Promethease isn’t a bad place to start. I don’t know how it works with uncharacterized variants, but it would be a good place to start.
Note: I do this work for cancer genomes (WGS, tumor and germline). Promethease is not something that I use for annotations, but my workflows are significantly more complex.
The biggest thing I’d look out for is mindset. Biology is very different from comp sci. CS is very deterministic. You change something here, you get a result there. Biology, on the other hand, is very messy. There are compensation mechanisms on top of compensation mechanisms, and everything favors life. If you see a deleterious variant, that still doesn’t mean you’ll see a phenotype (effect on you). It’s quite a different world and can be very scary if you are looking at your own data.
I think the biggest reason it's scary is a statistics literacy problem: everyone has lots of mutations, and a mutation is much more likely to be bad than good. This means that when people look at a Prometheus report and see a long list of deleterious mutations they tend to take it, overall, as bad news: so much red! But since that's what you would expect to see even before looking at the report it shouldn't move your opinion either way.
My prior is that any random variant would likely do nothing. It’s all about location, location, location. First off, a variant would need to be in a gene to do something (not entirely true, but a good enough approximation). Then, the variant would need to be in a coding region/exon. Finally, the variant would need to change the amino acid (there is a Twitter/biorxiv war going on about this specifically now). You have approximately 0.1% unique DNA sequence compared to someone else. But there are 3 billion bp in the human genome. So that’s an expected 3 million variants. And that’s just to start. And just to add to the prior probabilities — you’re probably living, right? So, whatever variants you might find haven’t been lethal yet! (Even better if you’ve made it to adulthood!)
And to complicate things further, one variant in a gene could do nothing if the other copy is still good. Even if you have two bad variants in a single gene, they might be on the same allele (from the same parent). In which case, you still have one good copy! It’s like how Iceman got hit twice in the same engine at the end of the original Top Gun. He still had one good engine to get home. For many genes, that’s all you need. For others, you might not even need one good copy as other genes could take over the same job.
Yes, there are some variants that you don’t want to see. Things that might indicate high likelihood of disease down the road. But even that is bound by statistical probabilities. Good news — some of those can’t be seen by this type of sequencing.
You’re absolutely right though — it can be scary. After looking at many genomes, it can be amazing that we all work as well as we do.
Note: I do this work for cancer genomes (WGS, tumor and germline). Promethease is not something that I use for annotations, but my workflows are significantly more complex.
The biggest thing I’d look out for is mindset. Biology is very different from comp sci. CS is very deterministic. You change something here, you get a result there. Biology, on the other hand, is very messy. There are compensation mechanisms on top of compensation mechanisms, and everything favors life. If you see a deleterious variant, that still doesn’t mean you’ll see a phenotype (effect on you). It’s quite a different world and can be very scary if you are looking at your own data.