Closed aababc1 closed 7 months ago
Hi, sorry to hear you had this issue. I have done some troubleshooting and have changed what appears to be the likely issue. However, as I have not reproduced your error, I'm not 100% sure if it will work. If possible, please use the oor_error branch, commit 62e35aa and let me know if this rectifies the problem.
Thank you for your prompt reply.
You mentioned that you cannot reproduce error, can you tell me the detail environment(tools and their version ) of ggcaller execution ?
I read your reply and adapt your instruction by switching the graph.cpp file. As your expectation issue seems to be resolved in Scoring ORF clusters step . .
In the core genome alignment step, issue was generated. I allocated 1terabytes of memory to do ggcaller job.
Is this error caused by memory shortage or do I have to adjust code or execution environment. Thank you very much.
$ time ggcaller --refs 1380list --clean-mode moderate --alignment core --core-threshold 0.9 --threads 80 --out ggcallertest& [1] 63929 Building coloured compacted DBG... Generating graph stop codon index... Mapping contigs to graph... Loading gene models... Traversing graph to identify ORFs... |██████████████████████████████████████████████████| 100% Generating clusters of high-scoring ORFs... Scoring ORF clusters... |██████████████████████████████████████████████████| 100% Identifying high-scoring ORFs... |██████████████████████████████████████████████████| 100% Generating initial network... Processing paralogs... 100%|████████████████████████████████████████████████████████████████████████| 365/365 [01:17<00:00, 4.71it/s] collapse mistranslations... Processing depth: 1 Iteration: 1 100%|████████████████████████████████████████████████████████████████| 219596/219596 [00:52<00:00, 4202.88it/s] Iteration: 2 100%|██████████████████████████████████████████████████████████████████| 13941/13941 [00:07<00:00, 1826.03it/s] Iteration: 3 100%|████████████████████████████████████████████████████████████████████| 8828/8828 [00:02<00:00, 3041.83it/s] Iteration: 4 100%|████████████████████████████████████████████████████████████████████| 1801/1801 [00:00<00:00, 2944.91it/s] Iteration: 5 100%|██████████████████████████████████████████████████████████████████████| 196/196 [00:00<00:00, 2469.51it/s] Iteration: 6 100%|██████████████████████████████████████████████████████████████████████████| 8/8 [00:00<00:00, 1694.07it/s] Iteration: 7 100%|█████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 44150.57it/s] Processing depth: 2 Iteration: 1 100%|████████████████████████████████████████████████████████████████| 151200/151200 [00:31<00:00, 4735.54it/s] Iteration: 2 100%|████████████████████████████████████████████████████████████████████| 2952/2952 [00:02<00:00, 1281.83it/s] Iteration: 3 100%|████████████████████████████████████████████████████████████████████████| 65/65 [00:00<00:00, 1112.43it/s] Iteration: 4 100%|██████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 1045.90it/s] Iteration: 5 100%|██████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1272.16it/s] Processing depth: 3 Iteration: 1 100%|████████████████████████████████████████████████████████████████| 147706/147706 [01:40<00:00, 1466.66it/s] Iteration: 2 100%|███████████████████████████████████████████████████████████████████████| 508/508 [00:01<00:00, 322.17it/s] Iteration: 3 100%|████████████████████████████████████████████████████████████████████████| 11/11 [00:00<00:00, 1053.00it/s] Iteration: 4 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 398.27it/s] Iteration: 5 100%|███████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 182.08it/s] annotating gene families... collapse gene families... Processing depth: 1 Iteration: 1 100%|████████████████████████████████████████████████████████████████| 147151/147151 [00:58<00:00, 2528.31it/s] Iteration: 2 100%|███████████████████████████████████████████████████████████████████| 12511/12511 [00:15<00:00, 805.53it/s] Iteration: 3 100%|█████████████████████████████████████████████████████████████████████| 7169/7169 [00:10<00:00, 689.31it/s] Iteration: 4 100%|█████████████████████████████████████████████████████████████████████| 3739/3739 [00:05<00:00, 669.09it/s] Iteration: 5 100%|█████████████████████████████████████████████████████████████████████| 1584/1584 [00:02<00:00, 692.07it/s] Iteration: 6 100%|███████████████████████████████████████████████████████████████████████| 696/696 [00:00<00:00, 803.60it/s] Iteration: 7 100%|███████████████████████████████████████████████████████████████████████| 417/417 [00:00<00:00, 904.32it/s] Iteration: 8 100%|███████████████████████████████████████████████████████████████████████| 248/248 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11 100%|███████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 257.47it/s] trimming contig ends... refinding genes... Number of searches to perform: 17245438 Searching... translating hits... Updating output... Number of refound genes: 824980 collapse gene families with refound genes... Processing depth: 1 Iteration: 1 100%|██████████████████████████████████████████████████████████████████| 35959/35959 [00:17<00:00, 2074.54it/s] Iteration: 2 100%|█████████████████████████████████████████████████████████████████████████| 32/32 [00:00<00:00, 423.63it/s] Processing depth: 2 Iteration: 1 100%|███████████████████████████████████████████████████████████████████| 35925/35925 [01:06<00:00, 539.30it/s] Iteration: 2 100%|████████████████████████████████████████████████████████████████████████████| 9/9 [00:00<00:00, 26.29it/s] Processing depth: 3 Iteration: 1 100%|████████████████████████████████████████████████████████████████████| 35916/35916 [09:06<00:00, 65.72it/s] Iteration: 2 100%|██████████████████████████████████████████████████████████████████████████| 81/81 [00:05<00:00, 13.97it/s] Iteration: 3 100%|████████████████████████████████████████████████████████████████████████████| 7/7 [00:01<00:00, 6.42it/s] Iteration: 4 100%|████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 6.09it/s] writing Roary output... writing GFF files... writing gene fasta... generating core genome MSAs... Exception in thread Thread-1: Traceback (most recent call last): File "miniconda3/envs/ggcaller134/lib/python3.9/threading.py", line 980, in _bootstrap_inner self.run() File "miniconda3/envs/ggcaller134/lib/python3.9/threading.py", line 917, in run self._target(*self._args, **self._kwargs) File "miniconda3/envs/ggcaller134/lib/python3.9/multiprocessing/pool.py", line 513, in _handle_workers cls._maintain_pool(ctx, Process, processes, pool, inqueue, File "miniconda3/envs/ggcaller134/lib/python3.9/multiprocessing/pool.py", line 337, in _maintain_pool Pool._repopulate_pool_static(ctx, Process, processes, pool, File "miniconda3/envs/ggcaller134/lib/python3.9/multiprocessing/pool.py", line 326, in _repopulate_pool_static w.start() File "miniconda3/envs/ggcaller134/lib/python3.9/multiprocessing/process.py", line 121, in start self._popen = self._Popen(self) File "miniconda3/envs/ggcaller134/lib/python3.9/multiprocessing/context.py", line 277, in _Popen return Popen(process_obj) File "miniconda3/envs/ggcaller134/lib/python3.9/multiprocessing/popen_fork.py", line 19, in init self._launch(process_obj) File "miniconda3/envs/ggcaller134/lib/python3.9/multiprocessing/popen_fork.py", line 66, in _launch self.pid = os.fork() OSError: [Errno 12] Cannot allocate memory
Hi, this looks like it's an issue with python multiprocessing. I would suggest running with fewer (~40) threads.
Thank you for your reply.
I found out that when ggcaller is terminated. the jobs remaining S in job queue consuming memory.
Memory usage is rolled back when ggcaller jobs in sleeping were terminated.
OOM(out of memory ) error cause abrupt termination of program (making jobs sleeping ) or , dose it intended action for rerunning the sleeping jobs? regarding this error and real adoption of ggcaller, I got 3 questions.
1 . I wonder how to prevent teminated jobs from going into sleeping. (also could you give me the real execution environment of ggcaller ? - OS, python, python library versions of etc.., )
I look forward your answer. Thank you very much.
===============================
time ggcaller --refs 1380list --clean-mode moderate --alignment core --core-threshold 0.9 --threads 40 --out ggcallertest
Building coloured compacted DBG...
Generating graph stop codon index...
Mapping contigs to graph...
Loading gene models...
Traversing graph to identify ORFs...
|██████████████████████████████████████████████████| 100%
Generating clusters of high-scoring ORFs...
Scoring ORF clusters...
|██████████████████████████████████████████████████| 100%
Identifying high-scoring ORFs...
|██████████████████████████████████████████████████| 100%
Traceback (most recent call last):
File "miniconda3/envs/ggcaller134/bin/ggcaller", line 33, in
Hi, to answer your questions:
mamba info --envs
. --clean-mode strict
to enable stringent prediction filtering.Hi, Thank you for your kind answer. I get your suggestions and explanations. Thank for the details.
Couple of things to mention regarding the last post. At first, I requested "your" ggcaller execution environment.
The conda installation of ggcaller 1.3.4 version is not runnable in our server (Centos7.9). So, I proceeded manual source compilation of your tool by git cloning and python setup following your instruction on github documentation.
But there something would be good if things are clarified. In the file https://github.com/samhorsfield96/ggCaller/blob/master/environment_linux.yml , the versions of python packages are not explicitly represented. In my experience, conda tries to download recent version packages if versions are not specified elsewhere.
I've encountered many errors due to numpy, pandas or etc while utilizing several other tools. (numpy <1.24 , numpy >= 1.24 , usage of different package version leads to run error. ) . Because the conda installation did not work for me (new environment creation for ggcaller by mamba create -n ~~~~ ,following the code on github), and you said you could not reproduce such errors. I requested your exact execution environment (python, numpy, pandas, networkx ~~ etc) of ggcaller to find out any potential incompatibility.
If you don't mind, I want to know your packages and tools version related with ggcaller. I think specifying versions of package would resolve errors regarding conda installation .
Thank you very much for your quick response and your valuable answers, I'll look into it.
Hi, we have found explicitly specifying versions for all packages can cause issues with incompatibility, therefore we choose only to do this in specific cases where it is warranted.
Please see the attached file for package versions for a working ggCaller environment. ggc_env_v1.3.4_packages.txt
Hi. Thank you. I got your point.
Best regards and many thanks.
Closed as resolved.
Hi thank you for your nice tool. I've encountered problem while using ggcaller v1.3.4. (error log is below the description part ) I created conda environment and installed ggcaller following official instruction . Test run with small number of genome (10) was very successful.
Hardware memory is 2TB. I guess it would not be caused by memory shortage. OS is centos 7.9 also all input files are raw genomic fasta files that is without Ns (1380 files).
Do I have to set any specific system variable? Could you provide any help for this situation ? Thank you .
time ggcaller --refs 1380list --out Bacteroids_uniformis --clean-mode moderate --alignment core --core-thresh old 0.9 --threads 80
Building coloured compacted DBG... Generating graph stop codon index... Mapping contigs to graph... Loading gene models... Traversing graph to identify ORFs... |██████████████████████████████████████████████████| 100% Generating clusters of high-scoring ORFs... Scoring ORF clusters... |████████████ | 25%terminate called after throwing an instance of 'std::out_of_range' what(): key not found Aborted
real 346m12.060s user 7820m31.364s sys 178m3.927s
created files till error are two . 572M 2023-11-24 07:25 1380list.color.bfg 440M 2023-11-24 07:25 1380list.gfa
here is the conda env list.
miniconda3/envs/ggcaller134: #
Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 2_kmp_llvm conda-forge alsa-lib 1.2.10 hd590300_0 conda-forge argcomplete 3.1.6 pyhd8ed1ab_0 conda-forge argh 0.30.4 pyhd8ed1ab_0 conda-forge attr 2.5.1 h166bdaf_1 conda-forge bcbio-gff 0.7.0 pyh7cba7a3_0 bioconda bifrost 1.3.1 h43eeafb_0 bioconda binutils 2.40 hdd6e379_0 conda-forge binutils_impl_linux-64 2.40 hf600244_0 conda-forge binutils_linux-64 2.40 hbdbef99_2 conda-forge biopython 1.80 py39hb9d737c_0 conda-forge blast 2.15.0 pl5321h6f7f691_1 bioconda boost-cpp 1.82.0 h44aadfe_6 conda-forge brotli 1.1.0 hd590300_1 conda-forge brotli-bin 1.1.0 hd590300_1 conda-forge bx-python 0.10.0 py39h31164c1_0 bioconda bzip2 1.0.8 hd590300_5 conda-forge c-ares 1.22.1 hd590300_0 conda-forge c-compiler 1.6.0 hd590300_0 conda-forge ca-certificates 2023.11.17 hbcca054_0 conda-forge cairo 1.18.0 h3faef2a_0 conda-forge cd-hit 4.8.1 h43eeafb_9 bioconda certifi 2023.11.17 pyhd8ed1ab_0 conda-forge cffi 1.16.0 py39h7a31438_0 conda-forge cmake 3.27.8 hcfe8598_0 conda-forge colorama 0.4.6 pyhd8ed1ab_0 conda-forge contourpy 1.2.0 py39h7633fee_0 conda-forge curl 8.4.0 hca28451_0 conda-forge cxx-compiler 1.6.0 h00ab1b0_0 conda-forge cycler 0.12.1 pyhd8ed1ab_0 conda-forge dbus 1.13.6 h5008d03_3 conda-forge diamond 2.1.8 h43eeafb_0 bioconda eigen 3.3.9 h4bd325d_1 conda-forge entrez-direct 16.2 he881be0_1 bioconda expat 2.5.0 hcb278e6_1 conda-forge font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge font-ttf-inconsolata 3.000 h77eed37_0 conda-forge font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge font-ttf-ubuntu 0.83 hab24e00_0 conda-forge fontconfig 2.14.2 h14ed4e7_0 conda-forge fonts-conda-ecosystem 1 0 conda-forge fonts-conda-forge 1 0 conda-forge fonttools 4.45.1 py39hd1e30aa_0 conda-forge freetype 2.12.1 h267a509_2 conda-forge future 0.18.3 pyhd8ed1ab_0 conda-forge gawk 5.3.0 ha916aea_0 conda-forge gcc 12.3.0 h8d2909c_2 conda-forge gcc_impl_linux-64 12.3.0 he2b93b0_3 conda-forge gcc_linux-64 12.3.0 h76fc315_2 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