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View Code? Open in Web Editor NEWSNP-Assisted SV Calling and Phasing Using ONT
License: BSD 3-Clause "New" or "Revised" License
SNP-Assisted SV Calling and Phasing Using ONT
License: BSD 3-Clause "New" or "Revised" License
Hello,
I'm trying to run SURVIVOR on the Duet output (generated using cuteSV) but it doesn't give me an output unless I run the same file against itself.
Is Duet supposed to be compatible with SURVIVOR? Any suggestions to get it running?
Thanks,
Melissa
There seems to be a Syntax error in snp_phasing
when running duet on a single chromosome.
The command am running: duet -t 8 -a -b sniffles 01_minimap2_mapping/sample1.bam /data/references/human_references/chr6_hg38.fasta 02_variants/duet_sniffles/sample1
15507/15507 alignments processed (100%, 7147/s); 1/1 tasks done; parallel 0/8; 0 SVs.
Took 2.17s.
Done.
Wrote 0 called SVs to 02_variants/duet_sniffles/sample1/sv_calling/variants.vcf (single-sample, sorted)
13:37:21 [INFO] ************************* SV CALLING COMPLETED IN 2.324s *************************
13:37:21 [INFO] ************************* SNP PHASING STARTED *************************
mkdir: cannot create directory ‘02_variants/duet_sniffles/sample1/snp_phasing/’: File exists
02_variants/duet_sniffles/sample1/snp_phasing/parallel_wh.sh: 1: Syntax error: "(" unexpected
13:37:21 [INFO] ************************* SNP PHASING COMPLETED IN 0.021s *************************
13:37:21 [INFO] ************************* SV PHASING STARTED *************************
13:37:21 [INFO] create output .vcf file
13:37:21 [INFO] extract SNP signatures
13:37:22 [INFO] signatures extracted from chr6
13:37:22 [INFO] extract SV signatures
13:37:22 [INFO] no signature from chr6
13:37:22 [INFO] integrate read weight information
13:37:22 [INFO] calculate read weight statistics
13:37:22 [INFO] predict SV haplotypes in the callset
13:37:22 [INFO] write phased callset into .vcf file
13:37:22 [INFO] ************************* SV PHASING COMPLETED IN 0.79s *************************
13:37:22 [INFO] ************************* DUET FINISHED IN 27.737s *************************
13:37:22 [INFO] OUTPUT .VCF FILE AT 02_variants/duet_sniffles/sample1/phased_sv.vcf
Running bash parallel_wh.sh
completes without any issues.
Hello,
Is there a preferred strategy to combine phased calls from multiple samples or genotype and phase existing SVs?
All the best,
Agnieszka
AttributeError: module 'numpy' has no attribute 'int'.
np.int
was a deprecated alias for the builtin int
. To avoid this error in existing code, use int
by itself. Doing this will not modify any behavior and is safe. When replacing np.int
, you may wish to use e.g. np.int64
or np.int32
to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
This looks like a pretty simple fix-- just change np.int to int and it should fix it for current versions of numpy. You could also consider np.int64 (considering the number of bases is greater than 2.7 billion, the largest directly representable number in int32).
Hi
While this program looks quite promising, we're encountering several problems trying to install the required software to make duet run.
Would it be possible to provide a docker image with duet and its runtime environment?
-Harald
您好,我发现在程序没有停止运行的情况下,遇到以下一些(截取了部分) error,在运行 log 中通常标记为 W,请问这些报错是为什么呢?是否会影响结果,谢谢!
Total processed positions in Chr2h00 (chunk 5/6) : 65085
Total time elapsed: 205.46 s
2022-12-09 16:44:06.651759: 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 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-12-09 16:44:07.597312: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-12-09 16:44:07.597403: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-12-09 16:44:09.659883: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:44:09.660136: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:44:09.660169: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2022-12-09 16:44:14.087976: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-12-09 16:44:14.088681: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2022-12-09 16:44:14.088953: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wxw-Super-Server): /proc/driver/nvidia/version does not exist
2022-12-09 16:44:14.091689: 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 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Calling variants ...
Total processed positions in Chr2h00 (chunk 6/6) : 65146
Total time elapsed: 209.73 s
2022-12-09 16:43:33.529776: 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 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-12-09 16:43:33.897579: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-12-09 16:43:33.897709: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-12-09 16:43:38.317267: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:38.318458: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:38.318650: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2022-12-09 16:43:43.359557: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-12-09 16:43:43.359668: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2022-12-09 16:43:43.359720: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wxw-Super-Server): /proc/driver/nvidia/version does not exist
2022-12-09 16:43:43.360174: 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 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Calling variants ...
Total processed positions in Chr2h18 (chunk 2/4) : 63390
Total time elapsed: 241.85 s
2022-12-09 16:43:48.758377: 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 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-12-09 16:43:50.615858: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-12-09 16:43:50.616531: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-12-09 16:43:52.739768: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:52.740052: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2022-12-09 16:43:52.740090: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2022-12-09 16:43:57.225463: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-12-09 16:43:57.226372: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2022-12-09 16:43:57.226688: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (wxw-Super-Server): /proc/driver/nvidia/version does not exist
2022-12-09 16:43:57.230685: 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 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Calling variants ...
Total processed positions in Chr2h18 (chunk 4/4) : 69829
Total time elapsed: 238.72 s
real 24m31.352s
user 668m49.375s
sys 37m54.743s
Hi,
I'm trying to run duet but the SNP calling isn't working.
Thanks,
Melissa
[INFO] Check environment variables
[INFO] --include_all_ctgs not enabled, use chr{1..22,X,Y} and {1..22,X,Y} by default
[INFO] Call variant in contigs: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X Y
[INFO] Chunk number for each contig: 50 49 40 39 37 35 32 30 29 28 28 27 24 22 21 19 17 16 12 13 10 11 32 12
[INFO] 1/7 Call variants using pileup model
Calling variants ...
Traceback (most recent call last):
File "/Project/tools/conda/duet/bin/scripts/../clair3.py", line 94, in
main()
File "/Project/tools/conda/duet/bin/scripts/../clair3.py", line 88, in main
submodule.main()
File "/Project/tools/conda/duet/bin/clair3/CallVariantsFromCffi.py", line 347, in main
Run(args)
File "/Project/tools/conda/duet/bin/clair3/CallVariantsFromCffi.py", line 61, in Run
call_variants_from_cffi(args=args, output_config=output_config, output_utilities=output_utilities)
File "/Project/tools/conda/duet/bin/clair3/CallVariantsFromCffi.py", line 117, in call_variants_from_cffi
tensor, all_position, all_alt_info = CT(args)
File "/Project/tools/conda/duet/bin/preprocess/CreateTensorPileupFromCffi.py", line 329, in CreateTensorPileup
chunk_result, all_alt_info_list, gvcf_output = pileup_counts_clair3(region,
File "/Project/tools/conda/duet/bin/preprocess/CreateTensorPileupFromCffi.py", line 84, in pileup_counts_clair3
chunk_results, all_alt_info_list, gvcf_output = __enforce_pileup_chunk_contiguity(results)
File "/Project/tools/conda/duet/bin/preprocess/CreateTensorPileupFromCffi.py", line 194, in __enforce_pileup_chunk_contiguity
for counts, positions, alt_info_list, gvcf_output in pileups:
File "/Project/tools/conda/duet/lib/python3.9/concurrent/futures/_base.py", line 600, in result_iterator
yield fs.pop().result()
File "/Project/tools/conda/duet/lib/python3.9/concurrent/futures/_base.py", line 440, in result
return self.__get_result()
File "/Project/tools/conda/duet/lib/python3.9/concurrent/futures/_base.py", line 389, in __get_result
raise self._exception
File "/Project/tools/conda/duet/lib/python3.9/concurrent/futures/thread.py", line 52, in run
result = self.fn(*self.args, **self.kwargs)
File "/Project/tools/conda/duet/bin/preprocess/CreateTensorPileupFromCffi.py", line 63, in _process_region
np_counts, positions, alt_info_string_list, gvcf_output = _plp_data_to_numpy(
File "/Project/tools/conda/duet/bin/preprocess/CreateTensorPileupFromCffi.py", line 141, in _plp_data_to_numpy
size_sizet = np.dtype(np.int).itemsize
File "/Project/tools/conda/duet/lib/python3.9/site-packages/numpy/init.py", line 305, in getattr
raise AttributeError(former_attrs[attr])
AttributeError: module 'numpy' has no attribute 'int'.
np.int
was a deprecated alias for the builtinint
. To avoid this error in existing code, useint
by itself. Doing this will not modify any behavior and is safe. When replacingnp.int
, you may wish to use e.g.np.int64
ornp.int32
to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
Am not sure but it seems you have pinned bcftools v1.54 but this raises issues with libcrypto.so.1.0.0
Hi Dr. Zhou,
Thanks for develop duet, I've successfully installed duet according to your instruction:
git clone https://github.com/yekaizhou/duet.git
cd duet && pip3 install .
But when I run on the demo data, it comes up with an error:
$duet duet_demo_data/HG00733_hg19_chr21.bam duet_demo_data/hg19_chr21.fa results
10:10:19 [INFO] ************************* DUET STARTED *************************
10:10:19 [INFO] ************************* SNP CALLING STARTED *************************
sh: line 1: run_clair3.sh: command not found
10:10:19 [INFO] ************************* SNP CALLING COMPLETED IN 0.007s *************************
10:10:19 [INFO] ************************* SV CALLING STARTED *************************
2022-12-09 10:10:19,723 [INFO] Running /usr/local/bin/cuteSV --genotype --report_readid duet_demo_data/HG00733_hg19_chr21.bam duet_demo_data/hg19_chr21.fa results/sv_calling/variants.vcf results/sv_calling/ -t 4 -s 2 -l 50
2022-12-09 10:10:19,724 [INFO] The total number of chromsomes: 86
2022-12-09 10:10:19,749 [INFO] Skip 1:0-10000000.
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2022-12-09 10:10:24,896 [INFO] Skip MT:0-16569.
2022-12-09 10:10:24,897 [INFO] Skip GL000207.1:0-4262.
2022-12-09 10:10:24,897 [INFO] Skip GL000226.1:0-15008.
2022-12-09 10:10:24,898 [INFO] Skip GL000229.1:0-19913.
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2022-12-09 10:10:24,903 [INFO] Skip GL000197.1:0-37175.
2022-12-09 10:10:24,903 [INFO] Skip GL000203.1:0-37498.
2022-12-09 10:10:24,904 [INFO] Skip GL000246.1:0-38154.
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2022-12-09 10:10:24,905 [INFO] Skip GL000196.1:0-38914.
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2022-12-09 10:10:24,910 [INFO] Skip GL000240.1:0-41933.
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2022-12-09 10:10:24,913 [INFO] Skip GL000230.1:0-43691.
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2022-12-09 10:10:24,914 [INFO] Skip GL000233.1:0-45941.
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2022-12-09 10:10:24,918 [INFO] Skip GL000228.1:0-129120.
2022-12-09 10:10:24,919 [INFO] Skip GL000214.1:0-137718.
2022-12-09 10:10:24,919 [INFO] Skip GL000221.1:0-155397.
2022-12-09 10:10:24,920 [INFO] Skip GL000209.1:0-159169.
2022-12-09 10:10:24,921 [INFO] Skip GL000218.1:0-161147.
2022-12-09 10:10:24,921 [INFO] Skip GL000220.1:0-161802.
2022-12-09 10:10:24,922 [INFO] Skip GL000213.1:0-164239.
2022-12-09 10:10:24,922 [INFO] Skip GL000211.1:0-166566.
2022-12-09 10:10:24,923 [INFO] Skip GL000199.1:0-169874.
2022-12-09 10:10:24,924 [INFO] Skip GL000217.1:0-172149.
2022-12-09 10:10:24,924 [INFO] Skip GL000216.1:0-172294.
2022-12-09 10:10:24,925 [INFO] Skip GL000215.1:0-172545.
2022-12-09 10:10:24,925 [INFO] Skip GL000205.1:0-174588.
2022-12-09 10:10:24,926 [INFO] Skip GL000219.1:0-179198.
2022-12-09 10:10:24,927 [INFO] Skip GL000224.1:0-179693.
2022-12-09 10:10:24,927 [INFO] Skip GL000223.1:0-180455.
2022-12-09 10:10:24,928 [INFO] Skip GL000195.1:0-182896.
2022-12-09 10:10:24,928 [INFO] Skip GL000212.1:0-186858.
2022-12-09 10:10:24,929 [INFO] Skip GL000222.1:0-186861.
2022-12-09 10:10:24,930 [INFO] Skip GL000200.1:0-187035.
2022-12-09 10:10:24,930 [INFO] Skip GL000193.1:0-189789.
2022-12-09 10:10:24,931 [INFO] Skip GL000194.1:0-191469.
2022-12-09 10:10:24,932 [INFO] Skip GL000225.1:0-211173.
2022-12-09 10:10:24,932 [INFO] Skip GL000192.1:0-547496.
2022-12-09 10:10:24,933 [INFO] Skip NC_007605:0-171823.
2022-12-09 10:10:24,933 [INFO] Skip hs37d5:0-10000000.
2022-12-09 10:10:24,934 [INFO] Skip hs37d5:10000000-20000000.
2022-12-09 10:10:24,935 [INFO] Skip hs37d5:20000000-30000000.
2022-12-09 10:10:24,935 [INFO] Skip hs37d5:30000000-35477943.
2022-12-09 10:10:25,647 [INFO] Finished 21:20000000-30000000.
2022-12-09 10:10:25,934 [INFO] Finished 21:40000000-48129895.
2022-12-09 10:10:26,028 [INFO] Finished 21:30000000-40000000.
2022-12-09 10:10:26,042 [INFO] Rebuilding signatures of structural variants.
2022-12-09 10:10:26,233 [INFO] Clustering structural variants.
2022-12-09 10:10:26,257 [INFO] Finished hs37d5:INV.
2022-12-09 10:10:26,342 [INFO] Finished 21:INV.
2022-12-09 10:10:26,351 [INFO] Finished X:DUP.
2022-12-09 10:10:26,359 [INFO] Finished hs37d5:DUP.
2022-12-09 10:10:26,360 [INFO] Finished 1-14:TRA/BND.
2022-12-09 10:10:26,360 [INFO] Finished 1-21:TRA/BND.
2022-12-09 10:10:26,361 [INFO] Finished 1-22:TRA/BND.
2022-12-09 10:10:26,361 [INFO] Finished 1-Y:TRA/BND.
2022-12-09 10:10:26,363 [INFO] Finished 1-hs37d5:TRA/BND.
2022-12-09 10:10:26,363 [INFO] Finished 10-21:TRA/BND.
2022-12-09 10:10:26,364 [INFO] Finished 10-8:TRA/BND.
2022-12-09 10:10:26,364 [INFO] Finished 10-Y:TRA/BND.
2022-12-09 10:10:26,365 [INFO] Finished 10-hs37d5:TRA/BND.
2022-12-09 10:10:26,369 [INFO] Finished 21:DUP.
2022-12-09 10:10:26,370 [INFO] Finished 12-2:TRA/BND.
2022-12-09 10:10:26,370 [INFO] Finished 12-20:TRA/BND.
2022-12-09 10:10:26,395 [INFO] Finished 11-21:TRA/BND.
2022-12-09 10:10:26,395 [INFO] Finished 12-4:TRA/BND.
2022-12-09 10:10:26,396 [INFO] Finished 12-6:TRA/BND.
2022-12-09 10:10:26,396 [INFO] Finished 12-7:TRA/BND.
2022-12-09 10:10:26,397 [INFO] Finished 12-hs37d5:TRA/BND.
2022-12-09 10:10:26,398 [INFO] Finished 13-21:TRA/BND.
2022-12-09 10:10:26,398 [INFO] Finished 13-6:TRA/BND.
2022-12-09 10:10:26,399 [INFO] Finished 13-hs37d5:TRA/BND.
2022-12-09 10:10:26,400 [INFO] Finished 14-15:TRA/BND.
2022-12-09 10:10:26,400 [INFO] Finished 14-21:TRA/BND.
2022-12-09 10:10:26,401 [INFO] Finished 15-20:TRA/BND.
2022-12-09 10:10:26,402 [INFO] Finished 12-21:TRA/BND.
2022-12-09 10:10:26,403 [INFO] Finished 15-22:TRA/BND.
2022-12-09 10:10:26,403 [INFO] Finished 15-3:TRA/BND.
2022-12-09 10:10:26,404 [INFO] Finished 16-21:TRA/BND.
2022-12-09 10:10:26,405 [INFO] Finished 17-21:TRA/BND.
2022-12-09 10:10:26,405 [INFO] Finished 17-3:TRA/BND.
2022-12-09 10:10:26,406 [INFO] Finished 17-hs37d5:TRA/BND.
2022-12-09 10:10:26,406 [INFO] Finished 15-21:TRA/BND.
2022-12-09 10:10:26,406 [INFO] Finished 18-21:TRA/BND.
2022-12-09 10:10:26,406 [INFO] Finished 19-21:TRA/BND.
2022-12-09 10:10:26,407 [INFO] Finished 2-9:TRA/BND.
2022-12-09 10:10:26,407 [INFO] Finished 2-GL000212.1:TRA/BND.
2022-12-09 10:10:26,408 [INFO] Finished 2-hs37d5:TRA/BND.
2022-12-09 10:10:26,409 [INFO] Finished 20-21:TRA/BND.
2022-12-09 10:10:26,409 [INFO] Finished 20-hs37d5:TRA/BND.
2022-12-09 10:10:26,442 [INFO] Finished 2-21:TRA/BND.
2022-12-09 10:10:26,443 [INFO] Finished 21-3:TRA/BND.
2022-12-09 10:10:26,443 [INFO] Finished 21-4:TRA/BND.
2022-12-09 10:10:26,444 [INFO] Finished 21-5:TRA/BND.
2022-12-09 10:10:26,444 [INFO] Finished 21-6:TRA/BND.
2022-12-09 10:10:26,528 [INFO] Finished 21-22:TRA/BND.
2022-12-09 10:10:26,528 [INFO] Finished 21-8:TRA/BND.
2022-12-09 10:10:26,558 [INFO] Finished 21-9:TRA/BND.
2022-12-09 10:10:26,558 [INFO] Finished 21-GL000199.1:TRA/BND.
2022-12-09 10:10:26,559 [INFO] Finished 21-GL000210.1:TRA/BND.
2022-12-09 10:10:26,588 [INFO] Finished 21-GL000212.1:TRA/BND.
2022-12-09 10:10:26,615 [INFO] Finished 21-7:TRA/BND.
2022-12-09 10:10:26,622 [INFO] Finished 21-GL000220.1:TRA/BND.
2022-12-09 10:10:26,622 [INFO] Finished 21-GL000226.1:TRA/BND.
2022-12-09 10:10:26,623 [INFO] Finished 21-GL000237.1:TRA/BND.
2022-12-09 10:10:26,623 [INFO] Finished 21-X:TRA/BND.
2022-12-09 10:10:26,636 [INFO] Finished 21-GL000216.1:TRA/BND.
2022-12-09 10:10:26,674 [INFO] Finished 21-Y:TRA/BND.
2022-12-09 10:10:26,675 [INFO] Finished 22-5:TRA/BND.
2022-12-09 10:10:26,676 [INFO] Finished 22-GL000210.1:TRA/BND.
2022-12-09 10:10:26,677 [INFO] Finished 22-hs37d5:TRA/BND.
2022-12-09 10:10:26,678 [INFO] Finished 3-6:TRA/BND.
2022-12-09 10:10:26,678 [INFO] Finished 3-X:TRA/BND.
2022-12-09 10:10:26,679 [INFO] Finished 4-7:TRA/BND.
2022-12-09 10:10:26,679 [INFO] Finished 4-X:TRA/BND.
2022-12-09 10:10:26,680 [INFO] Finished 5-GL000210.1:TRA/BND.
2022-12-09 10:10:26,680 [INFO] Finished 6-hs37d5:TRA/BND.
2022-12-09 10:10:26,681 [INFO] Finished 7-GL000237.1:TRA/BND.
2022-12-09 10:10:26,681 [INFO] Finished 8-hs37d5:TRA/BND.
2022-12-09 10:10:26,682 [INFO] Finished GL000212.1-hs37d5:TRA/BND.
2022-12-09 10:10:26,683 [INFO] Finished GL000220.1-GL000243.1:TRA/BND.
2022-12-09 10:10:26,683 [INFO] Finished GL000220.1-hs37d5:TRA/BND.
2022-12-09 10:10:26,683 [INFO] Finished GL000237.1-hs37d5:TRA/BND.
2022-12-09 10:10:26,684 [INFO] Finished GL000243.1-hs37d5:TRA/BND.
2022-12-09 10:10:26,684 [INFO] Finished X-hs37d5:TRA/BND.
2022-12-09 10:10:26,685 [INFO] Finished Y-hs37d5:TRA/BND.
2022-12-09 10:10:26,751 [INFO] Finished 21:INS.
2022-12-09 10:10:26,894 [INFO] Finished 21:DEL.
2022-12-09 10:10:27,315 [INFO] Finished 21-hs37d5:TRA/BND.
2022-12-09 10:10:27,322 [INFO] Writing to your output file.
2022-12-09 10:10:27,326 [INFO] Loading reference genome...
Traceback (most recent call last):
File "/usr/local/bin/cuteSV", line 4, in <module>
__import__('pkg_resources').run_script('cuteSV==2.0.2', 'cuteSV')
File "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py", line 651, in run_script
self.require(requires)[0].run_script(script_name, ns)
File "/usr/local/lib/python3.10/dist-packages/pkg_resources/__init__.py", line 1448, in run_script
exec(code, namespace, namespace)
File "/usr/local/lib/python3.10/dist-packages/cuteSV-2.0.2-py3.10.egg/EGG-INFO/scripts/cuteSV", line 888, in <module>
run(sys.argv[1:])
File "/usr/local/lib/python3.10/dist-packages/cuteSV-2.0.2-py3.10.egg/EGG-INFO/scripts/cuteSV", line 884, in run
main_ctrl(args, argv)
File "/usr/local/lib/python3.10/dist-packages/cuteSV-2.0.2-py3.10.egg/EGG-INFO/scripts/cuteSV", line 862, in main_ctrl
generate_output(args, semi_result, contigINFO, argv, ref_g)
File "/usr/local/lib/python3.10/dist-packages/cuteSV-2.0.2-py3.10.egg/cuteSV/cuteSV_genotype.py", line 287, in generate_output
REF = str(ref_g[i[0]].seq[int(i[2])]),
KeyError: 'hs37d5'
10:10:27 [INFO] ************************* SV CALLING COMPLETED IN 8.516s *************************
10:10:27 [INFO] ************************* SNP PHASING STARTED *************************
[E::idx_find_and_load] Could not retrieve index file for 'results/snp_calling/pileup.vcf.gz'
Could not load .tbi index of results/snp_calling/pileup.vcf.gz: No such file or directory
Traceback (most recent call last):
File "/home/disk2/vivi/.local/bin/duet", line 31, in <module>
main(sys.argv[1:])
File "/home/disk2/vivi/.local/bin/duet", line 25, in main
snp_phasing(args.OUTPUT, args.REFERENCE, args.BAM, args.thread)
File "/home/disk2/vivi/.local/lib/python3.10/site-packages/duet/snp_phasing.py", line 17, in snp_phasing
ctgs = subprocess.check_output(shlex.split('tabix --list-chroms ' + pileup_vcf_path)).decode('ascii').split('\n')[:-1]
File "/usr/lib/python3.10/subprocess.py", line 420, in check_output
return run(*popenargs, stdout=PIPE, timeout=timeout, check=True,
File "/usr/lib/python3.10/subprocess.py", line 524, in run
raise CalledProcessError(retcode, process.args,
subprocess.CalledProcessError: Command '['tabix', '--list-chroms', 'results/snp_calling/pileup.vcf.gz']' returned non-zero exit status 1.
Hi team,
I did check out the Duet preprint, very interesting approach
I've checked out the current algo and seems like the phasing steps were done with 24 chromosomes ?
Is it possible to make some flags to address this ?
Many thanks,
Tuan
It's probably a misguided proposal but is there a way that users can provide a sample_name to be used in place of SAMPLE
in the vcf files? This becomes handy when merging/concatenating vcf files. I know the files can be preprocessed with sed
or similar (cat sample.vcf | sed -e 's/SAMPLE/$filename/'
), but if the variant-calling tools accept a sample name
options, duet
will benefit from that.
Hi author team,
I believe it is of interest to add more sv_caller into duet
File sv_calling.py
, simply inserting:
elif caller == 'sniffles':
os.system('sniffles --input ' + aln_path + ' --reference ' + ref_path + ' --vcf ' + sv_calling_home + 'variants.vcf ' + '--output-rnames' + ' --snf' + sv_calling_home + 'variants.snf ' + ' -t ' + str(thread) + ' --minsvlen ' + str(svlen_thres) + ' --minsupport ' + str(supp_thres))
Obviously, you will need sniffles 2.0.6 install, easily done with conda install -c bioconda sniffles=2.0.6
. I've made a fork in my local cluster & can make a PR if this is worthwhile considering.
With Sniffles it is possible to merge the snf file across multiple samples & do joint calling for maximum discovery of SVs in a big cohort (similar with Clair3 GVCF options). But as Duet is developed as an start-to-end pipeline, it is perhaps tricky to deploy in such cases.
By the way, cute SV has several recent releases - latest version 2.0.2 so you might want to check that out & update accordingly😃
Best,
Tuan
I have been trying your tool on my data and noticed that there is no control for clair3
functions.
By default, Claire only includes the main chromosomes but, from my encounters, the alternative contigs
are also important to some people studying e.g. HLA and KIR.
Here is an example of mapping reads to the human genome reference GRCh38
<"https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_full_analysis_set.fna.gz"
>
samtools idxstats BTB.bam | awk '$3>100 {print $0}'| sort -k3 -n | sed -E '1 i\chr\tlen\t\#mapped\t\#unmapped' | column -t
chr len #mapped #unmapped
chr19_KI270888v1_alt 155532 109 0
chr19_GL949748v2_alt 1064304 124 0
chr18 80373285 160 0
chr19_KI270929v1_alt 186203 169 0
chrX 156040895 175 0
chr15 101991189 179 0
chr21 46709983 185 0
chr19_GL949753v2_alt 796479 193 0
chr16 90338345 197 0
chr22 50818468 204 0
chr20 64444167 207 0
chr19_GL949750v2_alt 1066390 211 0
chr17 83257441 220 0
chr14 107043718 244 0
chr13 114364328 245 0
chr19_GL949749v2_alt 1091841 275 0
chr8 145138636 285 0
chr12 133275309 325 0
chr11 135086622 331 0
chr9 138394717 339 0
chr5 181538259 364 0
chr6 170805979 385 0
chr19_KI270920v1_alt 198005 392 0
chr3 198295559 444 0
chr2 242193529 603 0
chr1 248956422 676 0
chr10 133797422 757 0
chr19_GL000209v2_alt 177381 853 0
chr19_GL949747v2_alt 729520 948 0
chr19_KI270882v1_alt 248807 958 0
chr19_KI270916v1_alt 184516 967 0
chr19_KI270921v1_alt 282224 1009 0
chr19_KI270923v1_alt 189352 1083 0
chr4 190214555 1101 0
chr19_KI270890v1_alt 184499 1190 0
chr19_GL949751v2_alt 1002683 1346 0
chr19_KI270886v1_alt 204239 1400 0
chr19_KI270889v1_alt 170698 1507 0
chr7 159345973 1566 0
chr19_KI270885v1_alt 171027 1732 0
chr19_KI270884v1_alt 157053 1740 0
chr19_KI270918v1_alt 123111 2187 0
chr19_KI270887v1_alt 209512 2528 0
chr19_KI270922v1_alt 187935 2598 0
chr19_KI270938v1_alt 1066800 3104 0
chr19_KI270917v1_alt 190932 3197 0
chr19_GL949752v1_alt 987100 3224 0
chr19_KI270915v1_alt 170665 3668 0
chr19_KI270931v1_alt 170148 3776 0
chr19_KI270891v1_alt 170680 3834 0
chr19_KI270919v1_alt 170701 4387 0
chr19 58617616 4679 0
chr19_KI270930v1_alt 200773 4792 0
chr19_KI270933v1_alt 170537 5592 0
chr19_KI270914v1_alt 205194 6336 0
chr19_KI270932v1_alt 215732 7106 0
chr19_KI270883v1_alt 170399 9526 0
For my installation, I have edited the snp_calling.py
script in my conda env to include --include_all_ctgs
nano ./miniconda3/envs/duet_sv/lib/python3.6/site-packages/duet/snp_calling.py
GNU nano 6.2 ./miniconda3/envs/duet_sv/lib/python3.6/site-packages/duet/snp_calling.py
# coding=utf-8
import logging
import os
import time
def snp_calling(home, ref_path, aln_path, maf, thread):
lines = '*************************'
logging.info(lines + ' SNP CALLING STARTED ' + lines)
starttime = time.time()
snp_calling_home = home + '/snp_calling/'
os.system('mkdir ' + snp_calling_home)
os.system('run_clair3.sh -b ' + aln_path + ' -f ' + ref_path + \
' -m "${CONDA_PREFIX}/bin/models/ont" -t ' + str(thread) + ' -p ont -o ' + snp_calling_home + \
' --snp_min_af=' + str(maf) + ' --pileup_only --call_snp_only --include_all_ctgs')
logging.info(lines + ' SNP CALLING COMPLETED IN ' + str(round(time.time() - starttime, 3)) + 's ' + lines)
It will be great if you can extend input options so as to enable some control for the underlying tools such as Clair3
.
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