Friday, October 31, 2014

Ancient Bronze Age M4 DNA

DNA from an ancient hair sample obtained from the Borum Eshøj Bronze Age burial in Denmark. The burial comprised three individuals in oak coffins, commonly referred to as the woman,• ”the young man,• and the old man.• The M4 sample is from the latter. The site was excavated in 1871-1875 and the coffins dated to c.1350 BC. I converted the M4 raw data into formats familiar to genetic genealogists (or genotyped). I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found the ancient DNA has less SNPs that are common with them. Hence, I did not upload to GEDMatch.

Download: 
Reference:
Carpenter, Meredith L., Jason D. Buenrostro, Cristina Valdiosera, Hannes Schroeder, Morten E. Allentoft, Martin Sikora, Morten Rasmussen et al. "Pulling out the 1%: whole-genome capture for the targeted enrichment of ancient DNA sequencing libraries." The American Journal of Human Genetics 93, no. 5 (2013): 852-864.

Data Used

Ancient Hungarian Neolithic genome - KO1

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 KO1 from Tiszaszőlős-Domaháza site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999931.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used
Related Blogs

Thursday, October 30, 2014

Ancient 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. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999930.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Wednesday, October 29, 2014

Ancient Bulgarian DNA - V2

The authors had sequenced the DNA from human found in a flat cemetery dating to the Late Bronze Age (1500-1100 BC) near the village of Vratitsa, Bulgaria. Nine inhumation burials were excavated between 2003 and 2004. A molar from a juvenile male (age 16-17) was used for DNA analysis. I converted the raw data of this V2 sample into formats familiar to genetic genealogists (i.e., genotyped). I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Carpenter, Meredith L., Jason D. Buenrostro, Cristina Valdiosera, Hannes Schroeder, Morten E. Allentoft, Martin Sikora, Morten Rasmussen et al. "Pulling out the 1%: whole-genome capture for the targeted enrichment of ancient DNA sequencing libraries." The American Journal of Human Genetics 93, no. 5 (2013): 852-864.

Data Used


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 from Ludas-Varjú-dűlő site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999929.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used



Monday, October 27, 2014

Ancient Hungarian Neolithic genome - NE7

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. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999928.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Related Blogs

Sunday, October 26, 2014

Ancient Hungarian Neolithic genome - NE5

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 NE5 from Kompolt-Kigyósér site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry and upload to GEDMatch as kit# F999927.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Related Blog

BAM Analysis Kit

(Version 1.8 released - 1-Aug-2015)

BAM Analysis Kit is a bundle of genome tools that will analyse .BAM raw data file and outputs in file format similar to genetic genealogy companies. The goal of this kit to enable end users to analyse their own genome on their personal computer.

The tool provides the following output,
  • genome_complete.txt.gz - Complete list from all confident sites
  • genome_full_snps.txt.gz - Complete list of all known SNPs
  • filtered-autosomal-o37-results.csv.gz - Filtered by Autosomal DNA SNPs tested by DNA companies
  • filtered-x-chromosome-o37-results.csv.gz - Filtered by X DNA SNPs tested by DNA companies
  • Admixture_Dodecad_Report.html - Dodecad dv3 Population Admixture Report
  • Admixture_Eurogenes_Report.html - Eurogenes K=36 Population Admixture Report
  • Admixture_Globe13_Report.html - Globe13 Population Admixture Report
  • Complete_SNPs_y.csv - List of all identified Y-SNPs along with other columns
  • ISOGG_Y_Haplogroup.txt - ISOGG Y-Haplogroup identification as on 1-Jul-2015
  • MtDNA_Haplogroup.txt - Mt-DNA Haplogroup based on Build 15 (30 Sep 2012)
  • MtDNA_Haplogroup_Report.html - Mt-DNA Haplogroup Report
  • rCRS_mtDNA.txt - MtDNA mutations in rCRS format
  • RSRS_mtDNA.txt - MtDNA mutations in RSRS format
  • telomere.txt - Telomere length
  • telseq.out - Telomere raw output file
  • Variants_Y.txt - Y-DNA Novel Variants
  • Y-STR_Markers.txt - Y-STR Markers
  • Y_SNPs.txt - ISOGG Y-DNA SNPs
  • bam_chr*.vcf.gz - VCF files if 'Delete VCF after processing' is unchecked.
Prerequisites: 
Usage:

Extract the download and click 'BAM Analysis Kit.exe'. Select the .BAM file and click 'Start Analysis'. After clicking 'Start Analysis', a command prompt will automatically open and start executing series of commands.
Screenshot of 

After a few minutes to several hours (or even days depending on your BAM file input and computer speed), the output will be available inside a subfolder called 'out'.

Download:  BAM_Analysis_Kit.zip (2 GB)

Source Code:
Located at 'src' folder and/or uploaded to GitHub

Human Genome Reference: The kit uses GRCh37.75 as reference. and uses snp142 for annotation of output genotype files.

License: The download bundles the following software for easy usage. So, if you are using this tool for non-commercial and/or personal use, you should be alright.

References:
  • Li H.*, Handsaker B.*, Wysoker A., Fennell T., Ruan J., Homer N., Marth G., Abecasis G., Durbin R. and 1000 Genome Project Data Processing Subgroup (2009) The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics, 25, 2078-9. [PMID: 19505943]
  • McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010). The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20:1297-303. [Pubmed]
  • Ding, Zhihao, Massimo Mangino, Abraham Aviv, Tim Spector, and Richard Durbin. "Estimating telomere length from whole genome sequence data." Nucleic acids research (2014): gku181.
  • Gymrek M, Golan D, Rosset S, & Erlich Y. lobSTR: A short tandem repeat profiler for personal genomes. Genome Research. 2012 April 22.
  • SNPedia: a wiki supporting personal genome annotation, interpretation and analysis  Michael Cariaso; Greg Lennon Nucleic Acids Research 2011; doi: 10.1093/nar/gkr798
  • van Oven M, Kayser M. 2009. Updated comprehensive phylogenetic tree of global human mitochondrial DNA variation. Hum Mutat 30(2):E386-E394. http://www.phylotree.org. 
  • doi:10.1002/humu.20921
Change Log :1.8
  • Bug Fix - filtered-x-chromosome-o37-results.csv is empty due to typo fixed.
Change Log :1.7
  • Bug Fix - Unable to load BAM from folders with spaces fixed.
Change Log :1.6
  • Human Genome Upgraded to GRCh37.75
  • SAMtools upgraded to 1.2
  • lobSTR upgraded to 3.0.3
  • SNPs upgraded to dbSNP 142
  • GATK upgraded to 3.4
  • Picard upgraded to 1.134
  • Filters SNPs tested by DNA testing companies
  • Provides mtDNA mutations in both RSRS and rCRS
  • Identifies mtDNA and ISOGG Y haplogroup
  • Reports Population Admixture using dv3, globe13 and eurogenes36.
  • UI/Speed improvements
  • Minor code change and bug fixes
  • lobSTR used to calculate only Y-STR but CODIS processing removed.
  • SNPedia report
  • Download size and operational disk space significantly reduced.
Change Log :1.5
  • Y-STR and CODIS supported for most BAM files.
Change Log :1.4
  • Upgraded lobSTR to v3.0.2, GATK to v3.2.2
  • Output includes more accurate Y-STR values.
  • Includes CODIS output.
  • Separated Y-STR and CODIS as optional.
  • Displays used software version for convenience and advanced use.
  • Adds Read Group tags for BAM files without them.
Change Log :1.3
  • Updated with lobSTR from v2.0.4 to v2.0.8 (beta).
  • Does not delete the VCF file after processing completes.
Change Log :1.2
  • UCSC reference positions are zero based. This caused an offset of 1 position in output result - bug fixed.
Change Log :1.1
  • Some files weren't created if mtDNA is not selected - bug fixed.
Change Log :1.0
  • Works on all BAM files with build 37 positions
  • Extracts SNPs from Autosomal DNA, X-DNA, Y-DNA and mtDNA.
  • Provides mtDNA FASTA.
  • Auto-converts Yoruba references in mtDNA and provides RSRS values.
  • Provides Y-SNPs in ISOGG Nomenclature.
  • Provides Y-STR markers.
  • Calculates Telomere Length.

Ancient Hungarian Neolithic genome - NE2

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 NE2 from Debrecen Tócópart Erdõalja site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs and the filtered SNPs are available for download.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Saturday, October 25, 2014

Ancient Hungarian genome - Neolithic - KO2

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 KO2 from Berettyóújfalu-Morotva-liget site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Ancient Hungarian genome - Bronze Age - BR1

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 BR1 from Kompolt-Kigyósér site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Wednesday, October 22, 2014

Ancient Hungarian Neolithic genome - NE3

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 NE3 from Garadna site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Ancient Hungarian Neolithic genome - NE4

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 NE4 from M. Neol. Tiszadob-Bükk Culture found at Polgár-Ferenci-hát site in Hungary into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Cristina Gamba, Eppie R. Jones, Matthew D. Teasdale, Russell L. McLaughlin, Gloria Gonzalez-Fortes, Valeria Mattiangeli, László Domboróczki, Ivett Kővári, Ildikó Pap, Alexandra Anders, Alasdair Whittle, János Dani, Pál Raczky, Thomas F. G. Higham, Michael Hofreiter, Daniel G. Bradley & Ron Pinhasi "Genome flux and stasis in a five millennium transect of European prehistory" doi:10.1038/ncomms6257.

Data Used

Monday, October 20, 2014

Ajvide70 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Ajvide70 from Pitted Ware Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Sunday, October 19, 2014

Ajvide52 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Ajvide52 from Pitted Ware Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Saturday, October 18, 2014

Ajvide58 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Ajvide58 from Pitted Ware Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch as kit# F999924.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used
Related Blog

Friday, October 17, 2014

Autosomal Segment Analyzer

Autosomal Segment Analyzer allows to analyze individual matching segments of autosomal comparison between two autosomal DNA files and drill down to each SNP.

Prerequisites: Microsoft .Net Framework 4.0

Usage: Just execute it, click Open Files, select two files (FTDNA and/or 23andMe format) and click OK. If you wish to change preferences, click settings and preferences.

Screenshot:
Matching Segments

Download Autosomal Segment Analyzer.exe (47 MB)

Source Code at GitHub.

Known Issues:
The tool is designed specifically and optimized for SNPs tested by DNA companies e.g., FTDNA, 23andMe and ancestry - This is primarily to minimize the file size for mapping Mb/cM (the complete set is huge which is certainly not feasible to be included with application). If you try to compare ancient DNA having SNPs that are not tested by DNA companies, you may get some strange lengths. This is the only known fault I am aware of. While the tool is also Ancient DNA friendly, please compare with filtered ancient DNA version.

Change Log
Version 3.1
  • Ability to save matching genotypes, which are genotypes of common ancestors.
Version 3.0
  • Several bug-fixes. Added cM, Probability and genotype frequency data from OpenSNP. Ancient DNA comparison friendly to analyze smaller segments with lower thresholds.
Version 2.0
  • Several bug-fixes. Removed cM and made Mb only to make it work on new SNP positions.
Version 1.1
  • Unhandled Exception: System.IndexOutOfRangeException - Fixed.
Version 1.0
  • Initial release.

Sunday, October 12, 2014

Gökhem5 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Gökhem5 from Funnel Beaker Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Gökhem4 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Gökhem4 from Funnel Beaker Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Saturday, October 11, 2014

Hinxton DNA

The authors had sequenced whole genome of 5 ancient DNA samples from skeletons excavated from Hinxton, Cambridgeshire, UK with estimated dates from the iron age through the Roman period (2500-1800 years ago). I converted these raw data of samples into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found some ancient DNA has less SNPs that are common with them. Hence, I did not upload those but the rest, I did upload to GEDMatch. Please note that the complete download is merged from several sequence runs and may not be sorted by coordinates.

Download: 

Relationship:


Samples:


SampleAccession NoGEDMatch
 Hinxton-1  ERS389795Less SNPs
 Hinxton-2  ERS389796F999921
 Hinxton-3 ERS389797F999922
 Hinxton-4  ERS389798F999925
 Hinxton-5  ERS389799F999926

Reference:
This data is part of a pre-publication release - Wellcome Trust Sanger Institute.

Data Used
Related Blogs

Friday, October 10, 2014

StoraFörvar11 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of the Mesolithic hunter-gather StoraFörvar11 from Stora Karlsö, Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Thursday, October 9, 2014

Ire8 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Ire8 from Pitted Ware Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Gökhem7 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Gökhem7 from Funnel Beaker Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Wednesday, October 8, 2014

Ajvide53 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Ajvide53 from Pitted Ware Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Ajvide59 DNA

The authors had generated between 0.01 to 2.2-fold genome wide coverage for 6 neolithic hunter-gathers from pitted ware culture, 4 neolithic farmers from funnel beaker culture and 1 late Mesolithic hunter-gatherer. I converted the raw data of Ajvide59 from Pitted Ware Culture excavated in Sweden into formats familiar to genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them. Hence, I did not upload this to GEDMatch. However, complete SNPs are available for download.

Download: 
Reference:
Skoglund, Pontus, Helena Malmström, Ayça Omrak, Maanasa Raghavan, Cristina Valdiosera, Torsten Günther, Per Hall et al. "Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers." Science 344, no. 6185 (2014): 747-750.

Data Used

Sunday, October 5, 2014

Loschbour DNA

To investigate European population history around the time of the agricultural transition, the authors sequenced complete genomes from a ~8,000 year old skeleton from the Loschbour rock shelter in Heffingen, Luxembourg. I converted this raw data into formats familiar to genetic genealogists.

Download: 
Reference:
Ancient human genomes suggest three ancestral populations for present-day Europeans.
Lazaridis, Iosif, Nick Patterson, Alissa Mittnik, Gabriel Renaud, Swapan Mallick, Peter H. Sudmant, Joshua G. Schraiber et al. "Ancient human genomes suggest three ancestral populations for present-day Europeans." Nature 513, 409–413 (2014).

Data Used
Related Blog

Wednesday, October 1, 2014

Linearbandkeramik LBK DNA

To investigate European population history around the time of the agricultural transition, the authors sequenced complete genomes from a ~7,500 year old early farmer from the Linearbandkeramik (LBK) culture from Stuttgart in Germany. I converted this raw data into formats familiar to genetic genealogists.

Download: 
Reference:
Ancient human genomes suggest three ancestral populations for present-day Europeans.
Lazaridis, Iosif, Nick Patterson, Alissa Mittnik, Gabriel Renaud, Swapan Mallick, Peter H. Sudmant, Joshua G. Schraiber et al. "Ancient human genomes suggest three ancestral populations for present-day Europeans." Nature 513, 409–413 (2014).

Data Used

Motala DNA

The Motala samples come from the site of Kanaljorden in the town of Motala, Östergötland, Sweden. The site was excavated between 2009 and 2013. The authors state that these samples are between  7,013 and 6,701 years old. I converted the raw data supplied in this scientific paper to formats familiar with genetic genealogists. I also filtered with SNPs tested by DNA testing companies like FTDNA, 23andMe and Ancestry in order to upload to GEDMatch but found this ancient DNA has less SNPs that are common with them except Motala-12. Hence, I am not uploading the rest to GEDMatch. Motala-1, Motala-2, Motala-3, Motala-4, Motala-6, Motala-9 and Motala-12 are available for download.

Download: 
Reference:
Ancient human genomes suggest three ancestral populations for present-day Europeans.
Lazaridis, Iosif, Nick Patterson, Alissa Mittnik, Gabriel Renaud, Swapan Mallick, Peter H. Sudmant, Joshua G. Schraiber et al. "Ancient human genomes suggest three ancestral populations for present-day Europeans." Nature 513, 409–413 (2014)

Data Used