Tim Millar

SGTM also, but this may require some re-working of the `identity_by_state` and `Weir_Goudet_beta` methods if/when windowing is required.

Thanks for looking into this @tszfungc! I think this could be a great approach for imputing `call_dosage` and `call_genotype_probability`. However, I don't think it will produce the desired result for...

@jeromekelleher the trade-off between returning new variables or replacing existing variables was previously discussed in https://github.com/pystatgen/sgkit/pull/308#issuecomment-705706571. I personally have a slight preference for replacing existing variables but there are some...

I think it's good to go, merging

I'm also interested in codebraid+jupytext but I'm not sure I have quite the same use-case as @teucer My use-case is leveraging jupytexts command-line tools to convert scripts (.py, .R, .sh...

Thanks @eric-czech, I missed the uses in regenie and the bgen reader. I can have a look at merging these variables when I get a chance. A couple of related...

I guess the issue with using `span_normalise` to alter the output is that any downstream methods can't determine if and how a variable has been normalised. So it's not safe...

Looking into this it's not completely clear to me what should be reported as the base length of each window. If we use the `window_start` and `window_stop` indices to calculate...

> Should the window functions add a `window_base_length` variable? Just a thought, would it be worth adding `window_base_start` and `window_base_stop` instead? That would allow a more direct translation to and...

> implying the call are unphased I'm not quite following this. Do you mean that within a single sample in which copy number is variable across a single chromosome, the...