Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/7b/74450db414a890a9cc6476da4aca80/1029_01S-N1-BDNA-1_B23KGCJLT4_1_normalized.parquet
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/stage-5a33db34-7422-4b3f-8604-8bf67919e454/dd/dd5083d3ada8e3e7b41471391c5172/test_pairs.tsv
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/d4/2127ec39c6bcca940838837e0ee870/.command.sh
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/53/d2261551d00bc842c6cbfe2ab3bea1/1029_01S-T1-TDNA-1_B23KFCWLT4_1_alleles.tsv.gz
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/82/c88c6af8c0eeced0cc2cb24b4eecb1/1029_01S-N1-BDNA-1_B23KGCJLT4_1_alleles.tsv.gz
  Downloading: s3://natera-platform-sandbox/pipeline-resources/ensembl/Homo_sapiens.GRCh38.110.gtf.gz
  Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/d4/2127ec39c6bcca940838837e0ee870/.command.run
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  Downloading: s3://ai-pipelines-experiment/somatic-cnv/altera_genes_hg38.bed
==> STAGING COMPLETE (9 inputs)

mkdir -p failed for path /.config/matplotlib: [Errno 13] Permission denied: '/.config'
Matplotlib created a temporary cache directory at /tmp/matplotlib-7ep9i6d2 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.gtf.gz...
  Loaded 62062 gene annotations
  [1/1] 1029_01S... MAD=0.2221, pen_mult=1.23  fit_multiclone_select: n_peaks=7, n_segs=142, dipLogR=-0.2440
  Greedy search: 7 model combinations
  n_clones=1 best[0]: sum_rho=0.1419, cost=0.02554, ICL=-858.29, converged=True, n_iter=2, init=[0.1403], phi=[0.1419]
  n_clones=2 best[0,1]: sum_rho=0.1534, cost=0.01782, ICL=-893.17, converged=True, n_iter=7, init=[0.1182, 0.1403], phi=[0.1136, 0.0397]
  n_clones=3 best[0,1,2]: sum_rho=0.1772, cost=0.01119, ICL=-953.94, converged=True, n_iter=13, init=[0.1002, 0.1182, 0.1403], phi=[0.0991, 0.0299, 0.0481]
  n_clones=4 best[0,1,2,3]: sum_rho=0.1845, cost=0.00940, ICL=-973.46, converged=True, n_iter=26, init=[0.0842, 0.1002, 0.1182, 0.1403], phi=[0.0836, 0.0339, 0.0217, 0.0453]
  n_clones=5 best[0,1,2,3,4]: sum_rho=0.1851, cost=0.00904, ICL=-973.71, converged=True, n_iter=24, init=[0.0701, 0.0842, 0.1002, 0.1182, 0.1403], phi=[0.0779, 0.0253, 0.0155, 0.0310, 0.0353]
  n_clones=6 best[0,1,2,3,4,5]: sum_rho=0.1841, cost=0.00905, ICL=-968.58, converged=True, n_iter=18, init=[0.0421, 0.0701, 0.0842, 0.1002, 0.1182, 0.1403], phi=[0.0398, 0.0364, 0.0170, 0.0268, 0.0307, 0.0333]
  n_clones=7 best[0,1,2,3,4,5,6]: sum_rho=0.1959, cost=0.00874, ICL=-969.42, converged=True, n_iter=37, init=[0.0421, 0.0701, 0.0842, 0.1002, 0.1182, 0.1403, 0.1703], phi=[0.0395, 0.0309, 0.0155, 0.0220, 0.0264, 0.0292, 0.0324]
  SELECTED (best-ICL): n_clones=5, ICL=-973.71, purity=0.1851 (7 models evaluated)
Wrote 435083 probes to 1029_01S_probe_agg.tsv.gz
 142 segments, 142 events, 21016 genes
Wrote 142 segments (142 events) to 1029_01S_segments.tsv
Wrote 142 segments to 1029_01S.seg
Wrote 1 metrics rows to 1029_01S_metrics.tsv
Wrote 21016 gene entries to 1029_01S_gene_cnv.tsv.gz
Wrote somatic VCF to 1029_01S_somatic.vcf

Single-sample analysis...
  1029_01S (tumor)...  fit_multiclone_select: n_peaks=7, n_segs=309, dipLogR=-0.2120
  Greedy search: 7 model combinations
  n_clones=1 best[0]: sum_rho=0.0883, cost=0.02565, ICL=-2075.41, converged=True, n_iter=4, init=[0.0802], phi=[0.0883]
  n_clones=2 best[0,1]: sum_rho=0.1436, cost=0.01789, ICL=-2182.64, converged=True, n_iter=6, init=[0.0802, 0.1383], phi=[0.0817, 0.0619]
  n_clones=3 best[0,1,2]: sum_rho=0.1630, cost=0.01069, ICL=-2334.05, converged=True, n_iter=14, init=[0.0802, 0.0942, 0.1383], phi=[0.0974, 0.0239, 0.0418]
  n_clones=4 best[0,1,2,3]: sum_rho=0.1668, cost=0.00946, ICL=-2364.46, converged=True, n_iter=12, init=[0.0802, 0.0942, 0.1082, 0.1383], phi=[0.0869, 0.0158, 0.0284, 0.0356]
  n_clones=5 best[0,1,2,3,4]: sum_rho=0.1659, cost=0.00934, ICL=-2361.56, converged=True, n_iter=10, init=[0.0802, 0.0942, 0.1082, 0.1202, 0.1383], phi=[0.0834, 0.0136, 0.0233, 0.0184, 0.0272]
  n_clones=6 best[0,1,2,3,4,5]: sum_rho=0.1689, cost=0.00922, ICL=-2360.24, converged=True, n_iter=17, init=[0.0641, 0.0802, 0.0942, 0.1082, 0.1202, 0.1383], phi=[0.0657, 0.0246, 0.0139, 0.0168, 0.0198, 0.0282]
  n_clones=7 best[0,1,2,3,4,5,6]: sum_rho=0.1670, cost=0.00926, ICL=-2352.95, converged=True, n_iter=16, init=[0.0421, 0.0641, 0.0802, 0.0942, 0.1082, 0.1202, 0.1383], phi=[0.0368, 0.0293, 0.0200, 0.0151, 0.0248, 0.0188, 0.0222]
  SELECTED (best-ICL): n_clones=4, ICL=-2364.46, purity=0.1668 (7 models evaluated)
 309 segments, 309 events
Wrote 309 segments to ./tumor_only/1029_01S.seg
Wrote 435083 probes to ./tumor_only/1029_01S_probe_agg.tsv.gz
  1029_01S (blood)... 134 segments, 42 events
Wrote 134 segments to ./blood_only/1029_01S.seg
Wrote 435083 probes to ./blood_only/1029_01S_probe_agg.tsv.gz
Single-sample analysis complete.