Compute the z-score (and more) for admixed hypotheses
profile_admixture(x0, df, hyp = NULL, grouping = "meta",
return_all = FALSE, calc_logP = TRUE, ...)A data frame/tibble with two columns: `locus` and `x0`
A tibble of reference profiles (as for `genogeo`)
If NULL all levels of `grouping` is crossed and looped over as pairwise hypotheses. If a single level of `grouping`, this value is crossed with the remaining levels. If vector of two levels this is the only tested hypothesis.
Should the calculations be for meta populations ("meta") or sample populations ("pop")?
Should z-score be returned (FALSE) or all locus results (TRUE)?
Should log P(Geno|Hyp) be calculated (TRUE) or not (FALSE)?
additional arguments passed on to other functions
A tibble of z-scores, or a list of pairwise results if `return_all = TRUE`