Dodecad Ancestry Project

Correspondence between ChromoPainter clusters and ADMIXTURE components in Balkans/West Asia

2012-02-15T14:59:00.000+02:00

I took the 25 different inferred clusters from my recent ChromoPainter analysis, and calculated their normalized median components in terms of the K12b calculator. This is a quite useful exercise, since it can show in what sense clusters are different from each other.

Here are two ways in which you may use this correspondence.

1. Different clusters of a single population

For example, the Turks with partial Balkan ancestry tend to belong to pop10, whereas those of Anatolian ancestry to pop13, and those from northeastern Anatolia to pop22. If we compare the admixture proportions of these three groups, we notice e.g.,

An excess of Atlantic_Baltic and North_European in pop10
An excess of Caucasus in pop22

Or, there is a group of 5 Iranians that belong to pop12, whereas the overwhelming majority of Iranians and Kurds belong to pop21. Strikingly, pop12 differs from all other populations in having substantial levels of East_African and Sub_Saharan. So, it seems that fineSTRUCTURE was able to infer that some Iranian individuals had this feature in common. These individuals were already evident in the Iranian population portrait (right), but fineSTRUCTURE was able to group them even though there were no African populations in the ChromoPainter analysis; presumably, the software was able to detect that these individuals shared a set of chunks that were quite different than is the norm for the Balkan/West Asian area.

2. Related clusters

fineSTRUCTURE grouped the different populations in a tree structure. For example, it grouped pop18, the "North Balkan" cluster with pop23, the "Bulgarian-Romanian" one.

Looking at the admixture proportions, we can tell that the two clusters do indeed seem quite similar, but there are some differences, e.g., an excess of North_European in pop18, and an excess of Caucasus in pop23. This makes sense given the geographical origin of individuals belonging to the two clusters.

ChromoPainter/fineSTRUCTURE analysis of Balkans/West Asia

2012-02-14T13:24:00.000+02:00

I have carried out a ChromoPainter/fineSTRUCTURE analysis of Balkans/West Asia. This is a slightly different dataset than the one used in the previous fastIBD analysis of the same region. It also took much longer (about a week, with two CPUs dedicated to the task) to complete, so it is not something that can be done routinely.

Technical details (skip if you want)

413 individuals from 33 populations were studied, on 258,100 SNPs, after --geno 0.03 --maf 0.01 filters were applied. Data were phased in Beagle with the default 10 iterations. Genetic maps from the HapMap were used. fineSTRUCTURE was used on ChromoPainter output, with 500,000 burnin/runtime iterations each.

25 Inferred Populations

fineSTRUCTURE imposes a tree structure on a number of inferred populations. The following heatmap shows this tree structure; columns represent donor populations, rows, recipient ones.

There was a total of 25 populations, labeled pop0, pop1, ..., pop24.

The following table summarizes how many individuals from each original population were assigned to each inferred population:

I will limit myself to populations which include Dodecad Project members:

pop6 includes a Project North Ossetian, as well as all Yunusbayev et al. North Ossetians
pop7 is mainly Armenian
pop16 is also mainly Armenian; it would be interesting to see whether this bipartite division of Armenians is in agreement with the one inferred in the previous fastIBD analysis
pop8 is mainly Greek, and appears to be "continental Greek"; it also includes some other Balkan individuals
pop14 is also Greek, and includes a variety of people with ancestry from Crete, the Aegean, Cyprus, Asia Minor, Cappadocia, and the Pontus as well as continental Greek. It could be labeled "eastern Greek"
pop11 is Cypriot, including the single 100% Greek Cypriot of the Project, all 3 100% Turkish Cypriots, as well as a Turkish individual of partial Turkish_Cypriot ancestry
pop10 is Turkish, and includes people with some ancestry from the Balkans, as well as Anatolia. It could be labelled "Balkan Turkish"
pop13 is also Turkish, and seems to include people with ancestry exclusively from Anatolia, including almost all the Behar et al. Turks
pop15 is Assyrian; some Assyrians also fall on the aforementioned pop16 which includes mainly Armenians
pop18 could be labelled "North Balkan"; there is probably structure to be uncovered within this cluster, once more participants from the Balkans join the Project
pop20 is "Georgian-Abkhazian"
pop21 is "Kurdish-Iranian"
pop22 could be labeled "Northeastern Anatolia" or (more classically) "Pontus-Colchis". It appears to unite various individuals from Northeastern Turkey and neighboring Georgia, having Karadeniz Turkish, Armenian, Pontic Greek, and Kartvelian ancestry. I strongly encourage participants from this region to join the Project, especially Pontic Greeks, as there are no 100% Pontic Greeks currently in the Project.
pop23 is "Bulgarian-Romanian" mainly, and also includes one Serb. Once again, I emphasize that the power of this approach using haplotypes depends on participation, so I encourage all people from the Balkans to consider joining the Project.

Principal Components Analysis

I have also used the PCA feature of fineSTRUCTURE to carry out principal components analysis. I am plotting the first two dimensions of this PCA, using my own visualization code that places labels in the average position on the plane:

Results

Results for Project participants are included in the spreadsheet.

Population matrix, shows how many individuals from each population were assigned to each cluster
Z score population matrix, shows the normalized number of "chunks" from each donor population (columns) to each recipient (row). Do not compare across rows! The way to read this table is the following: for each row, higher values indicate more sharing. For example, the "Cypriots" population has pop11 as its main donor.
Individual assignments: the pop number that all Project and reference IDs were assigned to
Individual Chunkcounts: the number of chunks copied from its donor population (column) to each individual
Individual PCA: your PCA co-ordinates that can help you find your dot on the Principal Components Analysis graphic (see above)

Averaged results were included only for populations with >=5 members.
The raw chunkcounts for all 413x413 individuals can be found here.

Other testing companies

2012-02-06T12:18:00.001+02:00

The Dodecad Project is not affiliated with any genetic testing companies. Until now, I have included Project participants from 23andMe and FamilyTreeDNA "Family Finder" tests, but it has come to my attention that there are new players in the field, such as Ancestry.com (see post on Your Genetic Genealogist) and Lumigenix (see post on GenomesUnzipped).

If you have data from any company entering this field, please contact me at dodecad@gmail.com (do not send data right away!). That way, I can find out how many markers are in common between the new tests and my existing datasets, and figure out how easy it will be to convert them for use in the Project and in DIYDodecad.

'K12b' and 'K7b' calculators

2012-01-31T22:27:00.000+02:00

I am releasing two new calculators with K=12 and K=7 components, named 'K12b' and 'K7b'. You can scroll down to the bottom if you are just interested in the downloads, or read on.

New Features

The new 'K12b' calculator is an update of the previous K12a one, that was inferred using all the new samples submitted during the last submission opportunity. The 12 components are still roughly the same, although their allele frequencies may have changed by a bit, so existing participants can expect to have slightly altered results, and new participants in the Project more so, since their data are now contributing to the creation of the new tool. Non-participants can, of course, use the new calculator with DIYDodecad.

I have also taken the opportunity to do some minor tweaks. I am releasing population portraits for K12b (which were lacking in K12a); I've changed my visualization code so that the sample IDs of non-Dodecad populations can now be seen in the barplots. This may be useful for anyone else using these reference populations, by quickly identifying potential outliers in them.

I have also decided to use normalized median admixture proportions for the populations. For example, if 5 individuals in a population have 0, 0, 0.2, 0.5, 10.0% of a particular component, then the average is 2.14%, but the median is 0.2%. By using the median, the proportions become less susceptible to the presence of outliers (such as the 10%). However, if the median is calculated over every component separately, it is no longer guaranteed that the components will add up to 100%; this can be addressed by re-normalizing them (scaling them by a constant factor) so that they do. I believe that use of the normalized median will not only give better proportions that are less susceptible to outliers, but will also improve results of the new Dodecad Oracle for K12b.

At the same time I am also releasing 'K7b' which is an update of the existing 'eurasia7' calculator and which has been built on exactly the same dataset as 'K12b' but at a lower (K=7) level of detail.

Information on K7b

Information spreadsheet.

Normalized median admixture proportions barplot for all included populations (a high resolution version of this is included in the download bundle):

Table of Fst divergences:

Neighbor-joining tree (based on above):

Information on K12b

Information spreadsheet.

Normalized median admixture proportions barplot for all included populations (a high resolution version of this is included in the download bundle):

Table of Fst divergences:

Neighbor-joining tree (based on above):

Multidimensional Scaling Plots of K12b and K7b

I have created MDS plots using synthetic individuals representing the 12 ancestral components of K12b and the 7 ancestral components of K7b. By including both in the same plot, one gets an idea of the relationship of the components at different resolution. The first 10 dimensions can be seen below:

Here is a blowup of the main West Eurasian groups from the plot of the first two dimensions:

Some observations:

The Atlantic_Med component which is bi-modal in Basques and Sardinians occupies the apex of the figure; this makes sense, since Southwest Europe is quite distant (along land routes) to both Asia and Africa.
The Caucasus component is surrounded by most of the others; this is consistent with my theory elaborated in The womb of nations: how West Eurasians came to be.
The Atlantic_Baltic component (from K=7) is intermediate between the Atlantic_Med and North_European components.
Similarly, the West_Asian component (from K=7) is intermediate between the Caucasus and Gedrosia components; the Gedrosia component diverges in the direction of the Asian groups (not shown in this figure), and in particular of South Asians. This divergence can also be seen in the plot of dimension #3.
The Northwest_African component diverges in the direction of Sub-Saharan Africans.

Technical Details

A dataset of 268 populations/3,115 individuals was assembled. A total of 265,519 SNPs are in common in the various source datasets as well as the 23andMe v2/v3 and Family Finder platforms. Iterative removal of distant relatives was performed by removing one individual from each pair within a population if that pair had a RATIO of 2.5 or greater or more than the mean and two standard deviations in IBD analysis performed in PLINK 1.07. A total of 2,675 individuals remained. 4 individuals were removed for low genotyping rate (less than 97%). 264,328 SNPs remained after removal of SNPs with less than 97% genotyping rate or 1% minor allele frequency. 166,770 SNPs remained after linkage-based disequilibrium pruning (--indep-pairwise 200 25 0.4). The final set thus consisted of 2,671 individuals/268 populations/166,770 SNPs. Ancestral populations (components) were inferred using ADMIXTURE 1.21, with K=7 and K=12 and default parameters.

No individuals were removed from the source datasets, except in the case of the Armenians_Y sample, where one individual (ID: armenia3) was dropped because he/she was the same as a Dodecad Project participant.

Downloads

K7b population portraits, spreadsheet, and DIYDodecad files.
K12b population portraits, spreadsheet, and DIYDodecad files.

Dodecad Oracle (K12b edition) can be downloaded from here. Please read the instructions of the previous Oracle on how to use this tool. Note that the number of populations is now 223.

To use either calculator with DIYDodecad, with your 23andMe or Family Finder data, follow the instructions in the README file, but substitute 'K12b' or 'K7b' for 'dv3'.

Project participant results for both K7b and K12b are found in the spreadsheets in the Individual Results tab.

Terms of Use

You are free to use K12b and K7b, including all downloaded files for any non-commercial purpose, as long as you attribute them to the Dodecad Project and to Dienekes Pontikos as follows:

The [K7b/K12b] admixture calculator is courtesy of Dienekes Pontikos and was developed as part of the Dodecad Ancestry Project; more information here.

Submission Opportunity is OVER

2012-01-24T04:10:00.000+02:00

Thank you everyone for submitting their data. I will not accept any more data at this time. A couple of submissions came in at the last second, so I accepted one more than I promised, who got the brand new DPD001 ID.

Those who submitted in time will get their IDs and their results will be posted in the K12a spreadsheet.
Additionally, I will run all participants over world9, so that spreadsheet will also include everybody.

From now on, I will be reworking some of the Project tools to make use of newer samples submitted during this submission opportunity.

If you wish to submit your data during this off period, note that you must contact me at dodecad@gmail.com. Do not send data at this time, unless I indicate that I can accept it! I will let you know if I can process it, and note that I will normally only consider those who matched the eligibility criteria of the most recent submission period.

Open submission for everybody until DOD999

2012-01-23T22:23:00.000+02:00

SUBMISSION OPPORTUNITY IS NOW OVER

Everyone on the planet is invited to submit their data, regardless of their ancestry.

All other rules apply, especially the no relatives clause. Additionally, I will accept a single submission from each submitter, so don't submit all your friends. Moreover, regardless of your ancestry, you should let me know the origin of your four grandparents.

There are 35 spots open, so hurry, since last time I had a free-for-all I had to close it down after about 12 hours due to overwhelming demand. I will close project submission after I assign DOD999.

All submissions after I post the end-of-submission announcement on the blog will be ignored. If you post this in any forums or mailing lists, include this post link so that people will know whether the opportunity is over.

fastIBD analysis of Afroasiatic groups (Jews, Arabs, Assyrians, Berbers, Somalis, Amharas, etc.)

2012-01-21T22:27:00.000+02:00

Please refer to the previous analysis on the Balkans/West Asia for more information about the interpretation of this type of analysis.

I am very pleased with the way this analysis of Afroasiatic groups has turned out, revealing an exceptional degree of resolution. I invite individuals from the Near East and Africa who are eligible, to submit their data, so that they can be included in future runs of this kind.

Clusters Galore

45 clusters were inferred with 29 dimensions.

I can't comment on all 45 clusters, so I'll just limit myself to the ones that are significantly represented among Project participants: 1. Ashkenazi, 4. Assyrian/Mandaean, 6. Somali, 7. Moroccan, 8. Algerian/Tunisian, 9. Sephardic, 10. Morocco Jews, 11. Iran/Iraq Jews, 12. Non-Jewish Ethiopians, 13. Saudi, 14. Arab #1, 15. Arab #2, 16. Egyptian

Inter-Population IBD

Results for Project Participants

The results can be found in the spreadsheet.

I have also added the full IBD sharing matrix which lists how many Morgans of sequence are estimated to be IBD with probability greater than 10^-6 between all pairs of individuals.

You can google any non-Project sample IDs to get some more information about their origin. For example, GSM536710 is an Iraqi Jew who shares about half his genome with GSM536714, also an Iraqi Jew. These two samples are almost certainly first-degree relatives. Or, GSM537032, a Samaritan shares 740-1,480cM with the other 2 Samaritans, an exceptional amount in this small and probably highly inbred population.

You can manipulate this matrix in R. After you download it and unzip it, you can load it into R as follows:

X<-read.table('afroasiatic_ibd_sharing.txt',row.names=1,header=T)

Then, you can, for example, sort the IBD sharing for a particular individual, as follows:

sort(X['DOD026',])

fastIBD analysis of Central/Eastern Europe

2012-01-21T11:49:00.000+02:00

Please refer to the previous analysis on the Balkans/West Asia for more information about the interpretation of this type of analysis.

Clusters Galore

The Clusters Galore can be found in the spreadsheet. After inspection of the 23 clusters inferred with 21 dimensions, they could be described as:

Mordvin
East Slavic
Polish-Ukrainian
East Balkan
Vologda Russians
Lithuanian
Central European (combining many groups with small sample sizes)
A couple of related (?) individuals
Anatolian
Greek
Chuvash
Ossetian
A couple of related individuals
A couple of related individuals
Balkar
A couple of related individuals
Chechen
Kumyk
A couple of related individuals
Adygei
Lezgin #1 (main)
Lezgin #2
Lezgin #3

If you belong to a population with few other participants, you might end up latching onto a cluster dominated by a bigger group. This does not mean that your population is not distinctive, only that there are not enough samples to reveal its distinctiveness if it exists.

Inter-Population IBD

Results for Dodecad Participants

Results can be found in the spreadsheet.

If you have joined the Project, please consider leaving a comment in the Information about Project samples thread. That will help others make better sense of their results, e.g., if you find that you belong in the same cluster with some other individual, you might want to know something about their origins.

UPDATE: I have added the IBD sharing matrix.See here on how to use it.

fastIBD analysis of South Asia

2012-01-19T12:00:00.001+02:00

Please refer to the previous analysis on the Balkans/West Asia for more information about the interpretation of this type of analysis.

Clusters Galore

The Clusters Galore analysis can be found in the spreadsheet. 59 clusters were inferred with 47 MDS dimensions. The very fine-scale structure (I only considered the first 50 dimensions, but many more seemed significant than in any previous experiment) is probably the result of the size of the South Asian population, as well as the practice of endogamy associated with the caste system. High intra-population IBD sharing is also evident in the following (notice how well-defined the diagonal is):

Inter-Population IBD

Results for Dodecad participants

They can be found in the spreadsheet. Many Project participants belong to a population with 1 or 2 individuals, so cluster #1 seems to be a generalized catch-all for many such individuals. Individuals from he two sub-populations that I've identified recently Iyer_D, and Jatt_D all belong to the same cluster. The Iyer_D cluster (#4) also seems to include the Iyengar project participants as might be expected.

It is also interesting how all Dodecad participants fall in just 7 of the 59 clusters. This goes to show how truly diverse people from the Indian subcontinent are. I fully expect that with more participation further structure will be revealed, since it seems that due to endogamy it only takes a few participants from each ethnic group for a specific cluster pertaining to that group to be identified. So, I invite people from South Asia to join the Project during this submission opportunity.

fastIBD analysis of Iberia, France, Italy, Balkans, Anatolia and European Jews

2012-01-17T01:13:00.003+02:00

On the heels of the previous analysis of Balkans/West Asia, a new experiment on a different set of populations. Please refer to the earlier post for some thoughts/explanations about this type of analysis, I'll stick to "just the data" for this post.

Clusters Galore

24 clusters inferred with 17 MDS dimensions.

The Galore analysis provides increased resolution within Iberia (#6-9, 11), Italy, and the Ashkenazi Jewish group (#14-16).

The Iberian results are particularly interesting, showing the power of this approach compared to the one with unlinked data. There appear to be:

a Spanish Basque (#6),
French Basque (#11) cluster, as well as
a Portuguese/Galician/Castilla Y Leon (#9) cluster, and
a complementary Castilla La Manch/Cantabria/Andalucia/Murcia (#7) cluster, and
a smaller Aragon/Cataluna cluster (#8).

There is overlap between these clusters, but the geographical contrasts are quite evident. I did not go through the results of Spanish Project participants (all the Portuguese fall in the Galician cluster, and our Basque member in the Basque cluster as expeccted), so it would be interesting to hear whether they fall in the cluster(s) which exist in their regions of origin.

Inter-Population IBD

Results for Project Participants

The results can be found in the spreadsheet.

fastIBD analysis of Balkans/West Asia

2012-01-14T13:22:00.001+02:00

Now that I've discovered a way to boost Clusters Galore analysis even further by using fastIBD, I will start experimenting with different regional populations. This analysis took about 5 hours to complete, so it appears to be quite practical.

For my first experiment, I carry out an analysis of various populations from the Balkans and West Asia.

Clusters Galore

27 different clusters were inferred with 17 MDS dimensions. Some interesting findings:

For the first time there emerge a couple of clusters that appear to be quite specific to Armenians (#2 and #3).
Similarly, Assyrians are broken to a few clusters that appear fairly specific to them (#9-11)
Georgians are split into three clusters, one of which (#14) is linked with the neighboring Abkhasians, who in turn have their own exclusive cluster (#25)
The cluster modal in Greeks (#6) includes 14 of 19 Greek participants, and a few Greeks are also in the Balkan cluster (#8) and an Iranian-Turkish cluster (#4)
The Behar Cypriot sample also splits into two, and the few Turkish Cypriot participants link to one of them (#13)
The Ossetian project participant links to one of the three North_Ossetian clusters
The major Balkan cluster (#8) still defies resolution. I am certain, however, that structure in this cluster will be uncovered with more participation. MCLUST adapts the cluster size and shape, and a "big", inclusive cluster spanning the Balkans appears more parsimonious than smaller clusters centered on the different groups. With larger participation, I anticipate that regional structure will be uncovered in the Balkans as well.

I cannot stress the importance of participation strongly enough. When groups have more participants, it is possible to both:

Discover group-specific clusters, by identifying what is common between members of groups
Discover within-group clusters, by identifying what is different between members of groups

For example, the great participation of Armenians in the Project has now allowed me to discover structure within the Armenian population. It appears, that cluster #2 corresponds to a more "western" Armenian group, and #3 to a more "eastern" one, with some overlap between the two.

Inter-population IBD

You can also see a visual representation of inter-population IBD:

I have only included populations with 5+ participants in this representation. Reddish shades express high IBD sharing; bluish ones low one. The heatmap has been scaled by row.

As you might expect, values across the diagonal are "reddish", since individuals within populations tend to have high IBD sharing with each other.

A few features "pop out" of the screen. Going from top to bottom:

Intra-Iranic sharing
Intra-Armenian sharing
Intra-Balkan sharing
Georgian-Abkhaz sharing

You can probably get more out of the figure, but these appear to be the most salient features.

Results for Project Participants

The results can be found in the spreadsheet, and include:

Probabilities of assignment in each of the 27 clusters of the Clusters Galore analysis
Z-scores of IBD between each individual and each of the 20 populations with 5+ participants. Higher values mean more IBD sharing. Note that Z-scores have been calculated for each row, hence each participant must scan his own row to find populations with an excess (+) or deficiency (-) of IBD sharing, and people should not compare across different rows.

Last but not least, I want to remind new project participants to leave a message in the Information about Project samples thread. Your comment will not appear immediately, since comment moderation is on, and also note that there are multiple pages of comments.

If you haven't joined the Project yet, I encourage you to do so if you are eligible.

Clusters Galore (fastIBD edition) for some northern European participants

2012-01-11T14:11:00.002+02:00

You can find some new Clusters Galore results here (scroll down for spreadsheet link). The new methodology described in that post has made it possible to infer even finer-level population structure than "classical" Clusters Galore.

Submission opportunity (January 2012)

2012-01-03T16:09:00.002+02:00

Who is eligible

Anyone who:

has 23andMe or Family Finder autosomal data,
is not related to any other Project participants,
has 4 grandparents from the same African, European, or Asian ethnic group or country (e.g., 4 Albanian grandparents, 4 grandparents born in Ethiopia, 4 Kazakh grandparents, etc.)

Any ineligible submissions will be blacklisted. Do not send data if you do not meet the eligibility criteria.

What to send

Send your compressed autosomal data (ending .zip or .gz) that you can download from your testing company.
Send to dodecad@gmail.com as an attachment, and include in your e-mail as much information about your ancestry as you can (e.g., birthplace of grandparents, spoken languages, practiced religions, ethnic affiliation, etc.). Samples without adequate ancestral information will be ignored.

Data Privacy Statement

Your raw data or genealogical information will not be shared or distributed in any manner, and it will not be analyzed for any other purpose than assessment of ancestry (i.e., not for any physical or health-related traits). It will be identified by a unique ID, known to you and me, and results will be posted in the blog using that ID. I will continue to analyze your data for ancestry, and new results will be posted using that same ID. Also, I will report aggregate results for populations with at least 5 participants.

What you will receive

I will add you to the K12a spreadsheet of the K12a calculator. You will also be eligible to participate in future data analyses, and newer results will be posted in this blog with your ID.

Clarification (added on 6 Jan, 2012): The results which you will receive will be based on the K12a calculator whose components were inferred in December 2011, and hence included only those who had submitted their data up to that time. As new members of the Project, your data will be used for the development of the next version of the admixture analysis, and this will -in all likelihood- lead to a subtle redrawing of the ancestral components and different ancestral proportions (see technical note).

By participating in the Project, you help better draw both the basic ancestral components underlying genomic variation in Africa/Europe/Asia, and create more robust samples of different populations. This is helpful both to the Project, and to yourself, because it helps you get increasingly better results with newer versions of the analysis. All newer analysis tools are announced on this blog.

End of Submission Opportunity

The end of this submission opportunity will be announced on this blog.

'world9' calculator

2011-12-19T15:00:00.000+02:00

I have consistently received requests for an assessment of Amerindian ancestry. While the focus of the Project is, and will remain, the region of Eurasia, I thought it was a good idea to release a tool that could be used by persons of partial Amerindian ancestry.

I have also included the two Australasian populations currently available, namely Bougainville Melanesians (NAN_Melanesian) and Papuans from the HGDP.

The inferred components at K=9 are quite similar to those of 'eurasia7', with the addition of the Australasian and Amerindian components. I have also included the Kalash in this experiment, which caused the 'West_Asian' component to be modal in them, although the Kalash's difference in terms of this component to other populations is not so great as to render it strongly population-specific; I have called this component 'Caucasus_Gedrosia' and it -like the 'eurasia7' West Asian component- ought to be quite similar to the k5 component inferred by Metspalu et al. (2011).

It is unfortunate that there are only two Australasian populations currently available as public data. There are many more Amerindian and Mestizo ones, but it should be noted that the Amazonian populations on which the 'Amerindian' component is modal are some of the most lacking in genetic diversity in my entire database. As a result, Eurasians who lack any Amerindian or Australasian ancestry can expect to see a little of it in their results as noise.

This is a very important caveat for Americans who suspect that they may have an Amerindian ancestor. Small levels of this component may be noise, and this component is also found in Siberia, and may represent either backflow from the Americas or the common ancestry of Siberian and Amerindian populations. If you are interested in the detection of Amerindian ancestry, I recommend that you use DIYDodecad's 'byseg', 'bychr', and 'target' modes to drill down deeper in your genomes.

Download Files

The spreadsheet contains admixture proportions, the table of Fst distances, and individual results in the Individual Results tab.
The RAR file contains files for use with DIYDodecad. Extract its contents to the working directory of DIYDodecad. In order to run the calculator, you follow the instructions of the README file, but type 'world9' instead of 'dv3'.

Terms of use:

'world9', including all files in the downloaded RAR file is free for non-commercial personal use. Commercial uses are forbidden. Contact me for non-personal uses of the calculator.

Information

Admixture proportions barplot:

The nine ancestral components are:

Amerindian
East_Asian
African
Atlantic_Baltic
Australasian
Siberian
Caucasus_Gedrosia
Southern
South_Asian

Table of Fst divergences:

Neighbor-joining tree of Fst distances; the long branch lengths of the Australasian (and to a less degree the Amerindian) branch is due to the high level of inbreeding in the populations for which this component is modal.

First 8 dimensions of multi-dimensional scaling (MDS):

Technical Details

A dataset of 3,548 individuals/265,519 SNPs/284 populations was assembled. Pruning for distantly related individuals was performed by iterative pruning of a single individual from each pair showing IBD RATIO greater than the mean plus 2 standard deviations, or greater than 2.5. 3,026 individuals remained. An additional 14 individuals were removed because they had less than 97% genotype rate. The marker set was thinned to remove SNPs with less than 97% genotype rate or 1% minor allele frequency. Linkage-disequilibrium based pruning with a window of 200 SNPs, advanced by 25 SNPs, and an R-squared of 0.4 was performed. A total of 3,012 individuals and 170,822 SNPs survived these filtering steps. PLINK 1.07 and ADMIXTURE 1.21 were used in the analyses.

Dodecad Oracle (K12a edition)

2011-12-11T22:33:00.003+02:00

I have created a new version of the Dodecad Oracle for use with the K12a calculator.

You can refer to the original Dodecad Oracle for detailed usage instructions.

(The only difference in the use of the program is that the number of populations is 204, so make sure to use this if you plan to remove any reference populations, as mentioned in the instructions)

In short:

you first load the file DodecadOracleK12a.RData in R. You can do this by double-clicking on this file in Windows, or using the File->Load Workspace menu. In Linux, you can use the "load" command, e.g., load('/home/ubuntu/Desktop/DodecadOracleK12a.RData')
You then enter commands at the command prompt

Some examples:

Comparing a population against other populations

DodecadOracle("Somali_D")

[,1] [,2]

[1,] "Somali_D" "0"

[2,] "Ethiopian_Jews" "12.3049"

[3,] "Ethiopians" "12.3309"

[4,] "Sandawe_He" "38.2093"

[5,] "MKK25" "40.7983"

[6,] "Egyptans" "63.2307"

[7,] "Yemenese" "69.1628"

[8,] "Moroccans" "72.6233"

[9,] "Jordanians" "73.1838"

[10,] "Palestinian" "74.2867"

Comparing a population against 2-way population mixes:

DodecadOracle("Pathan",mixedmode=T)

[,1] [,2]

[1,] "Pathan" "0"

[2,] "79.5% Sindhi + 20.5% Lezgins" "3.948"

[3,] "82% Sindhi + 18% Chechens_Y" "4.0251"

[4,] "16.7% Adygei + 83.3% Sindhi" "4.5471"

[5,] "83.4% Sindhi + 16.6% Balkars_Y" "4.6487"

[6,] "80.8% Sindhi + 19.2% Kumyks_Y" "4.7067"

[7,] "83.7% Sindhi + 16.3% North_Ossetians_Y" "4.8352"

[8,] "80.9% Sindhi + 19.1% Nogais_Y" "4.8821"

[9,] "66.6% Sindhi + 33.4% Tajiks_Y" "5.6708"

[10,] "86.4% Sindhi + 13.6% Georgians" "6.2927"

Comparing an individual against populations

DodecadOracle(c(8.4, 0, 2.8, 6, 2.2, 0.1, 40.3, 25.9, 0.3, 11.9, 1.5, 0.5))

[,1] [,2]

[1,] "Iranian_D" "2.2405"

[2,] "Kurd_D" "3.8092"

[3,] "Kurds_Y" "5.4945"

[4,] "Iranians" "6.634"

[5,] "Uzbekistan_Jews" "12.8957"

[6,] "Turks" "17.3173"

[7,] "Turkmens_Y" "17.7316"

[8,] "Iranian_Jews" "18.14"

[9,] "Assyrian_D" "18.8968"

[10,] "Azerbaijan_Jews" "18.9444"

Comparing an individual against 2-way population mixes

DodecadOracle(c(28, 0.8, 1.6, 49.9, 1.9, 0, 10.6, 4.1, 0, 2.4, 0, 0.6),mixedmode=T)

[,1] [,2]

[1,] "47.7% French_D + 52.3% Mordovians_Y" "2.5849"

[2,] "48.3% French + 51.7% Mordovians_Y" "2.6012"

[3,] "36.3% Spaniards + 63.7% Mordovians_Y" "2.9985"

[4,] "36% Spanish_D + 64% Mordovians_Y" "3.0577"

[5,] "65.9% Russian_D + 34.1% Spaniards" "3.0923"

[6,] "35.9% IBS + 64.1% Mordovians_Y" "3.0943"

[7,] "40% French + 60% Ukranians_Y" "3.1662"

[8,] "66.4% Russian_D + 33.6% IBS" "3.2359"

[9,] "24.5% Swedish_D + 75.5% Hungarians" "3.3021"

[10,] "39.3% French_D + 60.7% Ukranians_Y" "3.4046"

The numbers to the right of each result represent the "goodness" of the match; the lower, the better. If you wanted to list the top-30 results, in any of the above commands, you would enter, e.g.,

DodecadOracle(c(28, 0.8, 1.6, 49.9, 1.9, 0, 10.6, 4.1, 0, 2.4, 0, 0.6),mixedmode=T, k=30)

If you recently joined the Project, please consider leaving a brief comment in the Information about Project Samples thread.

Participant results for 'K12a' calculator

2011-12-11T14:24:00.003+02:00

The participant results can be found in the "Individual Results" tab of the K12a spreadsheet.

You can read more about the K12a calculator at my other blog; if you are not a Project participant, you can also find a DIY version of it there, which can be used in conjunction with DIYDodecad 2.1.

Origin of Kalash inferred with Eurogenes K=10 "test" calculator

2011-10-31T12:35:00.023+02:00

Vasishta, is asking Eurogenes for help in demonstrating that the Kalash have Northern-European-specific segments:

Yes. He keeps citing the Kalash as proof that the Indo-Iranians were an almost exclusively a West-Asian like population, even though I personally think the mainly West Asian-South Asian assortment of the Kalash in his analyses might be an artifact of their inbreeding and isolation, thus confusing ADMIXTURE. Zack's K=11 at Harappa has shown that the Kalash display around 22% of the component modal in Lithuanians. Yet, he ignores the North/Eastern European admixture in Northwest Indians and North Indian Brahmins (in his own analyses at that!). Interestingly enough the aforementioned groups tend to score a sliver of Northeast European admixture in Dr.Doug McDonald's analyses, with the top matches for that sliver usually being Lithuanians, Russians and Finns; in that order. It (NEU) is even found in frequencies of around 4-6% in Dravidian-speaking southern Brahmins. As much as I hate to say it, he is indeed rather stubborn and has somewhat of an underlying agenda.

David, I think you should look into proving that the Kalash do indeed have some NEU-specific segments. I would be super-surprised if they didn't, given that more mixed populations south of their geographical area display it themselves.

It appears that Vasishta disagrees with me because he "personally thinks" that the admixture proportions of the Kalash are due to inbreeding and the limitations of ADMIXTURE.

Does he cite any studies or make any argument why ADMIXTURE would remove precisely the component that he is so eager to be present? No. While genetic drift in an isolated population could indeed lead to the loss of genetic diversity, there is no reason to think that this would lead preferentially to the loss of Northern-European segments. It is strange that Vasishta accuses me of bias and yet, at the same time, invokes the magic of some unspecified flaw of ADMIXTURE for the loss of his favorite component.

Vasishta invokes the Harappa Ancestry Project K=11 admixture analysis in support of his idea that the Kalash have 22% of the component modal in Lithuanians. However, he neglects to mention that at K=11 there is no West-Asian or Caucasus centered component in the HAP analysis, but rather only "European" (modal in Lithuanians) and "SW Asian" (modal in Yemen Jews). It is indeed strange that he accuses me of bias for providing evidence about the relationship of the Kalash with West Asia, while at the same time, showing preference for a level of analysis where such a component is lacking.

The West Eurasian cline between Arabia and Northeastern Europe is evident in the 'weac' admixture analysis, where the European-centered component (Atlantic-Baltic) is present in populations such as Assyrians and Armenians whereas it is lacking at the appropriate level of resolution. Therefore, the fact that the Kalash show "European" admixture at the level of Europe vs. Near East does not mean that they ought to show such admixture at the level of Europe vs. West Asia/Caucasus vs. Arabia.

One of the benefits of DIYDodecad has been the availability of data from projects that have hitherto been black boxes. In the interest of transparency, I have taken the Eurogenes K=10 "test" calculator and repeated my analysis of the Kalash, that had been previously shown by me to be a fairly simple West/South Asian mix. I could have waited for him to get around to it, but since he's quick on the talk and slow on the trigger, I decided to do it for him.

The admixture proportions of the Kalash, according to the Eurogenes K=10 are: 40.3% S_Asian, 58.7% W_Asian, 0.9% N_E_Euro, 0.1% N_Asian, and hence the analysis based on the Eurogenes K=10 components confirms the analysis based on my eurasia 7, "showing the Kalash to be a "West Asian" population (62.4%) with substantial "South Asian" admixture (37.1%), and near-complete absence of any other genetic components."

Eurogenes alleges, not without his usual charm, that:

Dienekes has a keen eye for things he wants to see. But he hasn't yet noticed that in all accurate analyses, there's significant Eastern European admix in North India. His monocle got fogged up in that instance.

Let us consider some pertinent facts: the Indian peninsula has been invaded multiple times from Central Asia, a process that continued long after the establishment of the Indo-Aryans during the 2nd millennium BC. Eurogenes may want to think that the "Eastern European" admixture in South Asia dates to his mythological Polish Indo-Europeans, galloping across the steppes on their horses, but there is, at present, no particular reason to think that this is the case

Furthermore, the "West Asian" component as a fraction of the "West Asian" + "Atlantic-Baltic" component reaches a minimum of 77% in the Pathans in populations from the northern parts of the Indian subcontinent. His own monocle is surely in greater need of de-fogging if I miss the 23% and he misses the >77%.

Indeed, the Europe vs. Caucasus ratio in Indian subcontinental populations is similar to that found in people from the Middle East and Caucasus region. It is not surprising that Eurogenes has abandoned his search for North European components in South Asia, going as far as reconstructing Ancestral North Indians as "Northern Europeans". Needless to say, he was wrong. The West Eurasian ancestry of the population of the Indian subcontinent is similar to that found in modern West Asian populations, not Slavs.

Eurogenes promises:

This shouldn't be too difficult. I'll use Dienekes' calculator for the job, and then check the results with LAMP.How poetic.

Been there, done that. It will be fun to see what "Northern European" components he will be able to squeeze out of the 0.9% N_E_Euro component that my software, in conjunction with his "test" calculator produces.

Why are the Kalash important?

There are three reasons why the Kalash are important in the study of Eurasian prehistory:

Their mountainous habitat contributed to isolation and relative immunity from historical population movements
Their non-Islamic religion has definitely preserved them from recent gene inflow
Their language is unique within the Indo-Aryan family, and it often considered today as part of a separate Dardic family of Indo-Iranian in addition to the more populous Iranian and Indo-Aryan families.

The Kalash are crucial for those interested in the origins of Indo-Iranians, and the fact that they are, indeed, a simple West/South Asian mix is not without significance for that question.

UPDATE:

Here is the result of a PCA analysis of the Kalash together with 50 synthetic individuals from each of the S_Asian, W_Asian, and N_E_Euro components of Eurogenes K=10 "test". This was calculated with smartpca with numoutlieriter set to 0.

It is evident that the Kalash appear to fall on the S_Asian to W_Asian line, and toward the W_Asian pole, consistent with being a population of those two origins, with the W_Asian component predominating.

UPDATE II:

As mentioned in the eurasia7 post, the Kalash tend to form population-specific components in ADMIXTURE analyses, so they are generally not included in my runs. So, I run the K=7 analysis again, but this time I included the Kalash. Here are the top populations of the component that was modal in the Kalash:

[186,] "Kurd_D" "50.2"

[187,] "Kurds_Y" "50.7"

[188,] "Armenian_D" "50.9"

[189,] "Armenians_Y" "51.2"

[190,] "Adygei" "51.5"

[191,] "Chechens_Y" "53"

[192,] "North_Ossetians_Y" "53.2"

[193,] "Lezgins" "54.4"

[194,] "Georgians" "59.8"

[195,] "Georgian_D" "60.1"

[196,] "Abhkasians_Y" "60.5"

[197,] "Kalash" "63.2"

Here are their exact admixture proportions in this unsupervised ADMIXTURE run:

Kalash N=23

East_Asian: 0.5

Atlantic_Baltic: 1.5

South_Asian: 32.9

Sub_Saharan: 0.0

Southern: 0.0

Siberian: 1.8

West Asian: 63.2

UPDATE III (November 22): Eurogenes estimates that there is 4% "Northeast European" admixture for Kalash individual HGDP00302. He managed to avoid the creation of a Kalash-specific component by including only a single Kalash individual in an ADMIXTURE experiment.

The Kalash do tend to create their own Kalash-specific component, and a good way to avoid such a component is to include each of them individually, and repeat the analysis 23 times. An alternative, and less time consuming way, is to create a single synthetic individual using the allele frequencies of the Kalash population as a whole. Even simpler, one could randomly pick a single individual (such as HGDP00302), but at the risk of picking an individual that has either much more or much less than average a particular type of ancestry.

Below are the admixture proportions of all the 23 Kalash individuals from the unsupervised ADMIXTURE run of UPDATE II. Individual HDGP00302 is 4th of 23 in terms of their "Atlantic_Baltic" component that peaks in Lithuanians (3%). The Kalash have 1.5% "Atlantic_Baltic" on average (median=1%, standard deviation=2.1%).

ID	East_Asian	Atlantic_Baltic	South_Asian	Sub_Saharan	Southern	Siberian	West_Asian
HGDP00279	0.007	0.081	0.361	0	0	0.031	0.521
HGDP00307	0.004	0.059	0.336	0	0	0.018	0.583
HGDP00315	0.019	0.036	0.338	0	0	0	0.606
HGDP00302	0.006	0.03	0.337	0	0	0.02	0.608
HGDP00311	0.014	0.029	0.325	0	0	0.021	0.611
HGDP00285	0	0.027	0.319	0	0	0.019	0.635
HGDP00333	0	0.02	0.324	0	0	0.018	0.638
HGDP00277	0	0.016	0.334	0	0	0.021	0.63
HGDP00298	0.012	0.016	0.325	0	0	0.016	0.631
HGDP00281	0.011	0.015	0.332	0	0	0.01	0.633
HGDP00304	0.007	0.012	0.329	0	0	0.013	0.638
HGDP00290	0.007	0.01	0.325	0	0	0.021	0.637
HGDP00274	0.007	0.004	0.341	0	0	0.013	0.635
HGDP00309	0.007	0	0.317	0	0	0.019	0.656
HGDP00330	0	0	0.335	0	0	0.026	0.639
HGDP00319	0.011	0	0.328	0	0	0.01	0.651
HGDP00288	0.004	0	0.339	0	0	0.013	0.644
HGDP00286	0	0	0.329	0	0	0.018	0.653
HGDP00313	0	0	0.351	0	0	0.015	0.634
HGDP00328	0	0	0.31	0	0	0.023	0.667
HGDP00267	0	0	0.332	0	0	0.022	0.647
HGDP00326	0	0	0.307	0	0	0.03	0.663
HGDP00323	0.002	0	0.304	0	0	0.013	0.68

'eurasia7' calculator

2011-10-26T17:16:00.020+03:00

This calculator was made with 196 different populations and 2,659 individuals, including 518 project participants. The following Dodecad populations do not have 5 individuals yet, so they are included in the OTHERS_D generic category:

Algerian_D, North_African_Jews_D, Slovenian_D, Mixed_Scandinavian_D, Danish_D, Moroccan_D, Tunisian_D, Serb_D, Austrian_D, Saudi_D, Pakistani_D, Tatar_Various_D, Palestinian_D, Greek_Italian_D, Romanian_D, Swiss_German_D, Szekler_D, Mandaean_D, Azeri_D, Czech_D, Georgian_D, Belgian_D, Latvian_D, Estonian_D, Bangladesh_D, Yemenese_D, Sri_Lanka_D, Hungarian_D, Basque_D, Udmurt_D, Egyptian_D

As always, I encourage people with 4 grandparents from the same country or ethnic group of Eurasia, North or East Africa to contact me (do not send data!) for possible inclusion in the Project. If I have overlooked any such individuals, drop me a line (my e-mail address is at the bottom of the blog). I usually start a new _D population whenever individuals with 4 grandparents from the same group are submitted, but I may have missed some.

Note that all individuals from the reference populations have also been included, including outliers; you should be aware of this when reading the population averages, and consult the Outliers tab in the v3 spreadsheet for some instances of outliers.

Due to image size restrictions in Picasa, the labels are not visible well. A large version of the above plot can be found in the download bundle.

The seven ancestral populations inferred at this level of resolution are:

Sub_Saharan
West_Asian
Atlantic_Baltic
East_Asian
Southern
South_Asian
Siberian

As usual, you should take these names as useful labels, and interpret them in conjunction with the components' distribution in different populations, and their Fst distances, both of which can be found in the spreadsheet.

The table of Fst distances:

Below you can see a neighbor-joining tree based on inter-population Fst distances:

The first six dimensions of a multi-dimensional scaling of the same:

Calculator Files:

The spreadsheet contains population averages, the table of Fst distances, and individual results for included Project participants.
The download RAR file (Google Docs or Sendspace) contains all the files needed to run the calculator. You must download and install DIYDodecad 2.1 first. In order to run the calculator, you follow the instructions of the README file, but type 'eurasia7' instead of 'dv3'.

Terms of use: 'eurasia7', including all files in the downloaded RAR file is free for non-commercial personal use. Commercial uses are forbidden. Contact me for non-personal uses of the calculator.

Technical Details:

The calculator is built using allele frequencies of K=7 ancestral components inferred by ADMIXTURE 1.21 analysis of 2,659 individuals. Markers included in the source datasets, as well as the Family Finder and 23andMe (as of Oct 21) platforms were included. The marker set was thinned of markers with less than 99.5% genotype rate and less than 0.5% minor allele frequency. Linkage-disequilibrium based pruning was carried out with a window size of 250 SNPs, advanced by 25 SNPs and R-squared greater than 0.4. A total of 164,990 SNPs remained after these filtering steps.

All relevant populations available to me, and genotyped at a sufficient number of markers were included. Inclusion of the Kalash population resulted in a population-specific component at K=7, and hence their admixture components were inferred a posteriori. Their proportions are consistent with previous results, showing them to be a "West Asian" population (62.4%) with substantial "South Asian" admixture (37.1%), and near-complete absence of any other genetic components.

23andMe data file changes

2011-10-21T14:18:00.004+03:00

A few recent submissions to the Project have alerted me to the fact that 23andMe has been making changes to its data download. It is unfortunate that such changes are made apparently "silently", as they may negatively impact third-party tools built around the 23andMe data.

Apparently, the orientation of some SNPs has been changed. This should not be a problem for DIYDodecad, as it handles orientation of different companies automatically. A different problem is that apparently some SNPs have been dropped from the data file altogether. This is a problem if you are not using the latest 2.1 version of the DIYDodecad software, so you should upgrade to 2.1. It seems that about 80 of the SNPs expected by the 'dv3' calculator have been removed from the data file download, and these will appear as "absent". I do not expect 80 absent SNPs to have a huge impact on results, as they make up less than 0.1% of all SNPs in dv3.

The change in format has other consequences as well; as many of you know, I have been working on Dodecad v4 for some time now. This would use common markers between 23andMe v2 and v3 platforms and Family Finder Illumina platform. However, I will now have to backtrack on it, to make sure that the marker set used is actually consistent with people's current 23andMe downloads.

If you have a fresh 23andMe downloaded file and DIYDodecad 2.1 and you are unable to run 'dv3' or any other Project calculators, drop me a line.

Eurogenes is upset

2011-10-21T09:06:00.007+03:00

Eurogenes seems to be upset this week, first throwing a tantrum at Dr. McDonald and then at myself. You can probably find the cached text in Google for some time, although Eurogenes has deleted his anti-McDonald tantrum, and changed the verbiage on the one directed against me on advice of some more cool-headed people. Here is the epilogue of his original anti-Dienekes rant:

Dienekes, you've got a spreadsheet online showing all sorts of weird things. You need stop being a prat, and do something about it ASAP.

Eurogenes' animus towards me is not surprising for those who have followed our interactions since the old days. Of course he is benefiting from my work (I have pointed him towards data he didn't know existed, he is using DIYDodecad, as well as the 1000Genomes data extracted with my code by the MDLP), so one would think that if he had any criticism against me, he would at least express it in a more dignified way.

Of course, being rude, ungrateful and mean-spirited does not mean one is wrong! So, what has Eurogenes actually discovered?

He noted the high Ukrainian West/East European ratio produced by Dodecad v3, and objected to my idea that Ukrainians were transitional to the Balkans and the Caucasus. Actually, according to the PCA plot of the Yunusbayev et al. (2011) paper, they are transitional, being situated toward both the Balkans and the Caucasus, relative to Belorussians/Lithuanians, i.e., the populations that generally show peaks of East European-related components. This is also supported by the ADMIXTURE analysis that reveals Ukrainians to possess a Caucasus-centered component largely lacking in other Eastern Slavs, but shared with Balkan/Caucasus populations.

Should I have not tested the new Yunusbayev data with Dodecad v3 and reported their results? Of course not. When one has a measuring instrument, one uses it on new data to test its performance and reports what he sees. This is exactly what I have done. At the same time, one uses the new data to create new measuring instruments that have been trained using all available data, which is also what I have done with euro7 and the upcoming Dodecad v4.

To make matters worse, Eurogenes suggests that my euro7 analysis agrees with his K=10 which was presented two weeks later. So, apparently, I am posting correct information about Ukrainians 2 weeks before he does, and this means that I am turning around to his way of thinking rather than vice versa. Go figure.

Eurogenes continues with his posting of supposed MDS/PCA plots supporting his thesis. Actually, what he has posted are plots based on metric distances in the space of admixture proportions; these are not genetic distances because e.g., a +/- 1% difference in a Sub-Saharan component results in the same Euclidean distance difference as a +/-1% in a European one, although the former affects genetic distance much more strongly than the latter. Metric distances are fine to quickly determine closeness of samples in the space of admixture proportions, but they are certainly no substitute for real genetic distances. I have already linked above with evidence that Ukrainians are transitional to the Balkans and the Caucasus relative to the Yunusbaeyev et al. populations.

I am also, apparently, accused of neglecting to point out the deficiencies of Dodecad v3, and I am invited by Eurogenes to retract it completely! This proposal is equivalent to the idea that we should burn old topographic maps that were based on measurements with sticks, ropes, and trigonometers, because we can now measure distances with laser beams. And, it is funny indeed that I am supposedly neglecting the deficiencies of Dodecad v3 when, 3 weeks before the Eurogenes rant, I post exactly what its limitations are, and how it can be made better.

It is unfortunate that Eurogenes has chosen to go down that path. Envy is not a good guide to behavior, and perhaps, instead of relishing at the prospect of putting others down, he could spend a little more time inventing something of his own.

As for myself, I will continue to work on my tools, and to encourage cross-pollination between different projects for the benefit of all.

UPDATE: In a newer post, Eurogenes attempts to justify his mishandling of MDS, by suggesting that he presented results based on raw SNP data. This is of course nonsense, since Eurogenes does not have the raw SNP data of the Dodecad populations. He is comparing apples and oranges by comparing plots made on raw data with those made in the space of admixture proportions. Furthermore, his supposed findings have no bearing on the Yunusbayev et al. ADMIXTURE and PCA results, posted above.

Comparing different ADMIXTURE runs using Zombies

2011-10-20T13:05:00.013+03:00

My idea of using zombies with ADMIXTURE is the gift that keeps on giving. Remember that "zombies" are synthetic individuals created from ADMIXTURE output, representing the K inferred ancestral components. They can be viewed as hypothetical ancestral individuals representing each of these K components without any admixture from any of the others.

An interesting problem that often comes up is to compare across different ADMIXTURE runs. I can think of at least three different applications of this:

To compare components across different K; for example, how does a "West Asian"-centered component at K=5 differ from a similarly-centered component at K=12?
To compare components across different datasets; for example, how does a "West Asian"-centered component inferred from an existing dataset (e.g., the current Dodecad v3) differ from a "West Asian"-centered one from a new dataset (e.g., the upcoming Dodecad v4, which will also be trained on the valuable new populations of Yunusbayev et al. 2011)
To compare components across different projects; there has been a proliferation of different ancestry projects since the launching of Dodecad nearly a year ago, and since all of them slightly different individuals/SNPs/terminology, it is quite useful to be able to gauge how one component from one project maps onto other components in other projects.

As proof of concept, I took the MDLP calculator from the Magnus Ducatus Lituaniae Project and generated 50 zombies for each of its 7 ancestral components:

Scandinavian
Volga_Region
Altaic
Celto_Germanic
Caucassian_Anatolian_Balkanic
Balto_Slavic
North_Atlantic

I then inferred the ancestry of the MDLP zombies using Dodecad v3, and vice versa. Since Dodecad v3 also includes populations (e.g., Africans) not considered by MDLP, I did not try to map those onto MDLP.

I will comment on the MDLP-to-dv3 mapping:

The MDLP "Scandinavian" component appears to be West/East European with a little Mediterranean and a little Northeast Asian
The MDLP "Volga_Region" component appears to be East European with some Northeast Asian
The MDLP "Altaic" component is West Asian+Northeast Asian+Southeast Asian. Note that in Dodecad v3, the Northeast Asian component peaks at Chukchi, Nganasan, and Koryak, and most other east Eurasian populations have much less of it
The MDLP "Celto-Germanic" component is (surprisingly) Mediterranean-dominated. One possible interpretation is that in the context of MDLP this captures one aspect of the difference between Southwestern and Northeastern Europe -higher Mediterranean in the former-, whereas the...
... MDLP "North-Atlantic" component seems to be entirely West European, and is capturing a different aspect of east-west variation in Europe.
The MDLP "Balto-Slavic" appears the reverse of the "Celto-Germanic" with lower Mediterranean and reversed East/West European
Finally, the MDLP "Caucassian_Anatolian_Balkanic" component is predictably mainly West Asian, but with a little Mediterranean and Southwest Asian as well

A different way of comparing the different components is to include them all in a joint MDS plot, or calculate various types of distances between them (e.g., Fst).

For example, the first couple of dimensions are dominated by the African/Asian components of Dodecad v3 that are not present in MDLP. Notice, however, the position of "Altaic", right where one might expect to find it between West and East Eurasians.

Limiting ourselves to only European populations, we obtain:

It appears that the "North_Atlantic" component may be centered on a small number of related individuals.

I encourage other genome bloggers to try their own hand at comparing their components with those of other projects, or even their own. This process will be made possible if people using ADMIXTURE follow the simple instructions to convert their output for use with DIYDodecad.

Once Dodecad v4 is off the ground, and if I find time to fully automate the process, I will perhaps try to map all my past calculators (i.e., the initial K=10, Dodecad v3, 'bat', 'euro7', 'weac', 'africa9') onto the new golden standard of the Project.

PS: This analysis was done on ~63k SNPs in common between MDLP and Dodecad v3

'euro7' calculator

2011-09-30T12:07:00.017+03:00

I am releasing a new calculator for Europeans, including their immediate neighboring populations around the Black Sea (Caucasus and Anatolia). The calculator can be used with DIYDodecad

There are additional African and Far-Asian population controls, so, in principle, the calculator could be used by non-Europeans/Anatolians/Caucasians, although I would be less confident of their results. For example, people of South Asian ancestry may obtain a Far-Asian result if they use this calculator, due to the deep affinity of Ancestral South Indians with East Asians. Other West Eurasians and West Eurasian-admixed peoples, not from the studied regions (e.g., Arabians or East Africans) will have their West Eurasian components mapped onto the ones used in this calculator.

'euro7' uses 7 ancestral components:

Caucasus
Northwestern
Northeastern
Southeastern
African
Far_Asian
Southwestern

These names represent 7 ancestral populations inferred by ADMIXTURE, and have been chosen based on the geographical regions where each of them achieves its maximum representation. You should always refer to A note of caution on admixture estimates, Interpretation of ADMIXTURE results: component sharing, as well as the average population values in the spreadsheet when interpreting your individual results.

The distribution of these 7 components can be seen in the barplot on the top left, and precise admixture proportions can be found in the spreadsheet. Note that additional samples have been used to infer these components, but as these come from Dodecad populations with less than 5 participants, I am not reporting average values for them, as per the usual project policy.

Here is the neighbor-joining tree based on the Fst divergences between the 7 ancestral components:
Instructions:

You can download the calculator RAR from here (Google docs; File->Download original), or here (sendspace).

You need to extract the contents of the RAR file to the working directory of DIYDodecad. You use it by following exactly the instructions of the DIYDodecad README, but always type 'euro7' instead of 'dv3' in these instructions.

Terms of use: 'euro7', including all files in the downloaded RAR file is free for non-commercial personal use. Commercial uses are forbidden. Contact me for non-personal uses of the calculator.

Calculators released by the Dodecad Project:

Yunusbayev et al. (2011) data assessed with Dodecad v3

2011-09-25T23:26:00.010+03:00

I have acquired the data from the recent Yunusbayev et al. (2011) paper on the Caucasus. This includes the following populations:

Kurds_Y 6
Bulgarians_Y 13
Ukranians_Y 20
Mordovians_Y 15
Armenians_Y 16
Abhkasians_Y 20
Balkars_Y 19
North_Ossetians_Y 15
Chechens_Y 20
Nogais_Y 16
Kumyks_Y 14
Turkmens_Y 15
Tajiks_Y 15

It is a valuable new addition to the Project, and it is commendable that it has been made publicly and easily available so swiftly after the appearance of the Yunusbayev et al. (2011) paper.

To get the ball rolling on the new Yunusbayev et al. data, I will map the new populations onto the Dodecad v3 components; they will be added to the Dodecad v3 spreadsheet as they are calculated.

I have been laboriously designing a new global (including Amerindians and Australasians) Dodecad X1 experimental calculator with 3,010 individuals for a few weeks now, but I guess I will now have to reboot it with 3,214.

Together with some other new data I recently discovered, I now have 9,799 individuals (some duplicates from different sources) in my global database. My Dodecad dataset of 511 individuals from a single country or ethnic group isn't too shabby either. Let's hope for a new data release that will push the data collection above the magic 10,000.

UDDATE:

I have added the first 7 populations to the spreadsheet; the others are being calculated as we speak. Most of them seem in line with expectations, but the Abkhasian sample has one outlier individual (abh27), and has thus been placed in the "Outliers" tab of the spreadsheet; a new set of admixture proportions, minus that outlier individual, will be calculated anew:

UPDATE II: The population portraits have been uploaded to Google Docs as a rar file (Sendspace mirror). Average admixture results have all been entered to the spreadsheet.

'weac' calculator

2011-09-21T21:18:00.004+03:00

This new calculator places individuals on the West Eurasian cline. This cline is the first-order description of variation in West Eurasians, with populations from northern and western Europe falling on one end, and those from the Near East on the other.

On the left, you can see the populations on which the calculator is based, sorted on their average "Atlantic-Baltic" component. The raw data can be found in the spreadsheet.

Note that the main purpose of the calculator is to place European and Near Eastern samples on the West Eurasian cline, and to do so, some African and East Eurasian populations are used as controls. Other types of ancestry (e.g., South Asian or Amerindian) may register as Far-Asian in the context of this test.

You can download the calculator RAR from here (Google docs), or here (sendspace).

You need to extract the contents of the RAR file to the working directory of DIYDodecad. You use it by following exactly the instructions of the DIYDodecad README, but always type 'weac' instead of 'dv3' in these instructions.

Terms of use: 'weac', including all files in the downloaded RAR file is free for non-commercial personal use. Commercial uses are forbidden. Contact me for non-personal uses of the calculator.

Do-It-Yourself Dodecad v 2.1

2011-09-18T12:30:00.006+03:00

DIYDodecad v 2.1 allows incomplete genotype files to be used, i.e., genotype

files that do not include all expected SNP markers used in a calculator. This

is useful to individuals having older genotype files from their testing

companies, and allows the tool to be used with any type of genotype data, and

not only the Illumina platforms currently used by 23andMe and FamilyTreeDNA.

There is a minimum requirement of at least 100 usable SNPs, i.e., SNPs that are

in the genotype file and do not have no-calls.

If you had previously followed the instructions carefully, and got an "end of file reached" error, this was most likely due to your genotype file lacking some of the expected markers used in the calculator. Version 2.1 should work for you.

You can download it from here (Google Docs, File->Download Original), or here (Sendspace). Uncompress DIYDodecad2.1.rar to a local directory on your computer, and follow the instructions in the README.txt file.

Past versions: 2.0, 1.0