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Contigs binning -marker genes/hmmout problem
Hi @anuradhawick,
I am running LRBinner for ONT contigs generated from metaFlye. I would like to bin the contigs and come across this tool for binning of long reads data, however, I am running in the error indicating a missing file.
Could please give a helping hand on how to solve the problem?
Best, Nafi'u
here is the command I ran and error produced command: /tools/LRBinner/lrbinner.py contigs --reads-path Porechop/sample01.fastq --contigs final_assembly/sample01.assembly.fasta --output binning/
2024-02-27 14:29:48,189 - INFO - Computing contig lengths
2024-02-27 14:29:48,245 - INFO - Searching for marker genes
Traceback (most recent call last):
File "/lustre/groups/comi/tools/LRBinner/lrbinner.py", line 203, in
FileNotFoundError: [Errno 2] No such file or directory: '07_binning/marker_genes/contigs.hmmout'
Hi thanks for getting in touch.
Could you check if these are available in your system?
- fraggenescan 1.31
- hmmer 3.3.2
Hi @anuradhawick ,
Thank you for getting back to me.
I managed to run it successfully after installing the tool using conda. However, I have one more issues that I would like to clarify with you. I used metabat2 for binning of one sample and generated 7 bins. Later, this tool started running and produced only two bins from the same sample. Do you know any reason behind generating few bins compared to the software not designed purposely for binning of long reads sequences?
Best, Nafi'u
I think LRBinner can give lesser number of bins for assemblies because I have not designed it for binning contigs.
On the other hand, contigs binning tools may have heuristics more applicable for contigs like accuracy. If it's using marker genes long reads might mislead the binner too.
Thank you for the information. May I know if you know/have any other tool for binning of assemblies from long reads?
Maybe tools designed specifically for long reads binning would give a better genomes in terms of quality.
Thanks
You could try this
https://github.com/metagentools/MetaCoAG
Thank you for your response and recommendation.
On Thu, 21 Mar 2024 at 12:08, Anuradha @.***> wrote:
You could try this
https://github.com/metagentools/MetaCoAG
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