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Update code to support latest versions of pyhmmer and scikit-learn #105

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Update code to support latest versions of pyhmmer and scikit-learn #105

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20 changes: 10 additions & 10 deletions bigslice/bigslice
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Original file line number Diff line number Diff line change
Expand Up @@ -55,8 +55,8 @@ def run_subpfam_scan(tuples):
for hit in top_hits:
if hit.best_domain.score < top_hits.domT:
continue
target_name = hit.name.decode()
hmm_name = top_hits.query_name.decode()
target_name = hit.name
hmm_name = top_hits.query.name
alignment = hit.best_domain.alignment

bgc_id, cds_id, parent_hsp_id, locs = target_name.split("|")
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Expand Down Expand Up @@ -102,8 +102,8 @@ def run_subpfam_scan_hmmscan(tuples):
# this will return a sorted high-to-low hits, so no need to re-sort
if i >= top_k:
break
target_name = sequence.name.decode()
hmm_name = hit.name.decode()
target_name = sequence.name
hmm_name = hit.name

bgc_id, cds_id, parent_hsp_id, locs = target_name.split("|")
bgc_id = int(bgc_id.split("bgc:")[-1])
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Expand Down Expand Up @@ -673,8 +673,8 @@ def query_mode(report_name, input_folder, input_run_id, pool,
if hit.best_domain.score < top_hits.domT:
continue

target_name = hit.name.decode()
hmm_name = top_hits.query_accession.decode()
target_name = hit.name
hmm_name = top_hits.query.accession
alignment = hit.best_domain.alignment

bgc_id, cds_id, parent_hsp_id, locs = target_name.split("|")
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Expand Down Expand Up @@ -1365,8 +1365,8 @@ def main():
if hit.best_domain.score < top_hits.domT:
continue

target_name = hit.name.decode()
hmm_name = top_hits.query_accession.decode()
target_name = hit.name
hmm_name = top_hits.query.accession
alignment = hit.best_domain.alignment

bgc_id, cds_id, parent_hsp_id, locs = target_name.split("|")
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Expand Down Expand Up @@ -1648,8 +1648,8 @@ def main():
cpus=args.num_threads, T=20
):
for hit in top_hits:
target_name = hit.name.decode()
hmm_name = top_hits.query_name.decode()
target_name = hit.name
hmm_name = top_hits.query.name
alignment = hit.best_domain.alignment

bgc_id, cds_id, parent_hsp_id, locs = target_name.split("|")
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Expand Down
3 changes: 1 addition & 2 deletions bigslice/modules/clustering/birch.py
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Expand Up @@ -185,8 +185,7 @@ def fetch_threshold(df: pd.DataFrame,
# initiate birch object
birch = Birch(
n_clusters=None, # no global clustering
compute_labels=False, # only calc centroids
copy=False # data already copied
compute_labels=False # only calc centroids
)

# set threshold
Expand Down
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