Closed alexkrohn closed 2 years ago
There are only 2 imputation methods at the moment "sample" and "kmeans", both of these use information about allele frequencies within groups, so setting setting mincov
, which is global` would break their function, so I'm afraid there's not a way to do what you want. Unless I don't understand well.
Since this is more of a question about operation, rather than a bug or feature request it would be better to put these kinds of things in the gitter channel in the future: https://gitter.im/dereneaton/ipyrad. You might check out a conversation I had there within the last week with @bmichanderson who wanted to do something remarkably similar to what you are trying to do. And I had some thoughts for him there that you might find useful.
Got it. I didn't know about the gitter channel -- I will go there next time. Thanks.
I agree with your thoughts that a low mincov
might be dangerous. In order to get around the minmap
argument, though, it sounds like I'd just have to lump the single-individual populations into another population, or remove them.
Is there a way to not use the
minmap
filtering threshold in the PCA and Structure analyses included with ipyrad? I really like the imputation functions in your analysis tools, so I want to use them. However, I have some individuals that have high amounts of missing data and are one of 1-2 individuals in a population, thus they cause a lot of SNPs to be filtered at the minmap step. Is it possible to filter only withmincov
?I've tried setting
minmap
to 0 or NaN, and not includingminmap
in the PCA call, but both yield errors. Any thoughts?