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cnv detection in cow

Hi

I want to get cnv for cow. I used cnv-facet and cnvpytor for this. But if I understand correctly these are designed for humans and I didn't get any response. What do you suggest for me? Or with what changes can I use these for cow?

Thanks for your guidance

cow cnv

1 answer

CNV detection tools like cnv-facet and cnvpytor (which is a python wrapper of CNVnator) have been successfully deployed on many different non-model species. I've used CNVnator on a diploid fish species without any problems. Whilst assumptions about data quality might differ in non-model species, you should be fine with cow which has chromosome level assemblies.

If you're not getting any results I suspect there is an issue with the quality of your data, a mistake in the data processing, or you haven't followed the instructions correctly. Impossible to say without any detail.

Some things that may be useful to know:

  1. What is your input data? (Platform, depth, etc...)
  2. How have you processed/cleaned the data?
  3. What reference genome are you using?
  4. What does the run log say?
  5. If everything looks good until here, then maybe we should look at the commands you used.

Thank you very much for your answer. My data is wgs and my input file was a bam file. And I run the command and it stopped at length 1034!

cnvpytor -root file.pytor -rd 478m.sorted.bam -T genome.fa

and I received this response.

  • cnvpytor.root - INFO - Reading data for chromosome NKLS02001987.1 with length 1034 was killed

I've not gotten that error before, but I would be wary of a chromosome that is only 1kb. You're not going to get any meaningful results with really small reference contigs. I think you might need some filtering of your reference genome (as well as your input data if you've not already done that).

Can I see the steps to prepare your data for use in cnvpytor? After mapping with bwa, I convert the sam file to bam, sort and index it. Of course, this is the first time I've done cnv. But I've done other analyses. Thank you.

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