Friday, October 31, 2014

Analysis of Hungarian Copper age genome - CO1

The Great Hungarian Plain was a crossroads of cultural transformations that have shaped European prehistory. The authors had analysed a 5,000-year transect of human genomes, sampled from petrous bones giving consistently excellent endogenous DNA yields, from 13 Hungarian Neolithic, Copper, Bronze and Iron Age burials including two to high (~22 × ) and seven to ~1 × coverage, to investigate the impact of these on Europe’s genetic landscape. I converted the raw data of CO1 from Apc-Berekalja I. site in Hungary into formats familiar to genetic genealogists and uploaded here. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999930.

Admixture

Eurogenes Admixture Calculator

Dodecad V3 Admixture Calculator

MDLP K23b Admixture Calculator


Eye Color

The above is only based on 3 SNPs, so it may not be accurate.

Runs of Homozygosity

RoH reveals parents of CO1 are not related in their genealogical timeframe.

Telomere

Telomere length of 4.27076 suggests that CO1 is a teenager around the age of 17.

Telomere length of 4.27076 suggesting she is a teenager.
(Image adapted from http://learn.genetics.utah.edu/content/chromosomes/telomeres/)

Mt-DNA

Mt-Haplogroup is identified as H.

Big-Y CSV → Y-SNPs → ISOGG Y-Tree

A few days later after receiving my Big-Y results, I felt the need to download Y-SNPs and plot them on ISOGG Y-Tree in an easy way. FTDNA initially did not provide any download of SNPs. So, the easiest way is to get it directly from the webpage, as the data was readily displayed as a table is to use a browser add-on. So, I went ahead with a Google Chrome Browser and built an add-on called Big Y AddOn, with the ability to download SNPs, and plot on ISOGG Y-Tree and Morley Y-Tree.

I then realized, Y-SNPs are not specific to Big Y testers, but also for Geno 2.0 and other Y-DNA testers. So, I split the Big Y Add-On and created a new called called ISOGG Y-Tree AddOn for Google Chrome. Meanwhile, FTDNA provided a CSV download with contains the Y-SNPs. Hence, I felt the original Big-Y Add On is redundant and depreciated it. I placed a notice in Chrome WebStore and also moved the project to obsolete section. But still more people seems to download it even though the Big Y add-on is obsolete. Hence, after nearly 8 months of operation, I unpublished the Big-Y Add-on from the Chrome WebStore.

So, the obvious question to many is, how to get Y-SNPs from the Big-Y CSV download in-order to use the ISOGG Y-Tree Add-On. The simple answer is, use the Merge-Y tool. I had been responding in emails individually for people who email me. Hence, I thought of  post it as a blog. Briefly, the below steps explain how to add the Big-Y CSV download file to Merge-Y tool, export the Y-SNPs and how to use the Y-SNPs in ISOGG Y-Tree Add-On.

Step 1: Download the Big-Y CSV Download


Step 2: Download the Merge-Y tool. Open it and add the downloaded Big-Y CSV as Y-DNA file.


Step 3: Make sure the file is properly parsed and loaded.


Step 4: In Merge-Y, click File (menu) -> and Export SNPs.


Step 5: It will prompt you to save as a file, which can be opened in a notepad. Open it, as copy it (Ctrl+C) into clipboard.


 Step 6: Install the ISOGG Y-Tree Chrome Addon in your Chrome Browser. Go to extensions in Google Chrome Browser.
Step 7: Click Options for ISOGG Y-Tree Addon.



Step 8: Enter a name and paste the Y-SNPs (Ctrl+V) in Y-SNPs section. Then, click 'Save'.

Step 9: Now, go to ISOGG Y-Tree: www.isogg.org/tree/ISOGG_YDNATreeTrunk.html


Step 10: Enjoy.

If you found these steps useful, feel free to comment below.

Ancient Hungarian Iron age genome - IR1

The Great Hungarian Plain was a crossroads of cultural transformations that have shaped European prehistory. The authors had analysed a 5,000-year transect of human genomes, sampled from petrous bones giving consistently excellent endogenous DNA yields, from 13 Hungarian Neolithic, Copper, Bronze and Iron Age burials including two to high (~22 × ) and seven to ~1 × coverage, to investigate the impact of these on Europe’s genetic landscape. I converted the raw data of IR1 (830-980 cal BC) from Ludas-Varjú-dűlő site in Hungary into formats familiar to genetic genealogists and uploaded here. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999929.

Admixture

Dodecad V3 Aadmixture Calculator

Eurogenes K15 Admixture Calculator

MDLP K23b Admixture Calculator



Eye Color

GEDmatch Eye Color Prediction

HIrisPlex Report

PBlueEye 0.916574821
PIntermediateEye 0.052848709
PBrownEye 0.03057647
Full_AUC_BlueEye 0.940398377
Full_AUC_IntermediateEye 0.743643077
Full_AUC_BrownEye 0.945280146
Numb_missingSNPs_Eye 4
Name_missingSNPs_Eye rs16891982_C / rs12203592_T /
rs12896399_T / rs1393350_T
AUC_Loss_BlueEye 0.022900905
AUC_Loss_IntermediateEye 0.05986763
AUC_Loss_BrownEye 0.018971968
PBlondHair 0.685846523
PBrownHair 0.227750162
PRedHair 0.026530882
PBlackHair 0.059872433
Full_AUC_BlondHair 0.810615722
Full_AUC_BrownHair 0.75106119
Full_AUC_RedHair 0.922711998
Full_AUC_BlackHair 0.848113996
Numb_missingSNPs_Hair 12
Name_missingSNPs_Hair rs86insA_A / rs885479_T / rs1805008_T /
rs1805006_A / Y152OCH_A / rs2228479_A /
rs1110400_C / rs28777_C / rs16891982_C /
rs12821256_G / rs12203592_T / rs683_G
AUC_Loss_BlondHair 0.095088236
AUC_Loss_BrownHair 0.091919902
AUC_Loss_RedHair 0.093115552
AUC_Loss_BlackHair 0.0337268
PLightHair 0.920294911
PDarkHair 0.079705089
Full_AUC_HairShade 0.905443611
Numb_missingSNPs_HairShade 10
Name_missingSNPs_HairShade rs885479_T / rs1805008_T / rs1805006_A /
rs2228479_A / rs1110400_C / rs28777_C /
rs16891982_C / rs12821256_G /
rs12203592_T / rs683_G
AUC_Loss_HairShade 0.052745236
Ref: http://www.erasmusmc.nl/47743/3604975/HIris?lang=en

Runs of Homozygosity

RoH reveals IR1's parents are not related in his genealogical timeframe.


Telomere

Telomere length of 7.5229 suggests IR1 could be a child within age of ~5 when died.

Telomere length of 7.5229 suggesting a child of age less than 5.
(Image adapted from http://learn.genetics.utah.edu/content/chromosomes/telomeres/)

Y-DNA

Y-Haplogroup is N-M231

Y-STR Markers


  • DYS472 = 8
  • DYS643 = 10
  • DYS533 = 11
  • DYS537 = 11
  • YCAIIa/b = 18
  • DYS460 = 11

Mt-DNA

Mt-DNA Haplogroup is G2a1

One-to-Many Comparison

X-Matches on GEDmatch
IR1 has some matches with living people on X-Chromosome.

Wednesday, October 29, 2014

Accuracy of the ages of ancient DNA samples

I was so keen to compare ancient DNA samples with living people. Interestingly, some ancient DNA do match living people. I had been asked several times regarding, how accurate are the ages of these ancient DNA samples.

Introduction

It is generally accepted that radiometric dating is reasonably accurate and the accuracy can be improved by using different elements half-life on the same sample. It is also generally accepted that radiocarbon dating in particular can be calibrated using dendrochronology, which provides a more accurate age. However, both methods has one fundamental assumption that radio active decay rate is always a constant.

In the year 2010, (just 4 years back) scientists discovered that radioactive decay rate is not a constant 1. The authors concluded the following:
(Conclusion from Power spectrum analyses of nuclear decay rates1)
Then in 2011, a review of this experimental evidence does conclude the sun is indeed causing this radioactive decay rate variation 2. Let's listen to the authors themselves.

(Abstract from Analysis of Experiments Exhibiting Time-Varying
Nuclear Decay Rates: Systematic Effects or New Physics?2
)

(Conclusion from Analysis of Experiments Exhibiting Time-Varying
Nuclear Decay Rates: Systematic Effects or New Physics?2)

Then in 2012, there is additional experimental evidence for sun influencing nuclear decay rates3.

(Conclusion from Additional experimental evidence for
a solar influence on nuclear decay rates3
)
(Conclusion from Additional experimental evidence for
a solar influence on nuclear decay rates3
)
Again in 2013, more evidences emerge that sun is causing variations in nuclear decay rate.

(Abstract from Spectral content of 22Na/44Ti decay data: implications for a solar influence.4)

Then this year, in 2014,
(Abstract from Comparative study of beta-decay data for eight nuclides
measured at the Physikalisch-Technische Bundesanstalt5)

It seems to me most researchers do agree that the nuclear decay rate does vary even to the order of 10-3, whether it is solar or not, there are difference in opinions 6.

Conclusion

Radiometric dating is useful only when the core assumption of radioactive decay rate is constant. When this is proven to vary based on external influences, then there is no guarantee that the radiometric dating can provide any reasonable age estimates. If nuclear decay rate varies based on solar activity, so does all the estimated ages using radiometric dating , including these ancient DNA samples also varies. Hence, the ages of these ancient DNA samples are not accurate.

References

1 Javorsek II, D., P. A. Sturrock, R. N. Lasenby, A. N. Lasenby, J. B. Buncher, E. Fischbach, J. T. Gruenwald et al. "Power spectrum analyses of nuclear decay rates." Astroparticle Physics 34, no. 3 (2010): 173-178.

2 Jenkins, Jere H., Ephraim Fischbach, Peter A. Sturrock, and Daniel W. Mundy. "Analysis of Experiments Exhibiting Time-Varying Nuclear Decay Rates: Systematic Effects or New Physics?." arXiv preprint arXiv:1106.1678 (2011).

3 Jenkins, Jere H., Kevin R. Herminghuysen, Thomas E. Blue, Ephraim Fischbach, Daniel Javorsek II, Andrew C. Kauffman, Daniel W. Mundy, Peter A. Sturrock, and Joseph W. Talnagi. "Additional experimental evidence for a solar influence on nuclear decay rates." Astroparticle Physics 37 (2012): 81-88.

4 O’Keefe, Daniel, Brittany L. Morreale, Robert H. Lee, John B. Buncher, J. H. Jenkins, Ephraim Fischbach, T. Gruenwald, D. Javorsek II, and Peter A. Sturrock. "Spectral content of 22Na/44Ti decay data: implications for a solar influence." Astrophysics and Space Science 344, no. 2 (2013): 297-303.

5 Sturrock, P. A., E. Fischbach, D. Javorsek II, J. H. Jenkins, R. H. Lee, J. Nistor, and J. D. Scargle. "Comparative study of beta-decay data for eight nuclides measured at the Physikalisch-Technische Bundesanstalt." Astroparticle Physics 59 (2014): 47-58.

6 Kossert, Karsten, and Ole Nähle. "Disproof of solar influence on the decay rates of 90Sr/90Y." arXiv preprint arXiv:1407.2493 (2014).

Monday, October 27, 2014

Ancient Hungarian Genome (NE7) Analysis

The Great Hungarian Plain was a crossroads of cultural transformations that have shaped European prehistory. The authors had analysed a 5,000-year transect of human genomes, sampled from petrous bones giving consistently excellent endogenous DNA yields, from 13 Hungarian Neolithic, Copper, Bronze and Iron Age burials including two to high (~22 × ) and seven to ~1 × coverage, to investigate the impact of these on Europe’s genetic landscape. I converted the raw data of NE7 from Apc-Berekalja I. site in Hungary into formats familiar to genetic genealogists and made it available for download here. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999928.

Admixture

MDLP Admixture Calculator

Dodecad V3 Admixture Calculator

Eurogenes Admixture Calculator


Eye Color

Eye Color

HIrisPlex Report

PBlueEye NA
PIntermediateEye NA
PBrownEye NA
Full_AUC_BlueEye 0.940398377
Full_AUC_IntermediateEye 0.743643077
Full_AUC_BrownEye 0.945280146
Numb_missingSNPs_Eye 2
Name_missingSNPs_Eye rs16891982_C/rs12913832_T
AUC_Loss_BlueEye 0.325363303
AUC_Loss_IntermediateEye 0.158600074
AUC_Loss_BrownEye 0.334931231
PBlondHair 0.528412718
PBrownHair 0.3337846
PRedHair 0.004163469
PBlackHair 0.133639213
Full_AUC_BlondHair 0.810615722
Full_AUC_BrownHair 0.75106119
Full_AUC_RedHair 0.922711998
Full_AUC_BlackHair 0.848113996
Numb_missingSNPs_Hair 9
Name_missingSNPs_Hair rs86insA_A / Y152OCH_A / rs28777_C /
rs16891982_C / rs4959270_A / rs2402130_G /
rs12913832_T / rs2378249_C / rs683_G
AUC_Loss_BlondHair 0.096772454
AUC_Loss_BrownHair 0.053516898
AUC_Loss_RedHair 0.024799569
AUC_Loss_BlackHair 0.096513017
PLightHair NA
PDarkHair NA
Full_AUC_HairShade 0.905443611
Numb_missingSNPs_HairShade 7
Name_missingSNPs_HairShade rs28777_C /rs16891982_C / rs4959270_A /
rs2402130_G / rs12913832_T /rs2378249_C/ rs683_G
AUC_Loss_HairShade 0.123102156
Refer: http://www.erasmusmc.nl/47743/3604975/HIris?lang=en

HIrisPlex does not reveal the eye color. However, the closest hair color I was able to find based on above values using the paper, 'The HIrisPlex system for simultaneous prediction of hair and eye colour from DNA'.


Runs of Homozygosity

RoH reveals NE7's parent's are 3rd or 4th cousins.

Telomere

Telomere length of 5.723 suggests that he was a boy around 10 years old when he died.

Telomere length of 5.723 suggesting a teenage boy.
(Image adapted from http://learn.genetics.utah.edu/content/chromosomes/telomeres/)

Y-DNA

Y-Haplogroup is I-L1228

Y-STR Markers

  • DYS590 = 8
  • DYS439 = 12

CODIS Markers

  • D7S820 = 13,13

Mt-DNA

Mt-DNA Haplogroup is N1a.