Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/9d/bfe3a3416a90b7fb0ba4a1248ceaa3/.command.sh Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/c5/e09f79fe0a1a21147850e4de21008f/Sig_18_tissue_alleles.tsv.gz Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/51/791e6ec603a2d4b08cf43742fe6e96/Sig_18_Blood_alleles.tsv.gz Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/02/e6bb9c39b26f5cce30285fb8b37d30/Sig_18_Blood_normalized.parquet Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/tmp/59/4dbc46ca35143050a9693fcfb37a77/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/63/342290dbf169f4a9652b75e546d067/Sig_18_tissue_normalized.parquet Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/9d/bfe3a3416a90b7fb0ba4a1248ceaa3/.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-zf844v8j 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 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 1756, in run_germline_decomp fit_result = fit_diploid_logr(df, dipLogR_range=germ_dipLogR_range, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/bin/clonal_decomp.py", line 407, in fit_diploid_logr "se": horiz_se, ^^^^^^^^ UnboundLocalError: cannot access local variable 'horiz_se' where it is not associated with a value