Long time no see…
It’s been about two years since my last writing here on Vinland Shore. It’s been some time since I’ve bothered to welcome myself into the fold of sociopolitical, and commentary on the decline of the western world. However, I digress. I’ve been delving into another of a range of my interests, including writing in other capacities, artwork and language.
I recently had some Genetic testing done for the sake of my own curiosity. Using the AncestryDNA service primarily in addition to some online databases, in particular. While I found AncestryDNA is decidedly vague in analyzing your autosomal results. Although it is broadly accurate over populations it won’t satisfy those of you that are more interested in a deeper understanding of your own ancestry. There are a number of other sources that will compare your results against databases to give you a more accurate representation, in a regional breakdown of your ancestry.
One of these tools being GEDmatch which has numerous calculators for comparing rawDNA.
Below is an example of my ancestry results reflected by the MDLP K16 calculator 4-way Oracle developed by Alexandr Burnashev.
Using 1 population approximation:
1 English_Kent @ 2.153893
2 French_WestFrance @ 2.597180
3 Irish_Connacht @ 2.661182
4 English_Cornwall @ 2.820211
5 Scottish_Highlands @ 3.143058
6 Scottish_Grampian @ 3.287263
7 Irish_Ulster @ 3.343463
8 Scottish_Dumfries_Galloway @ 3.406949
9 Irish_Cork_Kerry @ 3.498379
10 Shetlandic_Shetland_Islands @ 3.502238
11 Irish_Leinster @ 3.532630
12 Scottish_Borders @ 3.822586
13 Scottish_Fife @ 3.838847
14 English_England @ 3.840620
15 Irish_Munster @ 3.984138
16 French_France @ 4.400902
17 Orcadian_Orkney_Islands @ 5.297052
18 Scottish_Argyll_bute @ 5.399024
19 Welsh_Wales @ 5.700744
20 Dutch_Netherlands @ 5.923079
Using 2 populations approximation:
1 50% English_Kent +50% French_WestFrance @ 1.811171
Using 3 populations approximation:
1 50% English_Kent +25% German_Germany +25% Scottish_Argyll_bute @ 1.591279
The results are listed in a rank-ordered plot, of closest approximate populations from the respective regions of Europe. Then divided into two, and three population correlations relative to my personal results. These results fall correctly in line with my Genealogical research from my family tree in proportional representation located there.
There are many additional tools, available through GEDmatch. While I won’t be discussing all of them in this post the eye colour prediction system I’ve found interesting. My results, along with an actual image of my eye colour is shown below.
Eye Colour Prediction
In addition the relevant SNPs (single nucleotide polymorphisms) and the position of the alleles attached therein. Whether being homozygous or heterozygous.
The accuracy of this particular test is debated, and I’ve seen others results that are not as true to their real-world eye colour, but I find them to be interesting none the less.
As well another resource although this second one is that of a private geneticist Lukasz Macuga available at lm-genetics which is available for 8,5 Euro or 10 USD. This provides access to one of the largest databases of population averages, and unlike the other available oracles like the one shown above, the reports available at lm-genetics give a much more region-specific output of your specific genetic data. It is also worth noting that the databases that Lukasz has available are more complete in whole than any commercial test currently available.
With additional correlations map Admix4 oracle, and plots (PCA and MDS) and dendrogram.
Below is an ancestral correlations map in the graphical representation of data followed by the populations distributed by rank ordered correlations
1 Cumbria 0,97522
2 Northern Ireland 0,97063
3 FR_West 0,96393
4 Orkney 0,96361
5 Wales 0,96231
6 England_North-East 0,961
7 England_North-West 0,96026
8 NL_Noord_Brabant 0,95851
9 Ireland 0,95822
10 England_South-West 0,95721
11 England_South-East 0,95707
12 Shetlands 0,95596
13 Scotland 0,95272
14 FR_North-West 0,95137
15 FR_Brittany 0,947
16 NL_Zuid_Holland 0,94522
17 Flemish 0,94037
18 NL_Overijssel 0,93878
19 DE Niedersachsen 0,93803
20 NL_Limburg 0,93725
Using 2 populations approximation:
1 Niedersachsen+FR_Brittany @ 5,044322
2 NL_Drenthe+FR_Brittany @ 5,159992
3 Niedersachsen+FR_West @ 5,258002
4 NL_Friesland+FR_Brittany @ 5,454768
5 Schleswig-Holstein+FR_Brittany @ 5,494483
Using 3 populations approximation:
1 50% FR_Brittany +25% NL_Drenthe +25% Cumbria @ 4,53065
2 50% FR_West +25% NL_Drenthe +25% Cumbria @ 4,547682
3 50% FR_Brittany +25% Mecklenburg-Vorpommern +25% NL_Drenthe @ 4,556569
4 50% FR_West +25% NL_Drenthe +25% Ireland @ 4,576506
5 50% Cumbria +25% NL_Drenthe +25% FR_Brittany @ 4,630153
The yDNA results I gathered from a prediction service through MorleyDNA. As the AncestryDNA service doesn’t provide results for your yDNA haplogroup specifically. However, it doesn’t mean that it can not be found from your rawDNA results. However, this will not be able to provide you with an accurate representation of the phylogeny of your specific yDNA haplogroup. This is because most commercial autosomal tests do not test for the specific SNP markers associated with your personal branch or haplotype.
A Y-DNA haplogroup is a group of men sharing the same series of mutations on their Y chromosome, which they inherited from a long line of common paternal ancestors. A few new mutations, known as SNP’s, happen every generation, and are passed unchanged to the next generation. Classifying the accumulated SNPs generation by generation make it possible to retrace the genealogical tree of humanity with great accuracy, to detect patterns in the distribution of shared historical lineages and to retrace historical migrations of male lineages. (Hay, 2017 Eupedia)
below is an example of a phylogenetic tree of haplogroup I1
Specifically using the Y-SNP converter, which pulls the available Y-SNP subclades from your autosomal test results. Personally, my most accurate prediction for my yDNA haplogroup is I1. This result isn’t a surprise as it lines up with my Paternal Norman heritage.
below is a distribution map of the yDNA haplogroup I1 throughout Europe sourced from
“Haplogroup I1 is the most common type of haplogroup I in northern Europe. It is found mostly in Scandinavia and Finland, where it typically represent over 35% of the Y chromosomes. Associated with the Norse ethnicity, I1 is found in all places invaded by ancient Germanic tribes and the Vikings. After the core of ancient Germanic civilisation in Scandinavia, the highest frequencies of I1 are observed in other Germanic-speaking regions, such as Germany, Austria, the Low Countries, England and the Scottish Lowlands, which all have between 10% and 20% of I1 lineages”. (Hay, 2017 Eupedia)
This should demonstrate how much you can extrapolate on from a little data. Also, a way for me to share with some of my readers a bit about my genetic history. In the future, I may discuss also some more analysis in regards to ancient populations. The ancient populations I find in particular to be very interesting. There will be more of the same material as my previous writing in the future. I won’t turn this into a genetics blog altogether.
Also, I am 3.25% Neanderthal apparently…