Ancestry discoveries – well, *that’s* interesting!

My Eurogenes K13 breakdown - high level
My Eurogenes K13 breakdown – high level

I’ve had to give up most coffee and all chocolate, because of migraine headaches.

No, I’m not happy about it. The headaches are so much better, but cutting back on those was not my first choice.

I don’t drink alcohol, I don’t smoke anything, and aside from work, I’m running out of vices. Happily, has stepped in to fill that vice void.

GEDmatch is a wondrous thing — I can’t stop laughing about how amazing it is. Very simply, you upload your raw DNA data (that you get from or or some other ancestry DNA service). In a matter of minutes, they parse it all out to tell you what populations your DNA comes from. I’ve spent more hours than I can count, combing through the results. And wonder of wonders, they now have a spreadsheet feature(!) that shows you the “Oracle” breakdown of all your source populations.

That shows you breakdowns by source populations in more detail. The Oracle results show you distances and percentages and the Oracle-4 results give you even more detail around source populations.

You can even choose to see your chromosome makeups.

I ran the numbers the other day, and under the MDLP calculations, I came away with 662 different populations. I studied the list, which was chock-full of all kinds of surprises (including LOTS of Subsaharan Africa DNA). However, it seemed like it might be more “enthusiastic” than is prudent. After a bit more reading online, I discovered that MDLP is not quite as reliable as I’d like. And the Eurogenes calculator was more reliable.

So, of course I re-ran my data through Eurogenes (K13), and I came away with 204 source populations, which seemed more reasonable. But still — all those surprises… including DNA from some of the earliest genomes sequenced, ever. Chances are, we all can trace our DNA back to 7,000 year-old caveman remains with both European and African DNA, but it’s super-cool to see myself connected to that, no matter how distant the connection may be.

The thing that strikes me, as I comb the list of all these DNA influences, is that many of the assumptions I’ve made about my heritage could use some updating. I turned the corner on 50 years, almost a year ago, and I’m thinking more and more about my legacy — what I’ll leave behind me in this world, both while I’m walking around here, and after I’m gone. I’m also thinking about those who have come before me… to see what they may have “left” to me, in terms of personality and character.

I know some are skeptical about the concept of  “cellular memory”, however, intergenerational effects are recognized in terms of emotional resilience and mental health. Plus, recent research has actually shown that daughters inherit corticolimbic circuit attributes from their mothers, and since the biological line from mother to daughter is unbroken, then for sure, women in particular can trace their roots back in a very personal way. Men, too, I’m sure. I just don’t have the research on hand, just now.

I know of one DNA test that looks at mitochondrial DNA — which is passed through the matrilineal line. I think there are patrilineal DNA analyses out there, too — possibly from the same company? And you can trace back your matrilineal heritage, waaaaayyyy back. A friend of mine did that once, and it was very cool hearing about who her foremothers were.

As for me, I’m going to have to do more digging. There are all kinds of surprises in there, for someone who’s always thought of herself in terms of being west-central European — French, German, Italian, Swiss, with a bit of English thrown in for good measure — and not much else.

Turns out, this is my heritage:

Admix Results (sorted):

# Population Percent
1 North_Atlantic 45.35
2 Baltic 21.39
3 West_Med 15.66
4 West_Asian 8.51
5 East_Med 7.49

204 populations found.
13 components mode.

The Baltic, West Asian, and Eastern Mediterranean are big surprises.

And when I dig into the 204 distinct populations, I find a whole lot of surprises. Including many, many Siberian influences, and Eastern European sources, many from along the Volga river. And then there’s the Brahmin from Uttar Pradesh. And Papua. Maasai. Yoruba.

How very cool is that?

And so the quest commences.

GEDmyth – Digging into the past with

My Dodecad V3 Admixture Proportions – some of it’s surprising.

Some who know me are aware that I’m big into genealogy. I come from a fairly connected extended family who have mostly kept in touch with each other, and my relatives have done a fair amount of family history research. History never gets boring for me, and when it has to do with my own lineage, so much the better.

When I was living in Germany from 1985-87, I spent the holidays with my distant relatives in Rohrbach-am-Hahn as well as Freiburg im Breisgau. I’ve also done a fair amount of reading about European history (since that’s where I always assumed that my heritage sprang from), and I’ve collected sufficient details about the gyrations of the European continent, to make sense of things and better place myself in the context of history.


So, of course, I plunged into Traced one line back to a certain “Knight of the Goat”, while others terminated on battlefields in long-forgotten England. And I had my DNA analyzed. That was interesting… albeit a little high-level for my tastes.

What really lit my fire was when I discovered

GEDmatch basically lets you analyze your raw DNA data (from Ancestry or 123-and-me, or some other source) and break it down to see where all you’re really from. It’s free. And it’s maintained by some extremely smart people who provide a lot of explanations and documentation for their own approaches to analysis.

As it turns out, my assumptions about being German-Swiss-Italian-French aren’t entirely accurate. There’s a whole lot of other DNA in there, from places I never – ever – expected to hail from.

Biggest surprise was the  Balochi bloodline. Balochi?! I had to look that one up.

More on that later.

Individual populations aside, the thing that fascinates me, is knowing that I’ve got (give or take) 662 different global populations represented in my DNA. And interestingly, Sub-Saharan Africa has the most frequent presence. Seriously, I need to look up all these people and learn more about them. I’ve got DNA from Pygmies, Kongo, Borneo… even indigenous peoples of Taiwan… and Mixtec. Whoah – I studied them at university. That’s wild… Oh, and of course there’s all the northeastern European stock. Apparently, Ukraine has a strong presence, according to one test. And Bulgaria. And a fair amount of Roma. The Roma piece probably explains a bit about me.

Now, all these different tests have a way of producing slightly different results, so you have to take it with a grain of salt. There’s a lot of overlap, however some results do not synch with each other, so you have to just treat it as a collective work-in-progress. The most valuable thing to me, is how your understanding of who you are and how you’re connected to everyone else can shift from having just a general knowledge that you’re not only from one place, and one place alone.

With 662 different populations represented in my double helix, I clearly have a lot of biological ties to a lot of different peoples. Even folks in the Arctic. And parts of West Asia that I never knew existed — Balochistan, for instance. I’m apparently 16% Balochi. How about that.

I’ll be writing a lot more on this over the coming weeks, and posting my genetic breakdowns, according to different calculators. It’s not only fascinating and stimulating for me to see where my heritage lies, but it’s also got me thinking about all the different ways we fashion the stories, the myths, of our lives… and so derive meaning from the lot of it.

In the end, we’re a lot more connected than we think. And figuring out just how that happens, is one of the things that keeps the wheels in this head turning.

How fun!

GEDMyth – Population Spreadsheet for Dodecad V3

Here’s a list of all the populations associated with my DNA using the Dodecad V3 calculator. Not in order of importance or prevalence – just more or less there.

This is a short list, compared to another I ran earlier that showed 662 different populations, but it’s fun reading, in any case.


  1. Adygei
  2. Altai
  3. Armenian
  4. Armenians_16
  5. Ashkenazi
  6. Ashkenazy_Jews
  7. Assyrian
  8. ASW
  9. Azerbaijan_Jews
  10. Balkans
  11. Balochi
  12. Bedouin
  13. Belorussian
  14. Biaka_Pygmies
  15. Bnei_Menashe_Jews
  16. Brahui
  17. British
  18. British_Isles
  19. Burusho
  20. Buryat
  21. C_Italian
  22. Cambodians
  23. CEU
  24. CHB
  25. CHD
  26. Chinese
  27. CHS
  28. Chukchi_11
  29. Chuvashs_16
  30. Cochin_Jews
  31. Cornwall
  32. Cypriots
  33. Dai
  34. Daur
  35. Dolgan
  36. Druze
  37. Dutch
  38. East_African
  39. Egyptans
  40. Ethiopian_Jews
  41. Ethiopians
  42. Evenk_15
  43. FIN
  44. Finnish
  45. French
  46. French_Basque
  47. French
  48. Georgia_Jews
  49. Georgians
  50. German
  51. GIH
  52. Greek
  53. Han
  54. Hazara
  55. Hezhen
  56. Hungarians
  57. IBS
  58. Indian
  59. INS
  60. Iranian
  61. Iranian_Jews
  62. Iranians
  63. Iraq_Jews
  64. Irish
  65. Japanese
  66. Japanese
  67. Jordanians_19
  68. Algeria
  69. Bamoun
  70. BiakaPygmy
  71. JPT
  72. Kalash
  73. Kent
  74. Korean
  75. Koryak_15
  76. Kurd
  77. Lahu
  78. Lebanese
  79. Lezgins
  80. Lithuanian
  81. Lithuanians
  82. LWK
  83. Makrani
  84. Mandenka
  85. MAS
  86. Mbuti_Pygmies
  87. Miaozu
  88. Mixed_Germanic
  89. Mixed_Slav
  90. MKK
  91. Mongol
  92. Mongola
  93. Moroccans
  94. Morocco_Jews
  95. Mozabite
  96. N_Italian
  97. Naxi
  98. Nganassan_12
  99. North_African
  100. North_Italian
  101. North_Kannadi
  102. Norwegian
  103. O_Italian
  104. Orcadian
  105. Orkney
  106. Oroqen
  107. Palestinian
  108. Pathan
  109. Polish
  110. Portuguese
  111. Romanians_14
  112. Russian
  113. Russian
  114. S_Italian
  115. S_Italian_Sicilian
  116. Samaritians
  117. San
  118. Sardinian
  119. Saudis
  120. Selkup
  121. Sephardic_Jews
  122. She
  123. Sicilian
  124. Sindhi
  125. Spaniards
  126. Spanish
  127. Swedish
  128. Syrians
  129. TSI
  130. Tu
  131. Tujia
  132. Turkish
  133. Turks
  134. Tuscan
  135. Tuva
  136. Uygur
  137. Uzbekistan_Jews
  138. Uzbeks
  139. Xibo
  140. Yakut
  141. Yemen_Jews
  142. Yemenese
  143. Yizu
  144. Yoruba
  145. YRI
  146. Yukagir
  147. Argyll
  148. Brong
  149. Bulala
  150. Egypt
  151. Fang
  152. Fulani
  153. HADZA
  154. Hausa
  155. Igbo
  156. Kaba
  157. Kongo
  158. Libya
  159. Luhya
  160. Maasai
  161. Mada
  162. Mandenka
  163. MbutiPygmy
  164. Morocco_N
  165. Morocco_S
  166. Mozabite
  167. Sahara_OCC
  168. SAN_NB
  169. SAN_SA
  170. SANDAWE
  171. TUNISIA
  172. Tuscan
  173. Xhosa
  174. Yoruba
  175. !Kung
  176. Alur
  177. AP_Brahmin
  178. AP_Madiga
  179. AP_Mala
  180. Bambaran
  181. Buryat
  182. Dogon
  183. Hema
  184. Iban
  185. Irula
  186. Khmer_Cambodian
  187. Kurd
  188. Kyrgyzstani
  189. Luhya
  190. N._European
  191. Nepalese
  192. Nguni
  193. Pakistani
  194. Pedi
  195. Pygmy
  196. Slovenian
  197. Sotho_Tswana
  198. Stalskoe
  199. Thai
  200. TN_Brahmin
  201. TN_Dalit
  202. Tuscan
  203. Urkarah
  204. Vietnamese
  205. Aonaga
  206. Bhil
  207. Chenchu
  208. Hallaki
  209. Kamsali
  210. Kashmiri_Pandit
  211. Kharia
  212. Kurumba
  213. Lodi
  214. Madiga
  215. Mala
  216. Meghawal
  217. Naidu
  218. Nysha
  219. Sahariya
  220. Santhal
  221. Satnami
  222. Siddi
  223. Srivastava
  224. Tharu
  225. Vaish
  226. Velama
  227. Vysya