch.to_json(orient="split")
def atlas_update():
data = request.get_json()
payload = data['data']
print(payload)
datasetId = payload['dataset_id']
column = payload['column']
rowIds = payload['rowIds']
value = payload['value']
ds = datasets.Dataset(datasetId)
updateAtlasValue = ds.updateAtlasValue(column, rowIds, value)
return updateAtlasValue
def get(self, datasetId):
"""
Returns samples or metadata files for a dataset, expects: {dataset_id}/{data_type} where data_type is either 'samples' or 'metadata'.
"""
ds = datasets.Dataset(datasetId)
json_string = ds.isPrivate()
json_object = json.loads(json_string)
result = json_object[0]
if result['datasets'][0]['private'] == True:
return Response("Private dataset" , mimetype="text/tsv", headers={"Content-disposition": datasetId})
elif result['datasets'][0]['private'] == False:
return Response("Public dataset" , mimetype="text/tsv", headers={"Content-disposition": datasetId})
def samples_grid():
data = request.get_json()
dataset_id = data['dataset_id']
ds = datasets.Dataset(dataset_id)
sampleTable = ds.sampleTable()
jsonSampleTable = sampleTable.to_json(orient="split")
if session["loggedIn"] == True:
if jsonSampleTable != None:
return jsonSampleTable
else:
return {
"Message": "No samples found for dataset_id: " + dataset_id
}
else:
return "Access Denied"
def get(self, datasetId, key):
"""
Returns expression files for a dataset, expects: {dataset_id}/{string} where string is either 'genes' or 'raw'.
"""
dataType = "expression"
key = key
ds = datasets.Dataset(datasetId)
json_string = ds.isPrivate()
json_object = json.loads(json_string)
result = json_object[0]
print("debugging:")
print(result)
# if result['datasets'][0]['private'] == True:
# return Response("Error: Private dataset", mimetype="text/tsv", headers={"Content-disposition": datasetId})
json_string = ds.expressionMatrix(key=key).to_json(orient="split")
result = Response(json_string, mimetype="text/csv", headers={"Content-disposition": key})
return result
def summary_table():
datasetId = 1000
ds = datasets.Dataset(datasetId)
summaryTable = ds.summaryTable()
dataset_id = summaryTable['dataset_id'].to_list()
title = summaryTable['title'].to_list()
authors = summaryTable['authors'].to_list()
description = summaryTable['description'].to_list()
generic_sample_type = summaryTable['generic_sample_type'].to_list()
handle = summaryTable['handle'].to_list()
date_list = []
for item in handle:
if item is not None:
result = item.split("_")
value = result[1]
date_list.append(value)
pubmed = summaryTable['pubmed'].to_list()
obj_list = []
for (a, b, c, d, e, f, g) in zip(dataset_id, title, authors, description,
generic_sample_type, date_list, pubmed):
obj = {
"Dataset_id": a,
"Title": b,
"Authors": c,
"Description": d,
"generic_sample_type": e,
"date": f,
"pubmed": g
}
obj_list.append(obj)
obj_list.pop(0) # The first dict/item in the array is always null - remov.
response_object = {"count": 10, "entries": obj_list}
if session["loggedIn"] == True:
return response_object
else:
return "Access Denied"
def atlas_samples_grid():
data = request.get_json()
atlas_type = data['atlas_type']
atlas_model = atlas_type['atlas_model']
atlas_project = atlas_type['tierModel']
update_column = atlas_model + '_' + atlas_project
dataset_id = data['dataset_id']
ds = datasets.Dataset(dataset_id)
atlasSampleTable = ds.atlasSampleTable()
newdf = atlasSampleTable[['sample_id'] + [update_column] + [
'annotator', 'evidence', 'phenotype', 'activation_status',
'display_metadata', 'include_blood', 'include_imac'
]] # construct a dataframe with the selected tier included in it.
include_blood = newdf['include_blood'].unique()
include_imac = newdf['include_imac'].unique()
if include_blood[0] == False:
print("drop all blood tier data")
# finaldf = atlasSampleTable[['sample_id'] + [update_column] + ['annotator', 'evidence', 'phenotype', 'activation_status', 'display_metadata', 'include_blood', 'include_imac'] ]
elif include_imac[0] == False:
print("drop all imac tier data")
elif include_blood[0] and include_imac[0] == False:
print("drop all tier data")
elif include_blood[0] and include_imac[0] == True:
print("include all tier data")
jsonSampleTable = newdf.to_json(orient="split")
if session["loggedIn"] == True:
return jsonSampleTable
else:
return "Access Denied"