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"""Endpoints for running the gemma cmd"""
import os
import redis
from flask import Blueprint
from flask import current_app
from flask import jsonify
from flask import request
from gn3.commands import queue_cmd
from gn3.commands import run_cmd
from gn3.fs_helpers import cache_ipfs_file
from gn3.fs_helpers import jsonfile_to_dict, assert_paths_exist
from gn3.computations.gemma import generate_gemma_cmd
from gn3.computations.gemma import assert_paths_exist
gemma = Blueprint("gemma", __name__)
@gemma.route("/version")
def get_version():
"""Display the installed version of gemma-wrapper"""
gemma_cmd = current_app.config["GEMMA_WRAPPER_CMD"]
return jsonify(run_cmd(f"{gemma_cmd} -v | head -n 1"))
@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
gemma endpoints, return the status of the command
"""
status = redis.Redis().hget(name=unique_id, key="status")
if not status:
return jsonify(status=128,
error="The unique id you used does not exist!"), 500
return jsonify(status=status.decode("utf-8"))
@gemma.route("/k-compute/<token>", methods=["POST"])
def compute_k(token):
"""Given a genofile, traitfile, snpsfile, and the token, compute the k-valuen
and return <hash-of-inputs>.json with a UNIQUE-ID of the job. The genofile,
traitfile, and snpsfile are extracted from a metadata.json file.
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR'))
assert_paths_exist([genofile, phenofile, snpsfile])
gemma_kwargs = {"g": genofile, "p": phenofile, "a": snpsfile}
results = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs)
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=results.get("gemma_cmd")),
status="queued",
output_file=results.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/k-compute/loco/<chromosomes>/<token>", methods=["POST"])
def compute_k_loco(chromosomes, token):
"""Similar to 'compute_k' with the extra option of using loco given chromosome
values.
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
assert_paths_exist([genofile, phenofile, snpsfile])
gemma_kwargs = {"g": genofile, "p": phenofile, "a": snpsfile}
results = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
chromosomes=chromosomes)
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=results.get("gemma_cmd")),
status="queued",
output_file=results.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/gwa-compute/<k_filename>/<token>", methods=["POST"])
def compute_gwa(k_filename, token):
"""Compute GWA values. No loco no covariates provided.
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
gemma_kwargs = {
"g": genofile,
"p": phenofile,
"a": snpsfile,
"lmm": _dict.get("lmm", 9)
}
results = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"input": os.path.join(working_dir, k_filename)
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=results.get("gemma_cmd")),
status="queued",
output_file=results.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/gwa-compute/covars/<k_filename>/<token>", methods=["POST"])
def compute_gwa_with_covar(k_filename, token):
"""Compute GWA values. No Loco; Covariates provided.
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile, covarfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps", "covar"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
gemma_kwargs = {
"g": genofile,
"p": phenofile,
"a": snpsfile,
"c": covarfile,
"lmm": _dict.get("lmm", 9)
}
results = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"input": os.path.join(working_dir, k_filename)
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=results.get("gemma_cmd")),
status="queued",
output_file=results.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/gwa-compute/<k_filename>/loco/maf/<maf>/<token>",
methods=["POST"])
def compute_gwa_with_loco_maf(k_filename, maf, token):
"""Compute GWA values. No Covariates provided. Only loco and maf vals given.
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
assert_paths_exist([genofile, phenofile, snpsfile])
gemma_kwargs = {
"g": genofile,
"p": phenofile,
"a": snpsfile,
"lmm": _dict.get("lmm", 9),
'maf': float(maf)
}
results = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"loco": f"--input {os.path.join(working_dir, k_filename)}"
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=results.get("gemma_cmd")),
status="queued",
output_file=results.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/gwa-compute/<k_filename>/loco/covars/maf/<maf>/<token>",
methods=["POST"])
def compute_gwa_with_loco_covar(k_filename, maf, token):
"""Compute GWA values. No Covariates provided. Only loco and maf vals given.
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile, covarfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps", "covar"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
assert_paths_exist([genofile, phenofile, snpsfile, covarfile])
gemma_kwargs = {
"g": genofile,
"p": phenofile,
"a": snpsfile,
"c": covarfile,
"lmm": _dict.get("lmm", 9),
"maf": float(maf)
}
results = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"loco": f"--input {os.path.join(working_dir, k_filename)}"
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=results.get("gemma_cmd")),
status="queued",
output_file=results.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/k-gwa-compute/<token>", methods=["POST"])
def compute_k_gwa(token):
"""Given a genofile, traitfile, snpsfile, and the token, compute the k-values
and return <hash-of-inputs>.json with a UNIQUE-ID of the job. The genofile,
traitfile, and snpsfile are extracted from a metadata.json file. No Loco no
covars; lmm defaults to 9!
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
assert_paths_exist([genofile, phenofile, snpsfile])
gemma_kwargs = {"g": genofile, "p": phenofile, "a": snpsfile}
gemma_k_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs)
gemma_kwargs["lmm"] = _dict.get("lmm", 9)
gemma_gwa_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"input": os.path.join(working_dir,
gemma_k_cmd.get("output_file"))
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=(f"{gemma_k_cmd.get('gemma_cmd')} && "
f"{gemma_gwa_cmd.get('gemma_cmd')}")),
status="queued",
output_file=gemma_gwa_cmd.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/k-gwa-compute/covars/<token>", methods=["POST"])
def compute_k_gwa_with_covars_only(token):
"""Given a genofile, traitfile, snpsfile, and the token, compute the k-values
and return <hash-of-inputs>.json with a UNIQUE-ID of the job. The genofile,
traitfile, and snpsfile are extracted from a metadata.json file. No Loco no
covars; lmm defaults to 9!
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile, covarfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps", "covar"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
assert_paths_exist([genofile, phenofile, snpsfile])
gemma_kwargs = {"g": genofile, "p": phenofile, "a": snpsfile}
gemma_k_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs)
gemma_kwargs["c"] = covarfile
gemma_kwargs["lmm"] = _dict.get("lmm", 9)
gemma_gwa_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"input": os.path.join(working_dir,
gemma_k_cmd.get("output_file"))
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=(f"{gemma_k_cmd.get('gemma_cmd')} && "
f"{gemma_gwa_cmd.get('gemma_cmd')}")),
status="queued",
output_file=gemma_gwa_cmd.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/k-gwa-compute/loco/<chromosomes>/maf/<maf>/<token>",
methods=["POST"])
def compute_k_gwa_with_loco_only(chromosomes, maf, token):
"""k-gwa-compute; Loco no covars; lmm defaults to 9!
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
assert_paths_exist([genofile, phenofile, snpsfile])
gemma_kwargs = {"g": genofile, "p": phenofile, "a": snpsfile}
gemma_k_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
chromosomes=chromosomes)
gemma_kwargs["maf"] = float(maf)
gemma_kwargs["lmm"] = _dict.get("lmm", 9)
gemma_gwa_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"loco":
("--input "
f"{os.path.join(working_dir, gemma_k_cmd.get('output_file'))}"
)
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=(f"{gemma_k_cmd.get('gemma_cmd')} && "
f"{gemma_gwa_cmd.get('gemma_cmd')}")),
status="queued",
output_file=gemma_gwa_cmd.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
@gemma.route("/k-gwa-compute/covars/loco/<chromosomes>/maf/<maf>/<token>",
methods=["POST"])
def compute_k_gwa_with_loco_and_cavar(chromosomes, maf, token):
"""k-gwa-compute; Loco with covars; lmm defaults to 9!
"""
working_dir = os.path.join(current_app.config.get("TMPDIR"), token)
_dict = jsonfile_to_dict(os.path.join(working_dir, "metadata.json"))
try:
phenofile, snpsfile, covarfile = [
os.path.join(working_dir, _dict.get(x))
for x in ["pheno", "snps", "covar"]
]
genofile = cache_ipfs_file(
ipfs_file=_dict.get("geno"),
cache_dir=current_app.config.get('CACHEDIR')
)
assert_paths_exist([genofile, phenofile, snpsfile])
gemma_kwargs = {"g": genofile, "p": phenofile, "a": snpsfile}
gemma_k_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
chromosomes=chromosomes)
gemma_kwargs["c"] = covarfile
gemma_kwargs["maf"] = float(maf)
gemma_kwargs["lmm"] = _dict.get("lmm", 9)
gemma_gwa_cmd = generate_gemma_cmd(
gemma_cmd=current_app.config.get("GEMMA_"
"WRAPPER_CMD"),
output_dir=current_app.config.get('TMPDIR'),
token=token,
gemma_kwargs=gemma_kwargs,
gemma_wrapper_kwargs={
"loco":
("--input "
f"{os.path.join(working_dir, gemma_k_cmd.get('output_file'))}"
)
})
return jsonify(
unique_id=queue_cmd(
conn=redis.Redis(),
email=(request.get_json() or {}).get('email'),
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
cmd=(f"{gemma_k_cmd.get('gemma_cmd')} && "
f"{gemma_gwa_cmd.get('gemma_cmd')}")),
status="queued",
output_file=gemma_gwa_cmd.get("output_file"))
# pylint: disable=W0703
except Exception:
return jsonify(
status=128,
# use better message
message="Metadata file non-existent!")
|
