def run_single(self, reads_ref, params):
"""
Performs a single run of HISAT2 against a single reads reference. The rest of the info
is taken from the params dict - see the spec for details.
"""
# 1. Get hisat2 index from genome.
# a. If it exists in cache, use that.
# b. Otherwise, build it
idx_prefix = self.build_index(params["genome_ref"])
# 2. Fetch the reads file and deal make sure input params are correct.
reads = fetch_reads_from_reference(reads_ref["ref"], self.callback_url)
# if the reads ref came from a different sample set, then we need to drop that
# reference inside the reads info object so it can be linked in the alignment
if reads_ref["ref"] != params["sampleset_ref"]:
reads["sampleset_ref"] = params["sampleset_ref"]
# make sure condition info carries over if we have it
if "condition" in reads_ref:
reads["condition"] = reads_ref["condition"]
elif "condition" in params:
reads["condition"] = params["condition"]
reads["name"] = reads_ref["name"]
output_file = "accepted_hits"
# 3. Finally all set, do the alignment and upload the output.
alignment_file = self.run_hisat2(idx_prefix,
reads,
params,
output_file=output_file)
alignment_name = reads["name"] + params["alignment_suffix"]
output_ref = self.upload_alignment(params, reads, alignment_name,
alignment_file)
alignment_set_ref = None
if is_set(params["sampleset_ref"], self.workspace_url):
# alignment_items, alignmentset_name, ws_name
set_name = get_object_names(
[params["sampleset_ref"]],
self.workspace_url)[params["sampleset_ref"]]
alignment_set_name = set_name + params["alignmentset_suffix"]
alignment_set_ref = self.upload_alignment_set(
[{
"ref": output_ref,
"label": reads["condition"]
}], alignment_set_name, params["ws_name"])
alignments = dict()
alignments[reads_ref["ref"]] = {
"ref": output_ref,
"name": alignment_name
}
os.remove(reads["file_fwd"])
if "file_rev" in reads:
os.remove(reads["file_rev"])
return (alignments, output_ref, alignment_set_ref)
def run_batch(self, reads_refs, params):
"""
Runs HISAT2 in batch mode.
reads_refs should be a list of dicts, where each looks like the following:
{
"ref": reads object reference,
"condition": condition for that ref (string)
}
"""
# build task list and send it to KBParallel
tasks = list()
set_name = get_object_names(
[params["sampleset_ref"]],
self.workspace_url)[params["sampleset_ref"]]
for idx, reads_ref in enumerate(reads_refs):
single_param = dict(params) # need a copy of the params
single_param["build_report"] = 0
single_param["sampleset_ref"] = reads_ref["ref"]
if "condition" in reads_ref:
single_param["condition"] = reads_ref["condition"]
else:
single_param["condition"] = "unspecified"
tasks.append({
"module_name": "kb_hisat2",
"function_name": "run_hisat2",
"version": self.my_version,
"parameters": single_param
})
# UNCOMMENT BELOW FOR LOCAL TESTING
batch_run_params = {
"tasks": tasks,
"runner": "parallel",
# "concurrent_local_tasks": 3,
# "concurrent_njsw_tasks": 0,
"max_retries": 2
}
parallel_runner = KBParallel(self.callback_url)
results = parallel_runner.run_batch(batch_run_params)["results"]
alignment_items = list()
alignments = dict()
for idx, result in enumerate(results):
# idx of the result is the same as the idx of the inputs AND reads_refs
if result["is_error"] != 0:
raise RuntimeError(
"Failed a parallel run of HISAT2! {}".format(
result["result_package"]["error"]))
reads_ref = tasks[idx]["parameters"]["sampleset_ref"]
alignment_items.append({
"ref":
result["result_package"]["result"][0]["alignment_objs"]
[reads_ref]["ref"],
"label":
reads_refs[idx].get("condition",
params.get("condition", "unspecified"))
})
alignments[reads_ref] = result["result_package"]["result"][0][
"alignment_objs"][reads_ref]
# build the final alignment set
output_ref = self.upload_alignment_set(
alignment_items, set_name + params["alignmentset_suffix"],
params["ws_name"])
return (alignments, output_ref)