DivNet on rRNA gene counts derived from metagenomes? about divnet HOT 7 OPEN

Hi there,

I also have a similar question and just wanted to boost this!
I'm working with RNAP (B and B' subunit genes separately) which are single-copy markers, so I don't have to worry about copy-numbers skewing thigns, but I'm wondering how the diversity calculations are implemented and interpreted with metagenomic data in which the whole composition of the single-gene community only accounts for a very small portion of the reads/members of the community - in other words, their relative abundances will not sum to 1?

Thanks,
Alaina :)

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@scubalaina I have used DivNet in a similar way to you. When you are running it on the subcommunity (ie just the rna pol seqs) you are passing the data to DivNet as counts right? If so, it will go through its process treating that as samples/community in the right way.

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@scubalaina something to keep in mind about normalizations ...you will be changing the read counts which could have an affect on variance estimations. Check out this tiny example. It's a silly contrived example where each gene has the same gene length, but the counts are still normalized by the gene length (ie reducing the count equally for all sample/genes in this particular example, and so increasing the variance). Of course this is just a silly example, but the point is that normalizing could impact variance estimations. Though, in practice, I'm not sure how much of an issue it will be. Someone from the Willis lab will have to comment on that.

One other thing if you're doing some normalization, you could think of a gene in a sample that has a low count like 2, but it is a 4kb gene, so its "per kilobase" count would be 0.5. Depending on your choice of pseudocount (for example, 0.5 was chosen in the DivNet manuscript for the analysis) that could be around the sam as that normalized count. Another thing to keep in mind.

divnet_rpk_variance.R.txt

(Not relevant to this discussion, but I work in a viral ecology lab, so I know some of your papers! Just a cool coincidence 😄)

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I wonder how one could avoid compromising variance calculations without overestimating the abundance of longer genes if gene length isn't accounted for?

^ Yeah, that's a good question...as far as I know that is still an open research question. Someone from the Willis lab will have to weigh in here.

I attached the example below

^ I think you may have forgotten the attachment...I'm not seeing it.

(Yep in Wommack's lab...small world haha!)

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Hi Ryan,

Sorry I was corresponding via email so the attachment probably didn't work through github. Here it is!

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