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abyzovlab / CNVpytor

a python extension of CNVnator -- a tool for CNV analysis from depth-of-coverage by mapped reads
MIT License
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Eval1 #192

Closed zainabae closed 1 year ago

zainabae commented 1 year ago

Hello, I am curious to know if using the -chrom option in cnvpytor will cause the eval1 output to be the result of multiplying the p-value with the size of the autosomes divided by the bin size, or if it will use the whole genome size instead.

arpanda commented 1 year ago

During RD step, if too few chromosomes are provided, it will impact the global statistics.

zainabae commented 1 year ago

During RD step, if too few chromosomes are provided, it will impact the global statistics.

I'm selecting 36 autosome In this case:

the eval1 = autosomes size * p- value / bin size

Or eval1 = whole genome size * p-value /bin size ?

suvakov commented 1 year ago

We always assume the human genome in this formula, with genome_size=2.9e9. When using cnvpytor from Python, you can adjust the genome size by specifying it as an argument: Root.call(..., genome_size=2.9e9). Alternatively, you can adjust that column manually. Thanks for pointing this out. In the future, we should determine this based on the reference genome size.

zainabae commented 1 year ago

We always assume the human genome in this formula, with genome_size=2.9e9. When using cnvpytor from Python, you can adjust the genome size by specifying it as an argument: Root.call(..., genome_size=2.9e9). Alternatively, you can adjust that column manually. Thanks for pointing this out. In the future, we should determine this based on the reference genome size.

Thank you for the quick and informative response 👍🏻 And this is applied even when using non-human organism genome?

suvakov commented 1 year ago

Yes, it is hard coded in current version.