Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/fc/bb85980035e90f1ee090ed7ebfa389/.command.sh
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/d8/b3b0c9f76a87a0f865b91a10142f34/Sig_18_tissue_alleles.tsv.gz
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/ce/a27cb7406f1d3f0912b6577b00c149/Sig_18_Blood_alleles.tsv.gz
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/6f/650960efedd77813abba3533a36610/Sig_18_Blood_normalized.parquet
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/tmp/95/dbd4851556ced0e95672a398a71a83/pairs.tsv
  Downloading: s3://natera-platform-sandbox/pipeline-inputs/test_sarek/shared/somatic_cnv/Homo_sapiens.GRCh38.110.chr21.gtf.gz
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/38/988419cad2fe6f6938fa2686500d24/Sig_18_tissue_normalized.parquet
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/fc/bb85980035e90f1ee090ed7ebfa389/.command.run
==> STAGING COMPLETE (8 inputs)

mkdir -p failed for path /.config/matplotlib: [Errno 13] Permission denied: '/.config'
Matplotlib created a temporary cache directory at /tmp/matplotlib-chr0wlxp because there was an issue with the default path (/.config/matplotlib); it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
Processing 1 T/N pair(s)...
  Enabled: mode=ascn, joint-seg, purity-estimation, adaptive-pen, weighted-seg, fit=clonal-decomp
  Loading gene annotations from Homo_sapiens.GRCh38.110.chr21.gtf.gz...
  Loaded 898 gene annotations
  [1/1] custom_Sig_18_tumor_normal... MAD=0.2363, pen_mult=1.40/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
/usr/local/lib/python3.12/site-packages/sklearn/base.py:1403: ConvergenceWarning: Number of distinct clusters (10) found smaller than n_clusters (12). Possibly due to duplicate points in X.
  return fit_method(estimator, *args, **kwargs)
  fit_multiclone_select: n_peaks=4, n_segs=13, dipLogR=-0.1080
  Greedy search: 4 model combinations
  n_clones=1 best[0]: sum_rho=0.2016, cost=0.12318, ICL=-29.15, converged=True, n_iter=2, init=[0.2156], phi=[0.2016]
  n_clones=2 best[0,1]: sum_rho=0.2159, cost=0.01157, ICL=-52.39, converged=True, n_iter=3, init=[0.0630, 0.2156], phi=[0.0704, 0.1455]
  n_clones=3 best[0,1,2]: sum_rho=0.2149, cost=0.00641, ICL=-56.99, converged=True, n_iter=2, init=[0.0630, 0.1202, 0.2156], phi=[0.0632, 0.0583, 0.0934]
  n_clones=4 best[0,1,2,3]: sum_rho=0.2149, cost=0.00622, ICL=-54.42, converged=True, n_iter=2, init=[0.0487, 0.0630, 0.1202, 0.2156], phi=[0.0479, 0.0149, 0.0586, 0.0935]
  SELECTED (best-ICL): n_clones=3, ICL=-56.99, purity=0.2149 (4 models evaluated)
Wrote 4581 probes to custom_Sig_18_tumor_normal_probe_agg.tsv.gz
 13 segments, 13 events, 255 genes
Wrote 13 segments (13 events) to custom_Sig_18_tumor_normal_segments.tsv
Wrote 13 segments to custom_Sig_18_tumor_normal.seg
Wrote 1 metrics rows to custom_Sig_18_tumor_normal_metrics.tsv
Wrote 255 gene entries to custom_Sig_18_tumor_normal_gene_cnv.tsv.gz
Wrote somatic VCF to custom_Sig_18_tumor_normal_somatic.vcf

Single-sample analysis...
  custom_Sig_18_tumor_normal (tumor)...  fit_multiclone_select: n_peaks=4, n_segs=14, dipLogR=-0.0920
  Greedy search: 4 model combinations
  n_clones=1 best[0]: sum_rho=0.0302, cost=0.00191, ICL=-84.07, converged=True, n_iter=2, init=[0.0344], phi=[0.0302]
  n_clones=2 best[0,1]: sum_rho=0.1336, cost=0.01726, ICL=-51.59, converged=True, n_iter=2, init=[0.0344, 0.1345], phi=[0.0303, 0.1033]
  n_clones=3 best[0,1,2]: sum_rho=0.1349, cost=0.01674, ICL=-49.31, converged=True, n_iter=3, init=[0.0344, 0.0964, 0.1345], phi=[0.0312, 0.0636, 0.0400]
  n_clones=4 best[0,1,2,3]: sum_rho=0.4212, cost=0.01523, ICL=-48.56, converged=True, n_iter=5, init=[0.0344, 0.0964, 0.1345, 0.4207], phi=[0.0301, 0.0645, 0.0387, 0.2879]
  SELECTED (best-ICL): n_clones=1, ICL=-84.07, purity=0.0302 (4 models evaluated)
 14 segments, 14 events
Wrote 14 segments to ./tumor_only/custom_Sig_18_tumor_normal.seg
Wrote 4581 probes to ./tumor_only/custom_Sig_18_tumor_normal_probe_agg.tsv.gz
  custom_Sig_18_tumor_normal (blood)...Traceback (most recent call last):
  File "/usr/local/bin/call_cnv.py", line 2215, in <module>
    main()
  File "/usr/local/bin/call_cnv.py", line 2117, in main
    ss_result, ss_probes, ss_clones, ss_metrics = call_cnv_single_sample(
                                                  ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/bin/call_cnv.py", line 1668, in call_cnv_single_sample
    result_df, clone_summary, metrics = run_germline_decomp(
                                        ^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/bin/clonal_decomp.py", line 1750, in run_germline_decomp
    fit_result = fit_diploid_logr(df, dipLogR_range=germ_dipLogR_range,
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/bin/clonal_decomp.py", line 373, in fit_diploid_logr
    fold_cost_curves[fi] = future.result()
                           ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/concurrent/futures/_base.py", line 449, in result
    return self.__get_result()
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
    raise self._exception
  File "/usr/local/lib/python3.12/concurrent/futures/thread.py", line 59, in run
    result = self.fn(*self.args, **self.kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/bin/clonal_decomp.py", line 361, in _cv_fold
    return _compute_cost_curve(
           ^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/bin/clonal_decomp.py", line 233, in _compute_cost_curve
    chunk_d = max(1, int(5e8 / (S * C * 8)))
                         ~~~~^~~~~~~~~~~~~
ZeroDivisionError: float division by zero