aboutsummaryrefslogtreecommitdiff
path: root/bh20seqanalyzer/main.py
blob: 1a8965b4076b1b3934deb3f80da98b1442b0173e (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
import argparse
import arvados
import arvados.collection
import time
import subprocess
import tempfile
import json
import logging
import ruamel.yaml
from bh20sequploader.qc_metadata import qc_metadata

logging.basicConfig(format="[%(asctime)s] %(levelname)s %(message)s", datefmt="%Y-%m-%d %H:%M:%S",
                    level=logging.INFO)
logging.getLogger("googleapiclient.discovery").setLevel(logging.WARN)

def validate_upload(api, collection, validated_project,
                    fastq_project, fastq_workflow_uuid):
    col = arvados.collection.Collection(collection["uuid"])

    # validate the collection here.  Check metadata, etc.
    valid = True

    if "metadata.yaml" not in col:
        logging.warn("Upload '%s' missing metadata.yaml", collection["name"])
        valid = False
    else:
        metadata_content = ruamel.yaml.round_trip_load(col.open("metadata.yaml"))
        #valid = qc_metadata(metadata_content) and valid
        if not valid:
            logging.warn("Failed metadata qc")

    if valid:
        if "sequence.fasta" not in col:
            if "reads.fastq" in col:
                start_fastq_to_fasta(api, collection, fastq_project, fastq_workflow_uuid)
                return False
            else:
                valid = False
                logging.warn("Upload '%s' missing sequence.fasta", collection["name"])

    dup = api.collections().list(filters=[["owner_uuid", "=", validated_project],
                                          ["portable_data_hash", "=", col.portable_data_hash()]]).execute()
    if dup["items"]:
        # This exact collection has been uploaded before.
        valid = False
        logging.warn("Upload '%s' is duplicate" % collection["name"])

    if valid:
        logging.info("Added '%s' to validated sequences" % collection["name"])
        # Move it to the "validated" project to be included in the next analysis
        api.collections().update(uuid=collection["uuid"], body={
            "owner_uuid": validated_project,
            "name": "%s (%s)" % (collection["name"], time.asctime(time.gmtime()))}).execute()
    else:
        # It is invalid, delete it.
        logging.warn("Deleting '%s'" % collection["name"])
        api.collections().delete(uuid=collection["uuid"]).execute()

    return valid


def run_workflow(api, parent_project, workflow_uuid, name, inputobj):
    project = api.groups().create(body={
        "group_class": "project",
        "name": name,
        "owner_uuid": parent_project,
    }, ensure_unique_name=True).execute()

    with tempfile.NamedTemporaryFile() as tmp:
        tmp.write(json.dumps(inputobj, indent=2).encode('utf-8'))
        tmp.flush()
        cmd = ["arvados-cwl-runner",
               "--submit",
               "--no-wait",
               "--debug",
               "--project-uuid=%s" % project["uuid"],
               "arvwf:%s" % workflow_uuid,
               tmp.name]
        logging.info("Running %s" % ' '.join(cmd))
        comp = subprocess.run(cmd, capture_output=True)
    if comp.returncode != 0:
        logging.error(comp.stderr.decode('utf-8'))

    return project


def start_fastq_to_fasta(api, collection,
                         analysis_project,
                         fastq_workflow_uuid):
    newproject = run_workflow(api, analysis_project, fastq_workflow_uuid, "FASTQ to FASTA", {
        "fastq_forward": {
            "class": "File",
            "location": "keep:%s/reads.fastq" % collection["portable_data_hash"]
        },
        "metadata": {
            "class": "File",
            "location": "keep:%s/metadata.yaml" % collection["portable_data_hash"]
        },
        "ref_fasta": {
            "class": "File",
            "location": "keep:ffef6a3b77e5e04f8f62a7b6f67264d1+556/SARS-CoV2-NC_045512.2.fasta"
        }
    })
    api.collections().update(uuid=collection["uuid"],
                             body={"owner_uuid": newproject["uuid"]}).execute()

def start_pangenome_analysis(api,
                             analysis_project,
                             pangenome_workflow_uuid,
                             validated_project):
    validated = arvados.util.list_all(api.collections().list, filters=[["owner_uuid", "=", validated_project]])
    inputobj = {
        "inputReads": []
    }
    for v in validated:
        inputobj["inputReads"].append({
            "class": "File",
            "location": "keep:%s/sequence.fasta" % v["portable_data_hash"]
        })
    run_workflow(api, analysis_project, pangenome_workflow_uuid, "Pangenome analysis", inputobj)


def get_workflow_output_from_project(api, uuid):
    cr = api.container_requests().list(filters=[['owner_uuid', '=', uuid],
                                                ["requesting_container_uuid", "=", None]]).execute()
    if cr["items"] and cr["items"][0]["output_uuid"]:
        return cr["items"][0]
    else:
        return None


def copy_most_recent_result(api, analysis_project, latest_result_uuid):
    most_recent_analysis = api.groups().list(filters=[['owner_uuid', '=', analysis_project]],
                                                  order="created_at desc", limit=1).execute()
    for m in most_recent_analysis["items"]:
        wf = get_workflow_output_from_project(api, m["uuid"])
        if wf:
            src = api.collections().get(uuid=wf["output_uuid"]).execute()
            dst = api.collections().get(uuid=latest_result_uuid).execute()
            if src["portable_data_hash"] != dst["portable_data_hash"]:
                logging.info("Copying latest result from '%s' to %s", m["name"], latest_result_uuid)
                api.collections().update(uuid=latest_result_uuid,
                                         body={"manifest_text": src["manifest_text"],
                                               "description": "Result from %s %s" % (m["name"], wf["uuid"])}).execute()
            break


def move_fastq_to_fasta_results(api, analysis_project, uploader_project):
    projects = api.groups().list(filters=[['owner_uuid', '=', analysis_project],
                                          ["properties.moved_output", "!=", True]],
                                 order="created_at desc",).execute()
    for p in projects["items"]:
        wf = get_workflow_output_from_project(api, p["uuid"])
        if wf:
            logging.info("Moving completed fastq2fasta result %s back to uploader project", wf["output_uuid"])
            api.collections().update(uuid=wf["output_uuid"],
                                     body={"owner_uuid": uploader_project}).execute()
            p["properties"]["moved_output"] = True
            api.groups().update(uuid=p["uuid"], body={"properties": p["properties"]}).execute()


def main():
    parser = argparse.ArgumentParser(description='Analyze collections uploaded to a project')
    parser.add_argument('--uploader-project', type=str, default='lugli-j7d0g-n5clictpuvwk8aa', help='')
    parser.add_argument('--pangenome-analysis-project', type=str, default='lugli-j7d0g-y4k4uswcqi3ku56', help='')
    parser.add_argument('--fastq-project', type=str, default='lugli-j7d0g-xcjxp4oox2u1w8u', help='')
    parser.add_argument('--validated-project', type=str, default='lugli-j7d0g-5ct8p1i1wrgyjvp', help='')

    parser.add_argument('--pangenome-workflow-uuid', type=str, default='lugli-7fd4e-mqfu9y3ofnpnho1', help='')
    parser.add_argument('--fastq-workflow-uuid', type=str, default='lugli-7fd4e-2zp9q4jo5xpif9y', help='')

    parser.add_argument('--latest-result-collection', type=str, default='lugli-4zz18-z513nlpqm03hpca', help='')
    args = parser.parse_args()

    api = arvados.api()

    logging.info("Starting up, monitoring %s for uploads" % (args.uploader_project))

    while True:
        move_fastq_to_fasta_results(api, args.fastq_project, args.uploader_project)

        new_collections = api.collections().list(filters=[['owner_uuid', '=', args.uploader_project]]).execute()
        at_least_one_new_valid_seq = False
        for c in new_collections["items"]:
            at_least_one_new_valid_seq = validate_upload(api, c,
                                                         args.validated_project,
                                                         args.fastq_project,
                                                         args.fastq_workflow_uuid) or at_least_one_new_valid_seq

        if at_least_one_new_valid_seq:
            start_pangenome_analysis(api,
                                     args.pangenome_analysis_project,
                                     args.pangenome_workflow_uuid,
                                     args.validated_project)

        copy_most_recent_result(api,
                                args.pangenome_analysis_project,
                                args.latest_result_collection)

        time.sleep(15)