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authorBonfaceKilz2021-03-08 15:22:26 +0300
committerBonfaceKilz2021-03-08 21:09:58 +0300
commite5bcb0faccf67f213538cad3670a8d1378c56ce7 (patch)
treeefcec4b89beb9262b86b3dbad4f06e2092d0a7da /gn3/api/gemma.py
parentc4449fe7eacc0dedf2d7456bd790d0c0f9ef6210 (diff)
downloadgenenetwork3-e5bcb0faccf67f213538cad3670a8d1378c56ce7.tar.gz
Remove "/k-gwa-computation"
Diffstat (limited to 'gn3/api/gemma.py')
-rw-r--r--gn3/api/gemma.py58
1 files changed, 0 insertions, 58 deletions
diff --git a/gn3/api/gemma.py b/gn3/api/gemma.py
index ed698d3..21c4cf5 100644
--- a/gn3/api/gemma.py
+++ b/gn3/api/gemma.py
@@ -26,64 +26,6 @@ def get_version():
return jsonify(run_cmd(f"{gemma_cmd} -v | head -n 1"))
-# This is basically extracted from genenetwork2
-# wqflask/wqflask/marker_regression/gemma_ampping.py
-@gemma.route("/k-gwa-computation", methods=["POST"])
-def run_gemma():
- """Generates a command for generating K-Values and then later, generate a GWA
-command that contains markers. These commands are queued; and the expected
-file output is returned.
-
- """
- data = request.get_json()
- app_defaults = current_app.config
- __hash = generate_hash_of_string(f"{data.get('genofile_name')}_"
- ''.join(data.get("values", "")))
- gemma_kwargs = {
- "geno_filename":
- os.path.join(app_defaults.get("GENODIR"), "bimbam",
- f"{data.get('geno_filename')}"),
- "trait_filename":
- generate_pheno_txt_file(
- tmpdir=app_defaults.get("TMPDIR"),
- values=data.get("values"),
- # Generate this file on the fly!
- trait_filename=(f"{data.get('dataset_groupname')}_"
- f"{data.get('trait_name')}_"
- f"{__hash}.txt"))
- }
- gemma_wrapper_kwargs = {}
- if data.get("loco"):
- gemma_wrapper_kwargs["loco"] = f"--input {data.get('loco')}"
- k_computation_cmd = generate_gemma_computation_cmd(
- gemma_cmd=app_defaults.get("GEMMA_WRAPPER_CMD"),
- gemma_wrapper_kwargs={"loco": f"--input {data.get('loco')}"},
- gemma_kwargs=gemma_kwargs,
- output_file=(f"{app_defaults.get('TMPDIR')}/gn2/"
- f"{data.get('dataset_name')}_K_"
- f"{__hash}.json"))
- gemma_kwargs["lmm"] = data.get("lmm", 9)
- gemma_wrapper_kwargs["input"] = (f"{data.get('dataset_name')}_K_"
- f"{__hash}.json")
- gwa_cmd = generate_gemma_computation_cmd(
- gemma_wrapper_kwargs=gemma_wrapper_kwargs,
- gemma_cmd=app_defaults.get("GEMMA_WRAPPER_CMD"),
- gemma_kwargs=gemma_kwargs,
- output_file=(f"{data.get('dataset_name')}_GWA_"
- f"{__hash}.txt"))
- if not all([k_computation_cmd, gwa_cmd]):
- return jsonify(status=128,
- error="Unable to generate cmds for computation!"), 500
- return jsonify(unique_id=queue_cmd(
- conn=redis.Redis(),
- email=data.get("email"),
- job_queue=app_defaults.get("REDIS_JOB_QUEUE"),
- cmd=f"{k_computation_cmd} && {gwa_cmd}"),
- status="queued",
- output_file=(f"{data.get('dataset_name')}_GWA_"
- f"{__hash}.txt"))
-
-
@gemma.route("/status/<unique_id>", methods=["GET"])
def check_cmd_status(unique_id):
"""Given a (url-encoded) UNIQUE-ID which is returned when hitting any of the