![]() ![]() This option produces an estimate of ΦPT, an analogue of FST. To suppress within population variance and simply calculate population differentiation based on the genotypic variance, choose Codom-Genotypic distance. Consequently, estimation of RST is often not useful. Note, RST should not be your default option for microsatellites, because the underlying assumptions of simple step-wise mutation rarely hold in natural populations. To estimate RST for microsatellites, choose Codom-Microsat. To estimate FST for codominant data, choose the Codom-Allelic distance. Within GenAlEx (FREE SOFTWARE), the data type and choice of distance calculation used as input for AMOVA lead to related but different analyses. 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. 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. 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. This is something automatically done with the YHRD AMOVA/MDS tool, and one will have to to do something parallel with Arlequin. allelic duplications), etc have to be removed prior to analyses. DYS458*18.2, etc), and (c) multi-allelic patterns (e.g. To start with, all those haplotypes with (a) null alleles, (b) partial alleles (e.g. Hello, to start with Rst calculations might be a bit problematic with Y-STRs for a number of reasons. But mostly ongoing geneflow from yellow to red, while red and blue have their most frequent, and therefore ancestral, haplotypes not shared. There seems to be geneflow because most haplotypes are connected across population. ![]() ![]() Looks like a pool of migrants from different locations. The black one is odd, only rare distantly related haplotypes scattered across the network. Same holds for the red and blue population. This pattern usually indicates an old population with one or a few ancestral haplotypes and lots of rare derivates split from them by mutation. Then you have a bunch of distantly related rare haplotypes, the small yellow nodes at the edge of the network. With respect to your yellow population, you find three closely related frequent haplotypes in the middle, which are shared with the red population. ![]() That means more distant nodes are more distantly related (more bp difference) haplotypes. The lengths of the lines connecting the haplotypes refer the distance of relatedness with the numbered steps usually representing one bp change per step. Each node represents a unique mtDNA sequence haplotype with the colour denoting the population where it is found and the size of the circle accounting for its frequency. Each colour represents a population (location?). ![]()
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