10/29/2023 0 Comments Gene construction kit error 199Then you have a bunch of distantly related rare haplotypes, the small yellow nodes at the edge of the network. This pattern usually indicates an old population with one or a few ancestral haplotypes and lots of rare derivates split from them by mutation. Same holds for the red and blue population. The black one is odd, only rare distantly related haplotypes scattered across the network. Looks like a pool of migrants from different locations. There seems to be geneflow because most haplotypes are connected across population. But mostly ongoing geneflow from yellow to red, while red and blue have their most frequent, and therefore ancestral, haplotypes not shared. Hello, to start with Rst calculations might be a bit problematic with Y-STRs for a number of reasons. To start with, all those haplotypes with (a) null alleles, (b) partial alleles (e.g. DYS458*18.2, etc), and (c) multi-allelic patterns (e.g. allelic duplications), etc have to be removed prior to analyses. This is something automatically done with the YHRD AMOVA/MDS tool, and one will have to to do something parallel with Arlequin. This would still be fine with some population datasets, but consider a population with a higher frequency of partial alleles, say Semitic populations with the DYS458*.2 variants, which mostly correlate with te J1 haplogroup, and which may make up to nearly 50% of the given population if not more. Do you really want to cut the population dataset in half or even more prior to the Rst analysis, even if this would mean cutting out perhaps the most relevant haplogroup for such populations? Alternatively one can remove the entire DYS458 locus which would be a more conservative approach, but which would in turn reduce the data resolution. In our hands, Nei's DA distance based estimate and visualisation via phylogenegtic trees and MDS plot seem to yield more reliable results with Y-STR datasets, though we still do calculate Rst at times, and only after cutting down our datasets to reduce above explained 'Rst unfriendly data' As a result of problems like these and others, we moved to the use of Spagedi software for Rst calculations at one point, and ultimaly we now normally prefer to do allele frequency-based Nei's DA distance calculations instead of Rsts. Within GenAlEx (FREE SOFTWARE), the data type and choice of distance calculation used as input for AMOVA lead to related but different analyses. To estimate FST for codominant data, choose the Codom-Allelic distance. To estimate RST for microsatellites, choose Codom-Microsat. Note, RST should not be your default option for microsatellites, because the underlying assumptions of simple step-wise mutation rarely hold in natural populations. Consequently, estimation of RST is often not useful. To suppress within population variance and simply calculate population differentiation based on the genotypic variance, choose Codom-Genotypic distance. This option produces an estimate of ΦPT, an analogue of FST.
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