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Tuesday, December 6, 2016

Fund-raising offer: Basal-rich K7 and/or Global 10 genetic map


I'm now taking donations for 2017. Anyone who donates $12 USD or $16 AUD, or more, will get the Basal-rich K7 ancestry proportions. Of course, you'll need to send me your genotype data for that to happen (Ancestry.com, FTDNA or 23andMe).

The Basal-rich K7

Please send your non-tax deductible donations via PayPal to eurogenesblog at gmail dot com. E-mail your genotype data to the same address. Please don't assume that I already have your data. I'll try and get back to everyone within a day and will put things on hold if that becomes an unrealistic target.

Using your Basal-rich K7 ancestry proportions, I'll show you where you cluster in the new and improved Fateful Triangle. Many people will probably land somewhere along the cline made up of Late Neolithic/Early Bronze Age Europeans and Middle/Late Bronze Age steppe herders and warriors. This, to me, looks like a cline produced by the expansion of early Indo-Europeans into Western and Central Europe.


For an extra donation of $16 USD or $21 AUD, those of you feeling more adventurous will also receive the Global 10 genetic map, and, more importantly, coordinates for ten dimensions.

A fresh look at global genetic diversity

The Basal-rich K7 is the best ancient ancestry test that I've been able to come up with. It correlates strongly with latest research reported in scientific literature. And, in fact, in some instances it probably trumps latest scientific literature.

For instance, Broushaki et al. 2016 characterized Early Neolithic farmers from the Zagros Mountains, Iran, as 62% Basal Eurasian and 38% Ancient North Eurasian-related (Figure S52). This, considering formal statistics like the D-stat below, with AfontovaGora3 (AG3) as the ANE proxy, is unlikely to be correct, despite the fact that AG3 is a relatively low quality sample.

D(Yoruba,Iran_Neolithic)(Villabruna,AfontovaGora3) 0.0223 Z 2.812

On the other hand, the Basal-rich K7 models the early Zagros farmers as 39.05% Ancient North Eurasian and 56.67% Basal-rich (which is probably a composite of Basal Eurasian and something Villabruna-related). To me this appears to be the more sensible solution.

Moreover, Lazaridis et al. 2016 characterized South Caspian forager Iran_HotuIIIb as more Basal Eurasian than the early Zagros farmers (Supplementary Information 4). The Basal-rich K7, on the other hand, shows the opposite. The D-stat below suggests that the Basal-rich K7 is closer to the truth.

D(Chimp,Ust_Ishim)(Iran_Neolithic,Iran_Hotu) 0.0156 Z 1.337

There are other such examples, and I might post them in the comments. In any case, the point I'm making is that the Basal-rich K7 is a solid piece of work and it's likely to remain relevant for a long time. Indeed, I'll be updating the Basal-rich K7 spreadsheet regularly as new ancient samples roll in, which means that you'll be able to model yourself as newly sampled ancient populations using the Basal-rich K7 ancestry proportions (for instance, see here).

The only problem with this test is that it's optimized for Eurasians. As a result, it might be sensible for anyone with significant (>5%) Sub-Saharan ancestry to skip the Basal-rich K7 and just ask for the Global 10 genetic map and coordinates.


You can use the Global 10 coordinates to model your ancient and recent fine-scale ancestry, just as you would using mixture proportions. In fact, I'd say the Global 10 coordinates are more useful in this respect than any mixture test, including the Basal-rich K7.

Thanks in advance for your support. Keep in mind that the more cash I raise the busier things will be on this blog in 2017, which, by all accounts, is shaping up to be the year for ancient DNA.

Thursday, September 22, 2016

Orcadians, the K15 and the calculator effect


Judging by the Google search terms that are bringing traffic to this and my other blogs, a total newb to the scene is analyzing the Orcadian samples from the HGDP at GEDmatch with my K15 test.

Please keep in mind that you will not see coherent results for many of the academic samples available online when using my tests.

That's because I used these samples to source the allele frequencies for the tests. As a result, their ancestry proportions will often be very different from those of other samples from the same ethnic groups that were not used in this way.

I call this problem the calculator effect, and it's described in my blog posts at the links below:

Beware the "calculator effect"

Ancient genomes and the calculator effect

The calculator effect is a very serious problem for most tests, but as far as my tests are concerned, it doesn't affect anyone except the above mentioned academic samples.

Wednesday, July 22, 2015

Marker overlap and test accuracy


A few people are asking me about the effects of marker overlap or genotype rate on test accuracy. Logic dictates that the better the overlap, the more accurate the results, but this isn't strictly true. Here's what I've learned over the years:

- accuracy doesn't necessarily improve with higher marker overlap, it improves (up to a certain point) with more markers

- you will still see accurate results using as little as 25,000 SNPs, as long as the test doesn't suffer from any serious problems

- poorly designed tests, such as those based on less than 1000 reference samples, always produce garbage results no matter what the marker overlap

In other words, a well designed test based on 200,000 SNPs will produce very accurate results for a genotype file with a marker overlap of 50%. On the other hand, another well designed test, based on just 50,000 SNPs, is likely to produce less accurate results for a genotype file with a marker overlap of 100%.

So how can you tell a well designed test from a poorly designed one? It's easy, just have a look at the results they're producing for people with less complex ancestry. For instance, ask a Lithuanian, Swede or Pole what they're seeing at the top of their oracles. Is the Swede seeing Swedish or, say, German? If the answer is German instead of Swedish, or at least some type of Scandinavian, then the test is garbage and best ignored.

By the way, the recent Allentoft et al. paper on the ancient genomics of Eurasia includes a useful discussion on the effects of missing markers on the accuracy of both ADMIXTURE and PCA results. Refer to section 6.2 in the freely available supplementary info PDF here.

Tuesday, May 12, 2015

4mix: four-way mixture modeling in R


Thanks to Eurogenes project member DESEUK1. A zip file with the R script, instructions and a couple of data sheets is available here.

So let's model Poles as a bunch of ancient genomes from Central and Eastern Europe using output from my K8 analysis.

Copy & Paste: source('4mix.r')

Hit ENTER

Copy & Paste: getMix('K8avg.csv', 'target.txt', 'HungaryGamba_EN', 'HungaryGamba_HG', 'Karelia_HG', 'Corded_Ware_LN')

Hit ENTER

After a few seconds you should see the results...

Target = 19% HungaryGamba_EN + 14% HungaryGamba_HG + 2% Karelia_HG + 65% Corded_Ware_LN @ D = 0.0062






Obviously the script can use ancestry proportions and/or population averages from any test, provided they're formatted properly. The accuracy of the modeling will depend on the quality of the input.

Update 19/05/2015: A new version of the 4mix script that can run multiple targets is available here, courtesy of Open Genomes.

Sunday, November 30, 2014

Short clip: The making of modern Europe


Simple but, I think, very cool animation: ten ancient genomes analyzed with the Eurogenes K15. More elaborate clips are on the way.



And this is basically the same thing, but restricted to samples from Hungary.

Monday, September 8, 2014

Eurogenes ANE K7


Update 01/01/2015: ANE is the primary cause of west to east genetic differentiation within West Eurasia.

...

As its name implies, the Eurogenes ANE K7 is specifically designed to estimate Ancient North Eurasian (ANE) ancestry. It's based on a series of supervised runs with the ADMIXTURE software, and freely available at GEDmatch under the Eurogenes Ad-mix tests tab.

The ANE component is not modeled on the Mal'ta boy or MA-1 genome, the main ANE proxy in scientific literature, because this sample didn't offer enough high quality markers for the job. So instead, I used the non-East Asian portions of several Karitiana genomes from the HGDP.

I wasn't sure what was going to come of that, but it actually seems to have worked out really well. Below are the results for several individuals that were not used in the making of the test, and clearly their ANE scores look pretty damn solid going by recent papers. For instance, both Lazaridis et al. and Raghavan et al. estimate the Karitiana Indians at just over 41% ANE (see here and here).

Karitiana_HGDP00998
ANE 41.56%
ASE 0.41%
WHG-UHG 0%
East_Eurasian 58.01%
West_African 0%
East_African 0.01%
ENF 0%

Lezgin_GSM536850
ANE 26.74%
ASE 3.88%
WHG-UHG 14.65%
East_Eurasian 0%
West_African 0.01%
East_African 0%
ENF 54.72%

Bedouin_HGDP00651
ANE 0%
ASE 0%
WHG-UHG 0.05%
East_Eurasian 1.49%
West_African 0%
East_African 8.19%
ENF 90.27%

Sardinian_HGDP01067
ANE 0%
ASE 0%
WHG-UHG 49.49%
East_Eurasian 1.8%
West_African 0.01%
East_African 0.01%
ENF 48.69%

You can also cross-check your ANE score with the results in this spreadsheet and table. The spreadsheet includes ANE estimates for more than 2,000 individuals that I tested with the ADMIXTURE software in supervised mode (see here).

On the other hand, the table comes from the Lazaridis et al. preprint, which I'm sure many of you have read by now several times over. And please pay attention to the range of ANE proportions for each population, rather than just the point estimates.

Obviously, there are also six other ancestral components in this test (hence the K7 in the name). They're basically byproducts of me trying to isolate ANE, and don't necessarily mean anything. Nevertheless, here's a brief rundown of what I think some of them might represent...

Ancestral South Eurasian (ASE): this is a really basal cluster that peaks in tribal groups of Southeast Asia. It's probably very similar in some ways to the Ancestral South Indian (ASI) component described by Reich et al. a few years ago.

Western European/Unknown Hunter-Gatherer (WHG-UHG): this essentially looks like a West Eurasian forager component, and includes the forager-like stuff carried by Neolithic farmers (Oetzi the Iceman has 40% of it).

Early Neolithic Farmer (ENF): I'd say that this is the component of the earliest Neolithic farmers from the Fertile Crescent.

The other three components should be easy to work out from their names. They're almost identical to several components with the same or similar names from my other tests.

Some of you might be wondering why this test doesn't offer an Early European Farmer (EEF) cluster. But the answer to that should be obvious by now. EEF is not a stable ancestral component. It's actually a composite of at least two ancient components, including the so called Basal Eurasian and WHG-UHG. If it really was a genuine ancestral component, like ANE, then I'm pretty sure I'd be able catch it with ADMIXTURE. But I can't.

Indeed, a really important thing to understand about the Lazaridis et al. study is that it doesn't actually attempt to estimate overall WHG-UHG ancestry in Europeans, but rather the excess WHG-UHG on top of what is already present in the EEF proxy Stuttgart.

Also worth noting is that this K7 can be a bit noisy. That's mainly because it's very difficult to correctly assign proportions of ancient ancestry to present-day samples. But like I say above, this test is basically designed to estimate ANE scores. If you're wanting to learn about your overall ancestry then I recommend the Eurogenes K13 and K15 tests.

Missing SNPs might also be an issue for some people. It stands to reason that results will be noisier with more missing markers and no calls.

Have fun and don't forget to make a donation at some point to the Eurogenes cause, via the PayPal tab at the top right of the page. This will help me to keep up with what's going on in the world of Paleogenomics, and continue blogging and running analyses.

Citations...

Iosif Lazaridis, Nick Patterson, Alissa Mittnik, et al., Ancient human genomes suggest three ancestral populations for present-day Europeans, arXiv, April 2, 2014, arXiv:1312.6639v2

Raghavan et al., Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans, Nature, (2013), Published online 20 November 2013, doi:10.1038/nature12736

See also...

Corded Ware Culture linked to the spread of ANE across Europe


Wednesday, July 16, 2014

Model yourself as a mixture of ancient genomes


Update 12/05/2015: 4mix: four-way mixture modeling in R

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This is really easy and should work well for most personal genomics customers (ie. those of European ancestry and with data files from 23andMe, FTDNA and AncestryDNA).

First of all, make sure you have your Eurogenes K15 ancestry proportions from GEDmatch. Then do the following:

- download the 4 Ancestors Oracle (here)

- download the Eurogenes ancient genomes datasheet (here)

- place everything into the same directory

- double click of the 4 Ancestors Oracle icon (the big red number 4)

- select the Eurogenes K15 ancient genomes datasheet

- type your Eurogenes K15 ancestry proportions into the fields provided

- hit the go button and let it rip

I'm not sure I'm allowed to upload the 4 Ancestors Oracle online, but I couldn't find the original link, so let's assume for the time being that I am. In any case, many thanks to Alexandr Burnashev for this great tool.

You'll also find some modern populations in the datasheet. They're there so that users with ancestry from outside of Europe don't end up with ridiculous results.

Obviously, you can edit the datasheet to explore more options by removing or adding individuals and populations. A spreadsheet of Eurogenes K15 population averages is available here. The oracle settings can also be tweaked in a couple of ways to fine tune the results.

If the calculator crashes, try replacing the periods with commas in both the datasheet and your ancestry proportions.

Please keep checking this post, because I'll attempt to update the datasheet at the link above every time a new ancient genome is published and has enough markers available to be tested with the Eurogenes K15. Eventually we might end up with a tool that covers most of the continents and many periods of history and prehistory.

I've done similar analyses of a variety of ancient genomes. For instance, StoraFörvar11, or SfF11, from Mesolithic Sweden came out 3/4 La Brana-1 and 1/4 MA-1, which translates to 3/4 Western European Hunter-Gatherer (WHG) and 1/4 Ancient North Eurasian (ANE), and lines up well with results reported recently for Swedish hunter-gatherers in scientific literature. You can see the full analysis StoraFörvar11 and a couple of other ancient genomes at the links below.

Analysis of Mesolithic Swedish forager StoraFörvar11

More ancient genomes from Sweden: Pitted Ware forager Ajvide58 and TRB farm girl Gokhem2

I'm still trying to answer a whole lot of e-mails so I won't be monitoring this post for a while. But please feel free to share your results and any tips you might have in the comments below.