Downloading: s3://natera-platform-sandbox/pipeline-resources/ngi-igenomes/igenomes/Homo_sapiens/GATK/GRCh38/Sequence/WholeGenomeFasta/Homo_sapiens_assembly38.fasta
Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/d1/928d74ac00137a539388e59c68dc07/.command.sh
Downloading: s3://natera-platform-sandbox/pipeline-inputs/test_sarek/end_to_end_regression/output_runs/dev_latest_regression_eks__47a821d--20260221-174447/preprocessing/recalibrated/Sig_18_Blood/Sig_18_Blood.recal.bam
Downloading: s3://natera-platform-sandbox/pipeline-resources/ngi-igenomes/igenomes/Homo_sapiens/GATK/GRCh38/Sequence/WholeGenomeFasta/Homo_sapiens_assembly38.fasta.fai
Downloading: s3://natera-platform-sandbox/pipeline-resources/ngi-igenomes/igenomes/Homo_sapiens/GATK/GRCh38/Annotation/RF_Models/germline_rescue_targets.bed
Downloading: s3://natera-platform-sandbox/pipeline-inputs/test_sarek/end_to_end_regression/output_runs/dev_latest_regression_eks__47a821d--20260221-174447/preprocessing/recalibrated/Sig_18_Blood/Sig_18_Blood.recal.bam.bai
Downloading: s3://natera-rnd-pltf-dev-nextflow-scratch-01/work/d1/928d74ac00137a539388e59c68dc07/.command.run
==> STAGING COMPLETE (7 inputs)
2026-06-04 19:27:58.627820: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI AVX512_BF16 AVX_VNNI AMX_TILE AMX_INT8 AMX_BF16 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
I0604 19:27:59.956749 139826811356992 run_deepvariant.py:513] Creating a directory for intermediate results in tmp
***** Intermediate results will be written to tmp in docker. ****
***** Running the command:*****
time seq 0 3 | parallel -q --halt 2 --line-buffer /opt/deepvariant/bin/make_examples --mode calling --ref "Homo_sapiens_assembly38.fasta" --reads "Sig_18_Blood.recal.bam" --examples "tmp/make_examples.tfrecord@4.gz" --channels "insert_size" --gvcf "tmp/gvcf.tfrecord@4.gz" --regions "germline_rescue_targets.bed" --task {}
I0604 19:28:01.807821 140551774365504 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:01.810882 140551774365504 make_examples_core.py:301] Task 3/4: Preparing inputs
I0604 19:28:01.820179 140551774365504 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:01.856081 140399643518784 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:01.858996 140399643518784 make_examples_core.py:301] Task 0/4: Preparing inputs
I0604 19:28:01.868239 140399643518784 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:01.891452 140104225748800 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:01.894347 140104225748800 make_examples_core.py:301] Task 1/4: Preparing inputs
I0604 19:28:01.903495 140104225748800 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:01.942635 140313045219136 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:01.945774 140313045219136 make_examples_core.py:301] Task 2/4: Preparing inputs
I0604 19:28:01.955768 140313045219136 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.133716 140399643518784 make_examples_core.py:301] Task 0/4: Common contigs are ['chr1', 'chr2', 'chr3', 'chr4', 'chr5', 'chr6', 'chr7', 'chr8', 'chr9', 'chr10', 'chr11', 'chr12', 'chr13', 'chr14', 'chr15', 'chr16', 'chr17', 'chr18', 'chr19', 'chr20', 'chr21', 'chr22', 'chrX', 'chrY', 'chrM']
I0604 19:28:02.086242 140551774365504 make_examples_core.py:301] Task 3/4: Common contigs are ['chr1', 'chr2', 'chr3', 'chr4', 'chr5', 'chr6', 'chr7', 'chr8', 'chr9', 'chr10', 'chr11', 'chr12', 'chr13', 'chr14', 'chr15', 'chr16', 'chr17', 'chr18', 'chr19', 'chr20', 'chr21', 'chr22', 'chrX', 'chrY', 'chrM']
I0604 19:28:02.167045 140104225748800 make_examples_core.py:301] Task 1/4: Common contigs are ['chr1', 'chr2', 'chr3', 'chr4', 'chr5', 'chr6', 'chr7', 'chr8', 'chr9', 'chr10', 'chr11', 'chr12', 'chr13', 'chr14', 'chr15', 'chr16', 'chr17', 'chr18', 'chr19', 'chr20', 'chr21', 'chr22', 'chrX', 'chrY', 'chrM']
I0604 19:28:02.362556 140399643518784 genomics_reader.py:222] Reading germline_rescue_targets.bed with NativeBedReader
I0604 19:28:02.293508 140551774365504 genomics_reader.py:222] Reading germline_rescue_targets.bed with NativeBedReader
I0604 19:28:02.390233 140104225748800 genomics_reader.py:222] Reading germline_rescue_targets.bed with NativeBedReader
I0604 19:28:02.241065 140313045219136 make_examples_core.py:301] Task 2/4: Common contigs are ['chr1', 'chr2', 'chr3', 'chr4', 'chr5', 'chr6', 'chr7', 'chr8', 'chr9', 'chr10', 'chr11', 'chr12', 'chr13', 'chr14', 'chr15', 'chr16', 'chr17', 'chr18', 'chr19', 'chr20', 'chr21', 'chr22', 'chrX', 'chrY', 'chrM']
I0604 19:28:02.559807 140551774365504 make_examples_core.py:301] Task 3/4: Starting from v0.9.0, --use_ref_for_cram is default to true. If you are using CRAM input, note that we will decode CRAM using the reference you passed in with --ref
I0604 19:28:02.613089 140551774365504 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.507681 140313045219136 genomics_reader.py:222] Reading germline_rescue_targets.bed with NativeBedReader
I0604 19:28:02.635304 140399643518784 make_examples_core.py:301] Task 0/4: Starting from v0.9.0, --use_ref_for_cram is default to true. If you are using CRAM input, note that we will decode CRAM using the reference you passed in with --ref
I0604 19:28:02.693521 140399643518784 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.737331 140399643518784 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.737911 140399643518784 make_examples_core.py:301] Task 0/4: Writing gvcf records to tmp/gvcf.tfrecord-00000-of-00004.gz
I0604 19:28:02.738305 140399643518784 make_examples_core.py:301] Task 0/4: Writing examples to tmp/make_examples.tfrecord-00000-of-00004.gz
I0604 19:28:02.738367 140399643518784 make_examples_core.py:301] Task 0/4: Overhead for preparing inputs: 0 seconds
I0604 19:28:02.741637 140399643518784 make_examples_core.py:301] Task 0/4: 0 candidates (0 examples) [0.00s elapsed]
I0604 19:28:02.656867 140551774365504 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.657463 140551774365504 make_examples_core.py:301] Task 3/4: Writing gvcf records to tmp/gvcf.tfrecord-00003-of-00004.gz
I0604 19:28:02.657875 140551774365504 make_examples_core.py:301] Task 3/4: Writing examples to tmp/make_examples.tfrecord-00003-of-00004.gz
I0604 19:28:02.657940 140551774365504 make_examples_core.py:301] Task 3/4: Overhead for preparing inputs: 0 seconds
I0604 19:28:02.660626 140551774365504 make_examples_core.py:301] Task 3/4: 0 candidates (0 examples) [0.00s elapsed]
I0604 19:28:02.661484 140104225748800 make_examples_core.py:301] Task 1/4: Starting from v0.9.0, --use_ref_for_cram is default to true. If you are using CRAM input, note that we will decode CRAM using the reference you passed in with --ref
I0604 19:28:02.714947 140104225748800 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.758488 140104225748800 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.759056 140104225748800 make_examples_core.py:301] Task 1/4: Writing gvcf records to tmp/gvcf.tfrecord-00001-of-00004.gz
I0604 19:28:02.759446 140104225748800 make_examples_core.py:301] Task 1/4: Writing examples to tmp/make_examples.tfrecord-00001-of-00004.gz
I0604 19:28:02.759505 140104225748800 make_examples_core.py:301] Task 1/4: Overhead for preparing inputs: 0 seconds
I0604 19:28:02.762100 140104225748800 make_examples_core.py:301] Task 1/4: 0 candidates (0 examples) [0.00s elapsed]
I0604 19:28:02.808684 140313045219136 make_examples_core.py:301] Task 2/4: Starting from v0.9.0, --use_ref_for_cram is default to true. If you are using CRAM input, note that we will decode CRAM using the reference you passed in with --ref
I0604 19:28:02.864575 140313045219136 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.908656 140313045219136 genomics_reader.py:222] Reading Sig_18_Blood.recal.bam with NativeSamReader
I0604 19:28:02.909218 140313045219136 make_examples_core.py:301] Task 2/4: Writing gvcf records to tmp/gvcf.tfrecord-00002-of-00004.gz
I0604 19:28:02.909606 140313045219136 make_examples_core.py:301] Task 2/4: Writing examples to tmp/make_examples.tfrecord-00002-of-00004.gz
I0604 19:28:02.909664 140313045219136 make_examples_core.py:301] Task 2/4: Overhead for preparing inputs: 0 seconds
I0604 19:28:02.912548 140313045219136 make_examples_core.py:301] Task 2/4: 0 candidates (0 examples) [0.00s elapsed]
I0604 19:28:04.417263 140551774365504 make_examples_core.py:301] Task 3/4: Writing example info to tmp/make_examples.tfrecord-00003-of-00004.gz.example_info.json
I0604 19:28:04.417393 140551774365504 make_examples_core.py:2958] example_shape = [100, 221, 7]
I0604 19:28:04.417570 140551774365504 make_examples_core.py:2959] example_channels = [1, 2, 3, 4, 5, 6, 19]
I0604 19:28:04.417857 140551774365504 make_examples_core.py:301] Task 3/4: Found 1 candidate variants
I0604 19:28:04.417886 140551774365504 make_examples_core.py:301] Task 3/4: Created 1 examples
I0604 19:28:04.649316 140104225748800 make_examples_core.py:301] Task 1/4: Writing example info to tmp/make_examples.tfrecord-00001-of-00004.gz.example_info.json
I0604 19:28:04.649451 140104225748800 make_examples_core.py:2958] example_shape = [100, 221, 7]
I0604 19:28:04.649626 140104225748800 make_examples_core.py:2959] example_channels = [1, 2, 3, 4, 5, 6, 19]
I0604 19:28:04.649929 140104225748800 make_examples_core.py:301] Task 1/4: Found 1 candidate variants
I0604 19:28:04.649957 140104225748800 make_examples_core.py:301] Task 1/4: Created 1 examples
I0604 19:28:05.049471 140313045219136 make_examples_core.py:301] Task 2/4: Writing example info to tmp/make_examples.tfrecord-00002-of-00004.gz.example_info.json
I0604 19:28:05.049586 140313045219136 make_examples_core.py:2958] example_shape = [100, 221, 7]
I0604 19:28:05.049742 140313045219136 make_examples_core.py:2959] example_channels = [1, 2, 3, 4, 5, 6, 19]
I0604 19:28:05.050002 140313045219136 make_examples_core.py:301] Task 2/4: Found 3 candidate variants
I0604 19:28:05.050031 140313045219136 make_examples_core.py:301] Task 2/4: Created 5 examples
I0604 19:28:06.179383 140399643518784 make_examples_core.py:301] Task 0/4: Writing example info to tmp/make_examples.tfrecord-00000-of-00004.gz.example_info.json
I0604 19:28:06.179520 140399643518784 make_examples_core.py:2958] example_shape = [100, 221, 7]
I0604 19:28:06.179694 140399643518784 make_examples_core.py:2959] example_channels = [1, 2, 3, 4, 5, 6, 19]
I0604 19:28:06.180018 140399643518784 make_examples_core.py:301] Task 0/4: Found 3 candidate variants
I0604 19:28:06.180081 140399643518784 make_examples_core.py:301] Task 0/4: Created 8 examples
real 0m6.571s
user 0m21.359s
sys 0m7.446s
***** Running the command:*****
time /opt/deepvariant/bin/call_variants --outfile "tmp/call_variants_output.tfrecord.gz" --examples "tmp/make_examples.tfrecord@4.gz" --checkpoint "/opt/models/wes"
/usr/local/lib/python3.8/dist-packages/tensorflow_addons/utils/tfa_eol_msg.py:23: UserWarning:
TensorFlow Addons (TFA) has ended development and introduction of new features.
TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024.
Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP).
For more information see: https://github.com/tensorflow/addons/issues/2807
warnings.warn(
I0604 19:28:08.466099 140584366806848 call_variants.py:563] Total 1 writing processes started.
I0604 19:28:08.467483 140584366806848 dv_utils.py:370] From tmp/make_examples.tfrecord-00000-of-00004.gz.example_info.json: Shape of input examples: [100, 221, 7], Channels of input examples: [1, 2, 3, 4, 5, 6, 19].
I0604 19:28:08.467546 140584366806848 call_variants.py:588] Shape of input examples: [100, 221, 7]
I0604 19:28:08.467751 140584366806848 call_variants.py:592] Use saved model: True
I0604 19:28:12.459741 140584366806848 dv_utils.py:370] From /opt/models/wes/example_info.json: Shape of input examples: [100, 221, 7], Channels of input examples: [1, 2, 3, 4, 5, 6, 19].
I0604 19:28:12.459922 140584366806848 dv_utils.py:370] From tmp/make_examples.tfrecord-00000-of-00004.gz.example_info.json: Shape of input examples: [100, 221, 7], Channels of input examples: [1, 2, 3, 4, 5, 6, 19].
I0604 19:28:12.992909 140584366806848 call_variants.py:716] Predicted 15 examples in 1 batches [2.730 sec per 100].
I0604 19:28:13.052647 140584366806848 call_variants.py:779] Complete: call_variants.
real 0m7.299s
user 0m8.603s
sys 0m5.121s
***** Running the command:*****
time /opt/deepvariant/bin/postprocess_variants --ref "Homo_sapiens_assembly38.fasta" --infile "tmp/call_variants_output.tfrecord.gz" --outfile "Sig_18_Blood.dv_rescue.vcf.gz" --cpus "4" --gvcf_outfile "Sig_18_Blood.dv_rescue.g.vcf.gz" --nonvariant_site_tfrecord_path "tmp/gvcf.tfrecord@4.gz"
I0604 19:28:15.590205 140692127807296 postprocess_variants.py:1211] Using sample name from call_variants output. Sample name: Sig_18_Blood
2026-06-04 19:28:15.593954: I deepvariant/postprocess_variants.cc:94] Read from: tmp/call_variants_output-00000-of-00001.tfrecord.gz
2026-06-04 19:28:15.594084: I deepvariant/postprocess_variants.cc:109] Total #entries in single_site_calls = 15
I0604 19:28:15.595119 140692127807296 postprocess_variants.py:1313] CVO sorting took 7.363557815551758e-05 minutes
I0604 19:28:15.595293 140692127807296 postprocess_variants.py:1316] Transforming call_variants_output to variants.
I0604 19:28:15.595329 140692127807296 postprocess_variants.py:1318] Using 4 CPUs for parallelization of variant transformation.
I0604 19:28:15.614283 140692127807296 postprocess_variants.py:1211] Using sample name from call_variants output. Sample name: Sig_18_Blood
I0604 19:28:15.619789 140692127807296 postprocess_variants.py:1386] Processing variants (and writing to temporary file) took 4.9845377604166666e-05 minutes
I0604 19:28:15.721025 140692127807296 postprocess_variants.py:1407] Finished writing VCF and gVCF in 0.0016852100690205893 minutes.
real 0m2.172s
user 0m3.120s
sys 0m4.766s
***** Running the command:*****
time /opt/deepvariant/bin/vcf_stats_report --input_vcf "Sig_18_Blood.dv_rescue.vcf.gz" --outfile_base "Sig_18_Blood.dv_rescue"
I0604 19:28:17.703829 140675375187776 genomics_reader.py:222] Reading Sig_18_Blood.dv_rescue.vcf.gz with NativeVcfReader
real 0m2.044s
user 0m3.249s
sys 0m4.639s