Refactor analysis code into a class

Arvados-DCO-1.1-Signed-off-by: Peter Amstutz <peter.amstutz@curii.com>

1 files changed, 309 insertions, 288 deletions

diff --git a/bh20seqanalyzer/main.py b/bh20seqanalyzer/main.py
index 0b52e6b..f2bb234 100644
--- a/bh20seqanalyzer/main.py
+++ b/bh20seqanalyzer/main.py
@@ -16,277 +16,306 @@ logging.basicConfig(format="[%(asctime)s] %(levelname)s %(message)s", datefmt="%
                     level=logging.INFO)
 logging.getLogger("googleapiclient.discovery").setLevel(logging.WARN)
 
-def validate_upload(api, collection, validated_project,
-                    fastq_project, fastq_workflow_uuid,
-                    revalidate):
-    col = arvados.collection.Collection(collection["uuid"])
-
-    if not revalidate and collection["properties"].get("status") in ("validated", "rejected"):
-        return False
-
-    # validate the collection here.  Check metadata, etc.
-    logging.info("Validating upload '%s' (%s)" % (collection["name"], collection["uuid"]))
-
-    errors = []
-
-    if collection["owner_uuid"] != validated_project:
-        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.
-            errors.append("Duplicate of %s" % ([d["uuid"] for d in dup["items"]]))
-
-    if not errors:
-        if "metadata.yaml" not in col:
-            errors.append("Missing metadata.yaml", collection["name"])
-        else:
+class SeqAnalyzer:
+
+    def __init__(self, api, keepclient,
+                 uploader_project,
+                 pangenome_analysis_project,
+                 fastq_project,
+                 validated_project,
+                 workflow_def_project,
+                 pangenome_workflow_uuid,
+                 fastq_workflow_uuid,
+                 exclude_list,
+                 latest_result_collection):
+        self.api = api
+        self.keepclient = keepclient
+        self.uploader_project = uploader_project
+        self.pangenome_analysis_project = pangenome_analysis_project
+        self.fastq_project = fastq_project
+        self.validated_project = validated_project
+        self.workflow_def_project = workflow_def_project
+        self.pangenome_workflow_uuid = pangenome_workflow_uuid
+        self.fastq_workflow_uuid = fastq_workflow_uuid
+        self.exclude_list = exclude_list
+        self.latest_result_uuid = latest_result_collection
+        self.schema_ref = None
+
+    def validate_upload(self, collection, revalidate):
+        col = arvados.collection.Collection(collection["uuid"], api_client=self.api, keep_client=self.keepclient)
+
+        if not revalidate and collection["properties"].get("status") in ("validated", "rejected"):
+            return False
+
+        # validate the collection here.  Check metadata, etc.
+        logging.info("Validating upload '%s' (%s)" % (collection["name"], collection["uuid"]))
+
+        errors = []
+
+        if collection["owner_uuid"] != self.validated_project:
+            dup = self.api.collections().list(filters=[["owner_uuid", "=", self.validated_project],
+                                                  ["portable_data_hash", "=", col.portable_data_hash()]]).execute()
+            if dup["items"]:
+                # This exact collection has been uploaded before.
+                errors.append("Duplicate of %s" % ([d["uuid"] for d in dup["items"]]))
+
+        if not errors:
+            if "metadata.yaml" not in col:
+                errors.append("Missing metadata.yaml", collection["name"])
+            else:
+                try:
+                    with col.open("metadata.yaml") as md:
+                        metadata_content = ruamel.yaml.round_trip_load(md)
+                    metadata_content["id"] = "http://arvados.org/keep:%s/metadata.yaml" % collection["portable_data_hash"]
+                    sample_id = metadata_content["sample"]["sample_id"]
+                    add_lc_filename(metadata_content, metadata_content["id"])
+                    valid = qc_metadata(metadata_content)
+                    if not valid:
+                        errors.append("Failed metadata qc")
+                except Exception as e:
+                    errors.append(str(e))
+
+        if not errors:
             try:
-                metadata_content = ruamel.yaml.round_trip_load(col.open("metadata.yaml"))
-                metadata_content["id"] = "http://arvados.org/keep:%s/metadata.yaml" % collection["portable_data_hash"]
-                sample_id = metadata_content["sample"]["sample_id"]
-                add_lc_filename(metadata_content, metadata_content["id"])
-                valid = qc_metadata(metadata_content)
-                if not valid:
-                    errors.append("Failed metadata qc")
-            except Exception as e:
-                errors.append(str(e))
-
-    if not errors:
-        try:
-            tgt = None
-            paired = {"reads_1.fastq": "reads.fastq", "reads_1.fastq.gz": "reads.fastq.gz"}
-            for n in ("sequence.fasta", "reads.fastq", "reads.fastq.gz", "reads_1.fastq", "reads_1.fastq.gz"):
-                if n not in col:
-                    continue
-                with col.open(n, 'rb') as qf:
-                    tgt = qc_fasta(qf)[0]
-                    if tgt != n and tgt != paired.get(n):
-                        errors.append("Expected %s but magic says it should be %s", n, tgt)
-                    elif tgt in ("reads.fastq", "reads.fastq.gz", "reads_1.fastq", "reads_1.fastq.gz"):
-                        start_fastq_to_fasta(api, collection, fastq_project, fastq_workflow_uuid, n, sample_id)
-                        return False
-            if tgt is None:
-                errors.append("Upload '%s' does not contain sequence.fasta, reads.fastq or reads_1.fastq", collection["name"])
-        except Exception as v:
-            errors.append(str(v))
-
-
-    if not errors:
-        # Move it to the "validated" project to be included in the next analysis
-        if "errors" in collection["properties"]:
-            del collection["properties"]["errors"]
-        collection["properties"]["status"] = "validated"
-        api.collections().update(uuid=collection["uuid"], body={
-            "owner_uuid": validated_project,
-            "name": "%s (%s)" % (collection["name"], time.asctime(time.gmtime())),
-            "properties": collection["properties"]}).execute()
-        logging.info("Added '%s' to validated sequences" % collection["name"])
-        return True
-    else:
-        # It is invalid
-        logging.warn("'%s' (%s) has validation errors: %s" % (
-            collection["name"], collection["uuid"], "\n".join(errors)))
-        collection["properties"]["status"] = "rejected"
-        collection["properties"]["errors"] = errors
-        api.collections().update(uuid=collection["uuid"], body={"properties": collection["properties"]}).execute()
-        return False
-
-
-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",
-               "--project-uuid=%s" % project["uuid"],
-               "arvwf:%s" % workflow_uuid,
-               tmp.name]
-        logging.info("Running %s" % ' '.join(cmd))
-        comp = subprocess.run(cmd, capture_output=True)
-    logging.info("Submitted %s", comp.stdout)
-    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,
-                         tgt,
-                         sample_id):
-
-    params = {
-        "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"
-        },
-        "sample_id": sample_id
-    }
-
-    if tgt.startswith("reads.fastq"):
-        params["fastq_forward"] = {
-            "class": "File",
-            "location": "keep:%s/%s" % (collection["portable_data_hash"], tgt)
-        }
-    elif tgt.startswith("reads_1.fastq"):
-        params["fastq_forward"] = {
-            "class": "File",
-            "location": "keep:%s/reads_1.%s" % (collection["portable_data_hash"], tgt[8:])
-        }
-        params["fastq_reverse"] = {
-            "class": "File",
-            "location": "keep:%s/reads_2.%s" % (collection["portable_data_hash"], tgt[8:])
+                tgt = None
+                paired = {"reads_1.fastq": "reads.fastq", "reads_1.fastq.gz": "reads.fastq.gz"}
+                for n in ("sequence.fasta", "reads.fastq", "reads.fastq.gz", "reads_1.fastq", "reads_1.fastq.gz"):
+                    if n not in col:
+                        continue
+                    with col.open(n, 'rb') as qf:
+                        tgt = qc_fasta(qf)[0]
+                        if tgt != n and tgt != paired.get(n):
+                            errors.append("Expected %s but magic says it should be %s", n, tgt)
+                        elif tgt in ("reads.fastq", "reads.fastq.gz", "reads_1.fastq", "reads_1.fastq.gz"):
+                            self.start_fastq_to_fasta(collection, n, sample_id)
+                            return False
+                if tgt is None:
+                    errors.append("Upload '%s' does not contain sequence.fasta, reads.fastq or reads_1.fastq", collection["name"])
+            except Exception as v:
+                errors.append(str(v))
+
+
+        if not errors:
+            # Move it to the "validated" project to be included in the next analysis
+            if "errors" in collection["properties"]:
+                del collection["properties"]["errors"]
+            collection["properties"]["status"] = "validated"
+            self.api.collections().update(uuid=collection["uuid"], body={
+                "owner_uuid": self.validated_project,
+                "name": "%s (%s)" % (collection["name"], time.asctime(time.gmtime())),
+                "properties": collection["properties"]}).execute()
+            logging.info("Added '%s' to validated sequences" % collection["name"])
+            return True
+        else:
+            # It is invalid
+            logging.warn("'%s' (%s) has validation errors: %s" % (
+                collection["name"], collection["uuid"], "\n".join(errors)))
+            collection["properties"]["status"] = "rejected"
+            collection["properties"]["errors"] = errors
+            self.api.collections().update(uuid=collection["uuid"], body={"properties": collection["properties"]}).execute()
+            return False
+
+
+    def run_workflow(self, parent_project, workflow_uuid, name, inputobj):
+        project = self.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",
+                   "--project-uuid=%s" % project["uuid"],
+                   "arvwf:%s" % workflow_uuid,
+                   tmp.name]
+            logging.info("Running %s" % ' '.join(cmd))
+            comp = subprocess.run(cmd, capture_output=True)
+        logging.info("Submitted %s", comp.stdout)
+        if comp.returncode != 0:
+            logging.error(comp.stderr.decode('utf-8'))
+
+        return project
+
+
+    def start_fastq_to_fasta(self, collection,
+                             tgt,
+                             sample_id):
+
+        params = {
+            "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"
+            },
+            "sample_id": sample_id
         }
 
-    newproject = run_workflow(api, analysis_project, fastq_workflow_uuid, "FASTQ to FASTA", params)
-    api.collections().update(uuid=collection["uuid"],
-                             body={"owner_uuid": newproject["uuid"]}).execute()
-
-def start_pangenome_analysis(api,
-                             analysis_project,
-                             pangenome_workflow_uuid,
-                             validated_project,
-                             schema_ref,
-                             exclude_list):
-    validated = arvados.util.list_all(api.collections().list, filters=[
-        ["owner_uuid", "=", validated_project],
-        ["properties.status", "=", "validated"]])
-    inputobj = {
-        "inputReads": [],
-        "metadata": [],
-        "subjects": [],
-        "metadataSchema": {
-            "class": "File",
-            "location": schema_ref
-        },
-        "exclude": {
-            "class": "File",
-            "location": exclude_list
+        if tgt.startswith("reads.fastq"):
+            params["fastq_forward"] = {
+                "class": "File",
+                "location": "keep:%s/%s" % (collection["portable_data_hash"], tgt)
+            }
+        elif tgt.startswith("reads_1.fastq"):
+            params["fastq_forward"] = {
+                "class": "File",
+                "location": "keep:%s/reads_1.%s" % (collection["portable_data_hash"], tgt[8:])
+            }
+            params["fastq_reverse"] = {
+                "class": "File",
+                "location": "keep:%s/reads_2.%s" % (collection["portable_data_hash"], tgt[8:])
+            }
+
+        newproject = self.run_workflow(self.fastq_project, self.fastq_workflow_uuid, "FASTQ to FASTA", params)
+        self.api.collections().update(uuid=collection["uuid"],
+                                 body={"owner_uuid": newproject["uuid"]}).execute()
+
+    def start_pangenome_analysis(self):
+
+        if self.schema_ref is None:
+            self.upload_schema()
+
+        validated = arvados.util.list_all(self.api.collections().list, filters=[
+            ["owner_uuid", "=", self.validated_project],
+            ["properties.status", "=", "validated"]])
+        inputobj = {
+            "inputReads": [],
+            "metadata": [],
+            "subjects": [],
+            "metadataSchema": {
+                "class": "File",
+                "location": self.schema_ref
+            },
+            "exclude": {
+                "class": "File",
+                "location": self.exclude_list
+            }
         }
-    }
-    validated.sort(key=lambda v: v["portable_data_hash"])
-    for v in validated:
-        inputobj["inputReads"].append({
-            "class": "File",
-            "location": "keep:%s/sequence.fasta" % v["portable_data_hash"]
-        })
-        inputobj["metadata"].append({
-            "class": "File",
-            "location": "keep:%s/metadata.yaml" % v["portable_data_hash"]
-        })
-        inputobj["subjects"].append("http://collections.lugli.arvadosapi.com/c=%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"]:
-        container = api.containers().get(uuid=cr["items"][0]["container_uuid"]).execute()
-        if container["state"] == "Complete" and container["exit_code"] == 0:
-            return cr["items"][0]
-    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").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
-
+        validated.sort(key=lambda v: v["portable_data_hash"])
+        for v in validated:
+            inputobj["inputReads"].append({
+                "class": "File",
+                "location": "keep:%s/sequence.fasta" % v["portable_data_hash"]
+            })
+            inputobj["metadata"].append({
+                "class": "File",
+                "location": "keep:%s/metadata.yaml" % v["portable_data_hash"]
+            })
+            inputobj["subjects"].append("http://collections.lugli.arvadosapi.com/c=%s/sequence.fasta" % v["portable_data_hash"])
+        self.run_workflow(self.pangenome_analysis_project, self.pangenome_workflow_uuid, "Pangenome analysis", inputobj)
+
+
+    def get_workflow_output_from_project(self, uuid):
+        cr = self.api.container_requests().list(filters=[['owner_uuid', '=', uuid],
+                                                    ["requesting_container_uuid", "=", None]]).execute()
+        if cr["items"] and cr["items"][0]["output_uuid"]:
+            container = self.api.containers().get(uuid=cr["items"][0]["container_uuid"]).execute()
+            if container["state"] == "Complete" and container["exit_code"] == 0:
+                return cr["items"][0]
+        return None
+
+
+    def copy_most_recent_result(self):
+        most_recent_analysis = self.api.groups().list(filters=[['owner_uuid', '=', self.pangenome_analysis_project]],
+                                                      order="created_at desc").execute()
+        for m in most_recent_analysis["items"]:
+            wf = self.get_workflow_output_from_project(m["uuid"])
+            if wf:
+                src = self.api.collections().get(uuid=wf["output_uuid"]).execute()
+                dst = self.api.collections().get(uuid=self.latest_result_uuid).execute()
+                if src["portable_data_hash"] != dst["portable_data_hash"]:
+                    logging.info("Copying latest result from '%s' to %s", m["name"], self.latest_result_uuid)
+                    self.api.collections().update(uuid=self.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(self):
+        projects = self.api.groups().list(filters=[['owner_uuid', '=', self.fastq_project],
+                                              ["properties.moved_output", "!=", True]],
+                                     order="created_at desc",).execute()
+        for p in projects["items"]:
+            wf = self.get_workflow_output_from_project(p["uuid"])
+            if not wf:
+                continue
 
-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()
+            self.api.collections().update(uuid=wf["output_uuid"],
+                                     body={"owner_uuid": self.uploader_project}).execute()
+
+            col = arvados.collection.Collection(wf["output_uuid"], api_client=self.api, keep_client=self.keepclient)
+            with col.open("metadata.yaml") as md:
+                metadata_content = ruamel.yaml.round_trip_load(md)
+
             p["properties"]["moved_output"] = True
-            api.groups().update(uuid=p["uuid"], body={"properties": p["properties"]}).execute()
+            p["properties"]["sequence_label"] = metadata_content["sample"]["sample_id"]
+            self.api.groups().update(uuid=p["uuid"], body={"properties": p["properties"]}).execute()
             break
 
 
-def upload_schema(api, workflow_def_project):
-    schema_resource = pkg_resources.resource_stream('bh20sequploader.qc_metadata', "bh20seq-schema.yml")
-    c = arvados.collection.Collection()
-    with c.open("schema.yml", "wb") as f:
-        f.write(schema_resource.read())
-    pdh = c.portable_data_hash()
-    wd = api.collections().list(filters=[["owner_uuid", "=", workflow_def_project],
-                                         ["portable_data_hash", "=", pdh]]).execute()
-    if len(wd["items"]) == 0:
-        c.save_new(owner_uuid=workflow_def_project, name="Metadata schema", ensure_unique_name=True)
-    return "keep:%s/schema.yml" % pdh
-
-
-def print_status(api, uploader_project, fmt):
-    pending = arvados.util.list_all(api.collections().list, filters=[["owner_uuid", "=", uploader_project]])
-    out = []
-    status = {}
-    for p in pending:
-        prop = p["properties"]
-        out.append(prop)
-        if "status" not in prop:
-            prop["status"] = "pending"
-        prop["created_at"] = p["created_at"]
-        prop["uuid"] = p["uuid"]
-        status[prop["status"]] = status.get(prop["status"], 0) + 1
-    if fmt == "html":
-        print(
-"""
-<html>
-<body>
-""")
-        print("<p>Total collections in upload project %s</p>" % len(out))
-        print("<p>Status %s</p>" % status)
-        print(
-"""
-<table>
-<tr><th>Collection</th>
-<th>Sequence label</th>
-<th>Status</th>
-<th>Errors</th></tr>
-""")
-        for r in out:
-            print("<tr valign='top'>")
-            print("<td><a href='https://workbench.lugli.arvadosapi.com/collections/%s'>%s</a></td>" % (r["uuid"], r["uuid"]))
-            print("<td>%s</td>" % r["sequence_label"])
-            print("<td>%s</td>" % r["status"])
-            print("<td><pre>%s</pre></td>" % "\n".join(r.get("errors", [])))
-            print("</tr>")
-        print(
-"""
-</table>
-</body>
-</html>
-""")
-    else:
-        print(json.dumps(out, indent=2))
+    def upload_schema(self):
+        schema_resource = pkg_resources.resource_stream('bh20sequploader.qc_metadata', "bh20seq-schema.yml")
+        c = arvados.collection.Collection(api_client=self.api, keep_client=self.keepclient)
+        with c.open("schema.yml", "wb") as f:
+            f.write(schema_resource.read())
+        pdh = c.portable_data_hash()
+        wd = self.api.collections().list(filters=[["owner_uuid", "=", self.workflow_def_project],
+                                             ["portable_data_hash", "=", pdh]]).execute()
+        if len(wd["items"]) == 0:
+            c.save_new(owner_uuid=self.workflow_def_project, name="Metadata schema", ensure_unique_name=True)
+        self.schema_ref = "keep:%s/schema.yml" % pdh
+
+
+    def print_status(self, fmt):
+        pending = arvados.util.list_all(self.api.collections().list, filters=[["owner_uuid", "=", self.uploader_project]])
+        out = []
+        status = {}
+        for p in pending:
+            prop = p["properties"]
+            out.append(prop)
+            if "status" not in prop:
+                prop["status"] = "pending"
+            prop["created_at"] = p["created_at"]
+            prop["uuid"] = p["uuid"]
+            status[prop["status"]] = status.get(prop["status"], 0) + 1
+        if fmt == "html":
+            print(
+    """
+    <html>
+    <body>
+    """)
+            print("<p>Total collections in upload project %s</p>" % len(out))
+            print("<p>Status %s</p>" % status)
+            print(
+    """
+    <table>
+    <tr><th>Collection</th>
+    <th>Sequence label</th>
+    <th>Status</th>
+    <th>Errors</th></tr>
+    """)
+            for r in out:
+                print("<tr valign='top'>")
+                print("<td><a href='https://workbench.lugli.arvadosapi.com/collections/%s'>%s</a></td>" % (r["uuid"], r["uuid"]))
+                print("<td>%s</td>" % r["sequence_label"])
+                print("<td>%s</td>" % r["status"])
+                print("<td><pre>%s</pre></td>" % "\n".join(r.get("errors", [])))
+                print("</tr>")
+            print(
+    """
+    </table>
+    </body>
+    </html>
+    """)
+        else:
+            print(json.dumps(out, indent=2))
 
 def main():
     parser = argparse.ArgumentParser(description='Analyze collections uploaded to a project')
@@ -310,50 +339,42 @@ def main():
     args = parser.parse_args()
 
     api = arvados.api()
-
-
-
-    schema_ref = upload_schema(api, args.workflow_def_project)
+    keepclient = arvados.keep.KeepClient(api_client=api)
+
+    seqanalyzer = SeqAnalyzer(api, keepclient,
+                              args.uploader_project,
+                              args.pangenome_analysis_project,
+                              args.fastq_project,
+                              args.validated_project,
+                              args.workflow_def_project,
+                              args.pangenome_workflow_uuid,
+                              args.fastq_workflow_uuid,
+                              args.exclude_list,
+                              args.latest_result_collection)
 
     if args.kickoff:
         logging.info("Starting a single analysis run")
-        start_pangenome_analysis(api,
-                                 args.pangenome_analysis_project,
-                                 args.pangenome_workflow_uuid,
-                                 args.validated_project,
-                                 schema_ref,
-                                 args.exclude_list)
+        seqanalyzer.start_pangenome_analysis()
         return
 
     if args.print_status:
-        print_status(api, args.uploader_project, args.print_status)
+        seqanalyzer.print_status(args.print_status)
         exit(0)
 
     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)
+        seqanalyzer.move_fastq_to_fasta_results()
 
         new_collections = arvados.util.list_all(api.collections().list, filters=[["owner_uuid", "=", args.uploader_project]])
         at_least_one_new_valid_seq = False
         for c in new_collections:
-            at_least_one_new_valid_seq = validate_upload(api, c,
-                                                         args.validated_project,
-                                                         args.fastq_project,
-                                                         args.fastq_workflow_uuid,
-                                                         args.revalidate) or at_least_one_new_valid_seq
+            at_least_one_new_valid_seq = seqanalyzer.validate_upload(c, args.revalidate) or at_least_one_new_valid_seq
 
         if at_least_one_new_valid_seq and not args.no_start_analysis:
-            start_pangenome_analysis(api,
-                                     args.pangenome_analysis_project,
-                                     args.pangenome_workflow_uuid,
-                                     args.validated_project,
-                                     schema_ref,
-                                     args.exclude_list)
-
-        copy_most_recent_result(api,
-                                args.pangenome_analysis_project,
-                                args.latest_result_collection)
+            seqanalyzer.start_pangenome_analysis()
+
+        seqanalyzer.copy_most_recent_result()
 
         if args.once:
             break