perjantai 17. marraskuuta 2017

Introductory Globetrotter analysis

Globetrotter is a new software being able to estimate admixtures and also admixture dates. The analysis itself is based on autosomal haplotype data, which is produced by the software Chromopainter, version 2.  My job queue was Plink, Shapeit, CromopainterV2 and Globetrotter.   The Plink format data consisted of 399000 SNPs and 254 individuals over the Eurasian continent.  I liked to have more individuals, but I can use only publicly available data and it is always my restriction.

In the first phase I made a phylogenetic tree using softwares Chromopainter and Finestructure.  Chromopainter was run in two phases, at first to define necessary run parameters and in the second phase generating a tree figure and ancestral matrices.  In the next step individual samples were grouped according to the phylogenetic tree and the result was moved to the following Chromopainter runs preceding Globetrotter analysis.  So there was no handmade grouping and all definitions were done by softwares.

Results:



Admixtures

The deep past can't be figured correctly by present day populations.  Names like Finnish, Polish and Eastern_Baltic_Finnic didn't exist thousands years ago and all group names should be understood representing something now unknown.  Another imperfection is that some populations are unmixed.   For example Balts and Basques cannot be defined by any other present day populations, with exception of themselves, which is not clever at all if we want to see ancient migrations.   In those cases there are sure unknown ancient admixtures without present day proxies and for example Balts are figured as East Slavs.

Finns

Khanty_Mansi    0.00669230541442569
Saami    0.0318001424720861
Scandinavian    0.0406288973530398
Eastern_Baltic_Finnic    0.372195068297064
South_Baltic_Finnic    0.547727866737746


Saami

Basque    0.00627519770432461
West_Europe    0.0203347268787166
Mongola    0.0285387511835476
Nganasan    0.0312587449978488
Irish_Scottish    0.0348178173049934
West_Siberia    0.0372717151545831
Khanty_Mansi    0.058915141944102
Eastern_Volga_Finnic_Chuvash    0.108026814008228
Eastern_Baltic_Finnic    0.120473106582914
Finnish    0.554087984240742


Irish

Basque    0.0168485068643567
Southwest_European    0.085582697894791
West_Europe    0.897568795240852


Tatar

Saami    0.00341643675195708
Nganasan    0.00501267346037914
RushanVanch_Tajikistan    0.00854395216066372
West_Siberia    0.0142527316035022
Irish_Scottish    0.0232322099579794
South_Baltic_Finnic    0.0375544108580537
Baltic    0.0616973387576695
Mongola    0.102871971437878
East_Slavic    0.119214847082816
South_European    0.12153228301688
Eastern_Volga_Finnic_Chuvash    0.184584853664197
Western_Volga_Finnic    0.317983363220266


Khanty-Mansi


RushanVanch_Tajikistan    0.00496570412383918
Western_Volga_Finnic    0.00973524498071095
Saami    0.0209045306129885
Scandinavian    0.0314001203298436
Mongola    0.0468217500718522
West_Europe    0.0512201282635752
Eastern_Volga_Finnic_Chuvash    0.322872736453914
West_Siberia    0.510808280436572


Scandinavian

Baltic    0.0039132358786016
Saami    0.0040658994834093
South_Baltic_Finnic    0.331326055831535
West_Europe    0.660694808806454


Western Volga-Finnic

West_Siberia    0.001211877430627
Basque    0.00153548108955792
Mongola    0.00217721497484364
Irish_Scottish    0.00441065912271718
Nganasan    0.00489486172279255
Saami    0.00654435392074552
South_Baltic_Finnic    0.00873613821602628
Khanty_Mansi    0.011149101703621
Eastern_Volga_Finnic_Chuvash    0.0443170163661487
Tatar    0.170123511582196
East_Slavic    0.744899783870725


Baltic

Saami    0.00434883756492699
East_Slavic    0.995651162435073


East Slavs

Western_Volga_Finnic    0.0180131830693537
Mediterranean-East    0.0941857330298036
Central_Europe    0.170383068761459
Baltic    0.717418015139384


Basque

Southwest_European 1


South Baltic-Finnic
  
Saami    0.0015403209540466
Basque    0.00277573750507665
Irish_Scottish    0.00668755305870894
Southwest_European    0.0131644799855559
Eastern_Volga_Finnic_Chuvash    0.0132143162745874
Eastern_Baltic_Finnic    0.0231748074310308
East_Slavic    0.152341012943326
Baltic    0.168097194491377
Scandinavian    0.203236330851964
Finnish    0.415614563156978


East Baltic-Finnic

Nganasan    0.00749839275609302
Khanty_Mansi    0.0101318772456883
Saami    0.0189334364744419
Eastern_Volga_Finnic_Chuvash    0.0341857812007321
Western_Volga_Finnic    0.0445466151938662
Baltic    0.259991450633669
Finnish    0.624712446495509




Finnish admixture dates and proportions.  

date in generations:  69.2367424689291

admixtures:


Khanty_Mansi 0,0290405745
Nganasan 0,0343370651
Saami 0,0360340021
Russian_Pinega 0,0402546721
South_Baltic_Finnic 0,8603336861

The software inferring admixture dates is quite sophisticated and I am still learning how to use it.   Before knowing more about it  I can't comment previous results, they are "as is".   







sunnuntai 29. lokakuuta 2017

Tollense Valley Bronze Age battle field, standardized PCA-results

Using the same standardized data we have the following PCA plot, which differs from what we see on plots made using only partly overlapping SNP sets.  I don't see any reason to use Mediterranean samples, because of the small SNP number of some samples.  What we see in general on the plot is that most ancient samples  fall between Germans and Poles.  We see also that Finns, Russians, Poles and Norwegians show genetic drift.  The most Polish ancient sample is WEZ56 and WEZ54 falls inside the British cluster.  Samples WEZ39, WEZ40 and WEZ51 fall somewhat closer Finns, being still Central European. WEZ56 is the most Polish sample in the original study graphics too.



lauantai 28. lokakuuta 2017

Tollense Valley Bronze Age battle field, standardized F3-results

According to my experience the f3-analysis (and dstat) generates error due to differences in SNP numbers between individuals.  Because the SNP number can vary as to the sample source, I removed all "bad" SNPs from the study data and added Finnish samples to make it equal to other sample groups.   Actually the average SNP amount in individual tests didn't change much from the original situation, with exception of samples gathered from the 1000genomes project.  After this operation the SNP number in each test between ancient and modern samples was almost constant.

Average SNP numbers per ancient sample, the difference inside one test group a few hundreds in maximum

WEZ15    56606
WEZ16    5453
WEZ24    13749
WEZ35-2    28766
WEZ39    9343
WEZ40    21711
WEZ48    6392
WEZ51    15313
WEZ53    14758
WEZ54    29468
WEZ56    28034
WEZ57    34161
WEZ58    21152
WEZ59    28256
WEZ61    34657
WEZ63    11920
WEZ64-1    26150
WEZ71    15698
WEZ74    9891
WEZ77    15721
WEZ83    14999

 Result of f3-tests using Mbuti as an outgroup:



























All data with exception of Finnish samples (1000genomes) are from the study

Addressing Challenges of Ancient DNASequence Data Obtained with NextGeneration Methods


 









































torstai 21. syyskuuta 2017

Estimates of ancient mixture proportions in present-day Europeans / software

The first Linux script makes possible to generate 23andMe format files from EIGENSTRAT-data and the second one estimates ancient mixture proportions of European people.  Download the full package (without Python interpreter) here.   Instructions are included in the README file.

lauantai 16. syyskuuta 2017

European ancient admixtures

This admixture test was done using the latest data from Reich Laboratory and Dna.Land's Admixture program.  Instead of following the rule and using a mixture triangle Steppe-Farmer-HG I picked also the Central-European Bronze Age to ensure the best coverage of European ancestry.  European Bronze Age was built up from all those three dimensions, so results of all those three roots will be somewhat lower than in tests without the European Bronze Age.  This test works best for Europeans and have obvious blind spots in Africa, Northern America, Near East and Central Asia. I took also some Western Asian samples in the interest of seeing the Iranian and Armenian Neolithic proportions.  

All samples were picked randomly, one sample per population, not as population averages.  No consensus was run.   Both, averaging and consensus calculation would minimize fluctuation in results of minor components, like between Siberian and East-Asian.  The data was converted from the EIGENSTRAT data format I usually use in my tests, of course with exception of the project members.  For that purpose I made a small Bash script which converts Eigenstrat to 23andMe format.  The data and Dna.Land's Admixture program will be soon available here and if anyone see the Eigenstrat-to-23andMe conversion useful I'll include also it to the downloadable library.

sunnuntai 13. elokuuta 2017

Project admixture analyses, revised

Now I used more SNP's with the method coded by Dna.Land authors.  It is now also possible to download all necessary tools for DIY purpose.  It works only on Linux and needs Python to be installed.  Here is a help how to install Python on Ubuntu.

Some comments to understand more about results:

- after a lot of testing I found that the Swedish sample bunch published by the study "No Evidence from Genome-Wide Data of a Khazar Origin for the Ashkenazi Jews" (Behar et.al) doesn't fit well with my Swedish project samples and all of them express more Northwest and Central European than the aforementioned Swedish reference.  This happens even if their self-declarations presume some Finnish admixture.   Therefore I decided to label them as East_Scandinavians, which seemed to be correct.  I wonder where they are geographically from.  

- Saami reference samples, unfortunately too few of them were available leading to increased statistic error,  cannot be considered as a source of Siberian.  They represent here a much more diverse source of genetic history.   The small Siberian admixture usually seen in Finnic results is built in Finnish results for the reason that the present-day Siberianness among Finnic people is old and distinct and doesn't match with present Siberians if we simultaneously use also Finnic reference samples.

The summarizing tree:













Results:

FI1
Finnic 54.6
East_Scandinavian 25.5
Saami 8.0
Northeast_European 5.7
Slavic 2.2
Northwest_European 1.0
Central_European 1.3
AMBIG_European 1.7

FI2
Finnic 52.7
Northwest_European 31.3
East_Scandinavian 6.1
Saami 3.8
Northeast_European 2.3
Slavic 1.9
Central_European 1.4

FI3
Finnic 72.9
East_Scandinavian 16.3
Saami 3.6
Baltic 3.4
Northwest_European 1.6
Northeast_European 1.7

FI4
Finnic 49.1
Northwest_European 25.1
East_Scandinavian 12.9
Northeast_European 5.1
Slavic 2.4
Saami 2.9
Baltic 2.3

FI5
Finnic 80.0
East_Scandinavian 13.4
Saami 3.4
Central_European 2.5

FI6
Finnic 54.2
East_Scandinavian 27.2
Baltic 9.3
Northwest_European 2.3
Saami 1.8
Northeast_European 1.7
Mediterranean 1.1
Central_European 2.0

FI7
Finnic 97.8
AMBIG_European 1.7

FI8
Finnic 95.1
East_Scandinavian 2.1
Baltic 1.7
AMBIG_European 1.1

FI9
Finnic 85.7
East_Scandinavian 11.9
Baltic 2.1

FI10
Finnic 64.0
Saami 31.5
Siberian 2.5
Uralic 1.0

FI11
Finnic 92.7
East_Scandinavian 5.2
Saami 2.1

FI12
Finnic 83.6
East_Scandinavian 15.2
AMBIG_European 1.1

FI14
Finnic 77.7
Baltic 16.8
East_Scandinavian 2.9
AMBIG_European 2.1

FI15
Finnic 97.8
AMBIG_European 1.7

FI16
Finnic 73.6
East_Scandinavian 14.6
Northwest_European 5.1
Central_European 5.4
Saami 1.0

FI17
Finnic 67.8
East_Scandinavian 14.8
Central_European 7.1
Slavic 5.1
Saami 1.4
Mediterranean 1.6
AMBIGUOUS 1.1
AMBIG_East_European 1.1

FI18
Finnic 82.0
East_Scandinavian 12.9
Saami 2.9
Baltic 1.5

FI19
Finnic 73.6
East_Scandinavian 14.3
Saami 6.9
Northwest_European 3.8
Slavic 1.0

FI20
Finnic 75.8
East_Scandinavian 17.3
Saami 4.6
Slavic 1.8

FI21
Finnic 94.0
Saami 2.1
AMBIG_European 2.0
Baltic 1.0

FI22
Finnic 94.5
Saami 1.3
Baltic 1.9
AMBIG_European 1.2
AMBIG_East_European 1.1

FI23
Finnic 68.8
East_Scandinavian 20.0
Saami 3.6
Northwest_European 3.3
Slavic 2.4
Central_European 1.7

SC2
Northwest_European 40.3
East_Scandinavian 22.4
Central_European 15.9
Finnic 9.0
Slavic 4.2
Baltic 3.9
Saami 1.6
Mediterranean 1.7
AMBIG_European 1.0

SC3
Northwest_European 52.1
East_Scandinavian 20.5
Finnic 14.8
Slavic 4.1
Central_European 4.3
Baltic 3.9

SC4
Northwest_European 59.5
East_Scandinavian 27.3
Central_European 5.4
Baltic 5.8
Saami 1.8

SC5
Northwest_European 38.1
East_Scandinavian 32.9
Finnic 11.5
Baltic 9.9
Northeast_European 3.4
Uralic 1.6
Central_European 1.9

SC6
Northwest_European 40.8
Finnic 20.7
Northeast_European 13.1
Central_European 9.0
East_Scandinavian 8.4
Slavic 4.0
Saami 2.1
Baltic 1.9

SC7
Northwest_European 45.8
East_Scandinavian 31.9
Finnic 11.5
Mediterranean 6.2
Slavic 2.2
Northeast_European 2.1

Although my primary goal was to find out Finnic and Scandinavian admixtures this obviously works fine for almost all Europeans, at least to some extent.

Other samples for a verification purpose:
 
Irish sample
Northwest_European 90.0
East_Scandinavian 8.7
AMBIG_European 1.3

Western Polish sample
Slavic 49.8
Baltic 18.3
Central_European 14.4
Northwest_European 6.5
Northeast_European 3.5
East_Scandinavian 4.0
Mediterranean 2.3
Uralic 1.1

Sardinian sample
Mediterranean 93.2
Northwest_European 4.5
East_Scandinavian 1.3

Baltic sample
Baltic 70.6
East_Scandinavian 12.3
Slavic 7.9
Northeast_European 6.3
Central_European 2.6
 
Lithuanian/Yotvingian sample
Baltic 49.0
Slavic 37.5
Central_European 5.8
Mediterranean 4.1
Northeast_European 1.8
AMBIG_European 1.7

Estonian sample
Finnic 41.4
Baltic 19.6
Slavic 16.8
Central_European 9.7
East_Scandinavian 7.8
Saami 2.3
Northeast_European 2.3

Genomes Unzipped sample
Mediterranean 45.7
Northwest_European 19.2
Central_European 19.9
East_Scandinavian 12.3
Slavic 1.9

Genomes Unzipped sample
Mediterranean 37.4
Northwest_European 37.0
East_Scandinavian 15.5
Central_European 9.3

Admixture sums don't give full 100 % because all admixtures below 1% are ignored.

Program downloading and running

Download programs here.  Unzip and locate all programs into a same directory.  To run tests you need use a command line "bash ./ajo1.sh <sample-id>,  where sample-id is the file name holding your genetic data in 23andme format.  The sample file must be compressed with gz file extension (gzip format), but on the command line you give only the sample id (sample-id.gz), not the extension.  The test works fine with following genome builds:  HG18, HG19, GRCh36, GRCh37, but if your genome file is in the FtDna format you have to convert it into the 23andme style.  On Linux it is done easily using four command line entries:

first unzip your genome file and then

cp <original filename> <sample-id>
sed -i 's/\"//g' <sample-id>
sed -i 's/,/\t/g' <sample-id>
gzip <sample-id> 

If your data is already in the 23andme format, but not compressed with gz file extension then you need to unzip it first and run the first and fourth commands explained as above.

edit date 14.8.17 time 17:30

Another Estonian results.  I can only say that it is plausible considering the history

Baltic 37.2
Slavic 29.6
Finnic 22.8
East_Scandinavian 8.1
Saami 1.5

edit 15.8.17 time 17:45

A British results.  It looks like Irish with more Mediterranean and minor Central European admixture..

Northwest_European 81.6
Mediterranean 10.3
Baltic 3.4
Central_European 2.9
AMBIG_European 1.8
 








tiistai 27. kesäkuuta 2017

Estonian Corded Ware enigma

The following simple dstat-figure shows the mystery of Estonian Corded Ware samples released during this spring.   There can't be any populational continuum from them to present-day Balts, including Estonians.  All thousands years older hunter-gatherer samples are overwhelmingly closer present-day Balts.  The change regarding HG ancestry can be seen in Western and Central Europe where we see a clear cut decrease of HG ancestry, obviously caused by increasing real Corded Ware and Bell Beaker ancestries.   We have to compare pure Neolithic populations against Estonian CW samples to reach parity in the Baltic area.  There is a tiny evidence about the given continuum;  Finns are closer German BA samples than Balts, giving a hint that there could be some subtle continuum.