Eupedia Forums
Site NavigationEupedia Top > Eupedia Forum & Japan Forum
Page 13 of 13 FirstFirst ... 3111213
Results 301 to 312 of 312

Thread: Dodecad K12b Ancient West Eurasia [by Eupedia Team]

  1. #301
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    Here are studies that I am currently unable to obtain samples for, since I am only able to utilize FTP submitted BAM files. I need to figure out how to utilize Fastq and/or SRA, as well as CRAM, in order to create coordinates:

    New insights into the Tyrolean Iceman's origin and phenotype as inferred by whole-genome sequencing https://www.ebi.ac.uk/ena/browser/view/PRJEB2830 1 *Unclear sample arrangement
    Upper Palaeolithic genomes reveal deep roots of modern Eurasians https://www.ebi.ac.uk/ena/browser/view/PRJEB11364 3 BAMs do not work with WGSextract
    The Neolithic Transition in the Baltic Was Not Driven by Admixture with Early European Farmers https://www.ebi.ac.uk/ena/browser/view/PRJEB18067 9 BAMs do not work with WGSextract
    The genetic history of admixture across inner Eurasia https://www.ebi.ac.uk/ena/browser/view/PRJEB31152 6 BAMs do not work with WGSextract
    Paleogenomic Evidence for Multi-generational Mixing between Neolithic Farmers and Mesolithic Hunter-Gatherers in the Lower Danube Basin https://www.ebi.ac.uk/ena/browser/view/PRJEB20616 6 BAMs do not work with WGSextract
    Extensive farming in Estonia started through a sex-biased migration from the Steppe https://www.ebi.ac.uk/ena/browser/view/PRJEB21037 9 BAMs do not work with WGSextract
    Genomic signals of migration and continuity in Britain before the Anglo-Saxons https://www.ebi.ac.uk/ena/browser/view/PRJEB11004 14 BAMs do not work with WGSextract
    The population genomics of archaeological transition in west Iberia: Investigation of ancient substructure using imputation and haplotype-based methods https://www.ebi.ac.uk/ena/browser/view/PRJEB14737 14 BAMs do not work with WGSextract
    A western route of prehistoric human migration from Africa into the Iberian Peninsula https://www.ebi.ac.uk/ena/browser/view/PRJEB29189 21 BAMs do not work with WGSextract
    The first horse herders and the impact of early Bronze Age steppe expansions into Asia https://www.ebi.ac.uk/ena/browser/view/PRJEB26349 111 BAMs do not work with WGSextract
    Understanding 6th-century barbarian social organization and migration through paleogenomics https://www.ebi.ac.uk/ena/browser/view/PRJEB27220 53 No FTP BAMs
    Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genome https://www.ebi.ac.uk/ena/browser/view/PRJEB11995 28 No FTP BAMs
    A genomic Neolithic time transect of hunter-farmer admixture in central Poland https://www.ebi.ac.uk/ena/browser/view/PRJNA318237 17 No FTP BAMs
    Ancient genomes from North Africa evidence prehistoric migrations to the Maghreb from both the Levant and Europe https://www.ebi.ac.uk/ena/browser/view/PRJEB22699 23 No FTP BAMs
    Continuity and Admixture in the Last Five Millennia of Levantine History from Ancient Canaanite and Present-Day Lebanese Genome Sequences https://www.ebi.ac.uk/ena/browser/view/PRJEB21330 100 No FTP BAMs
    A Transient Pulse of Genetic Admixture from the Crusaders in the Near East Identified from Ancient Genome Sequences https://www.ebi.ac.uk/ena/browser/view/PRJEB31618 116 No FTP BAMs
    The genetic prehistory of the Baltic Sea region https://www.ebi.ac.uk/ena/browser/view/PRJNA421333 80 No FTP BAMs
    Ancient Genomes Reveal Yamnaya-Related Ancestry and a Potential Source of Indo-European Speakers in Iron Age Tianshan https://www.ebi.ac.uk/ena/browser/view/PRJEB32336 10 No FTP BAMs
    A Common Genetic Origin for Early Farmers from Mediterranean Cardial and Central European LBK Cultures https://www.ebi.ac.uk/ena/browser/view/PRJNA280812 12 No FTP BAMs
    Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic European https://www.ebi.ac.uk/ena/browser/view/PRJNA230689 1 No FTP BAMs
    Iron Age and Anglo-Saxon genomes from East England reveal British migration history (Hinxton) https://www.ebi.ac.uk/ena/browser/view/PRJEB4604 92 No FTP BAMs
    Iron Age and Anglo-Saxon genomes from East England reveal British migration history (Linton and Oakington) https://www.ebi.ac.uk/ena/browser/view/PRJEB6915 18 No FTP BAMs
    Genomic diversity and admixture differs for Stone-Age Scandinavian foragers and farmers https://www.ebi.ac.uk/ena/browser/view/PRJEB6090 35 No FTP BAMs
    Paleogenomics. Genomic structure in Europeans dating back at least 36,200 years https://www.ebi.ac.uk/ena/browser/view/PRJEB7618 1 BAMs do not work with WGSextract
    Unraveling ancestry, kinship, and violence in a Late Neolithic mass grave https://www.ebi.ac.uk/ena/browser/view/PRJEB28451 24 BAMs do not work with WGSextract
    Ancient Egyptian mummy genomes suggest an increase of Sub-Saharan African ancestry in post-Roman periods https://www.ebi.ac.uk/ena/browser/view/PRJEB15464 93 Raw data files are too small
    ANGSD: Analysis of Next Generation Sequencing Data ? ? *Cannot locate samples
    Ancient admixture in human history ? ? *Cannot locate samples
    A Late Bronze Age II clay coffin from Tel Shaddudin the Central Jezreel Valley, Israel: context andhistorical implications ? ? *Cannot locate samples
    Testing support for the northern and southern dispersal routes out of Africa: an analysis of Levantine and southern Arabian populations ? ? *Cannot locate samples
    Ancient DNA of Phoenician remains indicates discontinuity in the settlement history of Ibiza accession numbers: MH43585-43559 ? Author to upload bams

  2. #302
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    1 members found this post helpful.
    Here are non-Homo Sapien studies, but I will not include them in the project.

    A high-coverage genome sequence from an archaic Denisovan individual https://www.ebi.ac.uk/ena/browser/view/PRJEB3092
    A high-coverage Neandertal genome from Vindija Cave in Croatia https://www.ebi.ac.uk/ena/browser/view/PRJEB21157 & https://www.ebi.ac.uk/ena/browser/view/PRJEB21195
    The complete genome sequence of a Neanderthal from the Altai Mountains https://www.ebi.ac.uk/ena/browser/view/PRJEB1265 & https://www.ebi.ac.uk/ena/browser/view/PRJEB1757
    The genome of the offspring of a Neanderthal mother and a Denisovan father https://www.ebi.ac.uk/ena/browser/view/PRJEB24663
    Reconstructing the genetic history of late Neanderthals PRJEB21870; PRJEB21875; PRJEB21881; PRJEB21882: PRJEB21883

  3. #303
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    1 members found this post helpful.
    Quote Originally Posted by Jovialis View Post
    I will endeavor to potentially add 1,547 new DNA samples from 37 Ancient DNA studies. I obtained the sources from the Reich Lab data set. I specifically took solely DNA studies from the West Eurasian region; Europe, Middle East, and North Africa. While excluding east Asian, North American, South Asia, Sub-Saharan African, and Oceania studies. I have already located all of the ENA download links, and excluded studies that do not offer BAM format compatible with the means of which I will process the files.

    I currently have 1,315 raw data files from 20 DNA studies, that I can create coordinates for any calculator. If I include the new additions from the 37 studies, I will potentially have up to 2,800+ files give or take, from 57 DNA studies.

    There are currently 3,589 aDNA samples, I will have 2,800 of them. Which would probably be 95% of all the West Eurasian DNA samples there are.

    Fortunately, some of the ones I am missing are on gedmatch, so we could have up to 99% of them.
    Here is where the project currently is:

    Completed Studies (Raw data files obtained)

    Pending Studies (Work in progress)

    Problem Studies (Will not be included unless resolved)

    Non-West Eurasian Studies (Will not be included)

    Non-Homo Sapien Studies(Will not be included)

  4. #304
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    Quote Originally Posted by Jovialis View Post
    Here are studies that I am currently unable to obtain samples for, since I am only able to utilize FTP submitted BAM files. I need to figure out how to utilize Fastq and/or SRA, as well as CRAM, in order to create coordinates:

    New insights into the Tyrolean Iceman's origin and phenotype as inferred by whole-genome sequencing https://www.ebi.ac.uk/ena/browser/view/PRJEB2830 1 *Unclear sample arrangement
    Upper Palaeolithic genomes reveal deep roots of modern Eurasians https://www.ebi.ac.uk/ena/browser/view/PRJEB11364 3 BAMs do not work with WGSextract
    The Neolithic Transition in the Baltic Was Not Driven by Admixture with Early European Farmers https://www.ebi.ac.uk/ena/browser/view/PRJEB18067 9 BAMs do not work with WGSextract
    The genetic history of admixture across inner Eurasia https://www.ebi.ac.uk/ena/browser/view/PRJEB31152 6 BAMs do not work with WGSextract
    Paleogenomic Evidence for Multi-generational Mixing between Neolithic Farmers and Mesolithic Hunter-Gatherers in the Lower Danube Basin https://www.ebi.ac.uk/ena/browser/view/PRJEB20616 6 BAMs do not work with WGSextract
    Extensive farming in Estonia started through a sex-biased migration from the Steppe https://www.ebi.ac.uk/ena/browser/view/PRJEB21037 9 BAMs do not work with WGSextract
    Genomic signals of migration and continuity in Britain before the Anglo-Saxons https://www.ebi.ac.uk/ena/browser/view/PRJEB11004 14 BAMs do not work with WGSextract
    The population genomics of archaeological transition in west Iberia: Investigation of ancient substructure using imputation and haplotype-based methods https://www.ebi.ac.uk/ena/browser/view/PRJEB14737 14 BAMs do not work with WGSextract
    A western route of prehistoric human migration from Africa into the Iberian Peninsula https://www.ebi.ac.uk/ena/browser/view/PRJEB29189 21 BAMs do not work with WGSextract
    The first horse herders and the impact of early Bronze Age steppe expansions into Asia https://www.ebi.ac.uk/ena/browser/view/PRJEB26349 111 BAMs do not work with WGSextract
    Understanding 6th-century barbarian social organization and migration through paleogenomics https://www.ebi.ac.uk/ena/browser/view/PRJEB27220 53 No FTP BAMs
    Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genome https://www.ebi.ac.uk/ena/browser/view/PRJEB11995 28 No FTP BAMs
    A genomic Neolithic time transect of hunter-farmer admixture in central Poland https://www.ebi.ac.uk/ena/browser/view/PRJNA318237 17 No FTP BAMs
    Ancient genomes from North Africa evidence prehistoric migrations to the Maghreb from both the Levant and Europe https://www.ebi.ac.uk/ena/browser/view/PRJEB22699 23 No FTP BAMs
    Continuity and Admixture in the Last Five Millennia of Levantine History from Ancient Canaanite and Present-Day Lebanese Genome Sequences https://www.ebi.ac.uk/ena/browser/view/PRJEB21330 100 No FTP BAMs
    A Transient Pulse of Genetic Admixture from the Crusaders in the Near East Identified from Ancient Genome Sequences https://www.ebi.ac.uk/ena/browser/view/PRJEB31618 116 No FTP BAMs
    The genetic prehistory of the Baltic Sea region https://www.ebi.ac.uk/ena/browser/view/PRJNA421333 80 No FTP BAMs
    Ancient Genomes Reveal Yamnaya-Related Ancestry and a Potential Source of Indo-European Speakers in Iron Age Tianshan https://www.ebi.ac.uk/ena/browser/view/PRJEB32336 10 No FTP BAMs
    A Common Genetic Origin for Early Farmers from Mediterranean Cardial and Central European LBK Cultures https://www.ebi.ac.uk/ena/browser/view/PRJNA280812 12 No FTP BAMs
    Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic European https://www.ebi.ac.uk/ena/browser/view/PRJNA230689 1 No FTP BAMs
    Iron Age and Anglo-Saxon genomes from East England reveal British migration history (Hinxton) https://www.ebi.ac.uk/ena/browser/view/PRJEB4604 92 No FTP BAMs
    Iron Age and Anglo-Saxon genomes from East England reveal British migration history (Linton and Oakington) https://www.ebi.ac.uk/ena/browser/view/PRJEB6915 18 No FTP BAMs
    Genomic diversity and admixture differs for Stone-Age Scandinavian foragers and farmers https://www.ebi.ac.uk/ena/browser/view/PRJEB6090 35 No FTP BAMs
    Paleogenomics. Genomic structure in Europeans dating back at least 36,200 years https://www.ebi.ac.uk/ena/browser/view/PRJEB7618 1 BAMs do not work with WGSextract
    Unraveling ancestry, kinship, and violence in a Late Neolithic mass grave https://www.ebi.ac.uk/ena/browser/view/PRJEB28451 24 BAMs do not work with WGSextract
    Ancient Egyptian mummy genomes suggest an increase of Sub-Saharan African ancestry in post-Roman periods https://www.ebi.ac.uk/ena/browser/view/PRJEB15464 93 Raw data files are too small
    ANGSD: Analysis of Next Generation Sequencing Data ? ? *Cannot locate samples
    Ancient admixture in human history ? ? *Cannot locate samples
    A Late Bronze Age II clay coffin from Tel Shaddudin the Central Jezreel Valley, Israel: context andhistorical implications ? ? *Cannot locate samples
    Testing support for the northern and southern dispersal routes out of Africa: an analysis of Levantine and southern Arabian populations ? ? *Cannot locate samples
    Ancient DNA of Phoenician remains indicates discontinuity in the settlement history of Ibiza accession numbers: MH43585-43559 ? Author to upload bams
    Thankfully, there are gedmatch kits for some of these studies. Moreover, there are already coordinates for some of these for Dodecad K12b included in the existing list. For example, we already have CEG Amorim et al 2018. I just don't have the raw data files to utilize for other calculators, for those specific studies. We also already have Ötzi.

  5. #305
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    Once I finish the West Eurasian studies that I can, I will move on to the non-West Eurasian studies.

  6. #306
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    3 members found this post helpful.
    In addition to the 400 new samples from the Bell Beaker paper, here are the coordinates for the new studies I have included. I will give the appropriate archeological information, once I am done. These 8 studies didn't have that many samples, but many of the files were huge. I still have 15 studies to go, but with over a thousand samples left:

    Code:
    H_Malmström_et_al._2019:ajv54,0,1.42,0,0,30.67,65.9,0,0,0,0,0,2
    H_Malmström_et_al._2019:ber2F,11.14,1.77,0,0,23.35,51.06,2.05,0.31,0,0,8.25,2.08
    H_Malmström_et_al._2019:oll007,9.45,0.02,0,1.38,33.34,45.34,0.49,0.86,0.97,0,7.12,1.04
    H_Malmström_et_al._2019:oll009,8.29,0.29,0,0,36.86,50.43,0.3,0.04,0,0,2.85,0.94
    H_Malmström_et_al._2019:oll010,9.85,0,0,0.58,31.76,50.61,0,0,0,0,5.99,1.22
    H_Malmström_et_al._2019:poz44,17.34,1.17,0,0,13.69,58.69,3.48,0.76,0,0,4.73,0.15
    H_Malmström_et_al._2019:poz81,26.07,1.99,0,0,9.07,60.49,0.24,0,0,0,0,2.14
    H_Malmström_et_al._2019:ros3,0,1.06,1.29,0,61.05,11.23,0,0,11.51,0.12,12.95,0.8
    H_Malmström_et_al._2019:ros005,0,0,2.25,0.84,59.11,19.45,0.02,0,9.18,0,8.87,0.28
    Broushaki_et_al._2016:AH1,66.39,0,0,1.02,0,0.09,7.83,1.19,3.06,0,16.99,3.44
    Broushaki_et_al._2016:AH2,63.99,0,0,2.76,0,0,6.41,2.52,5.04,0,16.65,2.63
    Broushaki_et_al._2016:AH4,63.77,2.47,0,0,0,0,6.51,0.34,7.73,0,15.36,3.81
    Broushaki_et_al._2016:F38,25.65,0.25,0,0,9.04,4.5,3.43,0,14.62,0,40.6,1.91
    Broushaki_et_al._2016:WC1,57.56,0,0,0,0,0,8.04,0.57,6.98,0,23.25,3.6
    M_Krzewińska_et_al._2018_(Vikings):2072,3.04,0,4.72,4.28,19.03,66.26,0,0,0,0,0,2.67
    M_Krzewińska_et_al._2018_(Vikings):84001,6.89,1.42,0.83,0.41,33.37,50.53,0,0,0,0.4,3.08,3.06
    M_Krzewińska_et_al._2018_(Vikings):84005,5.44,0.75,0.46,1.13,26.1,58.18,1.65,0,2.34,0,2.13,1.82
    M_Krzewińska_et_al._2018_(Vikings):84035,7.41,2.36,0,0,32.78,46.42,2.82,0,2.47,0,5.13,0.62
    M_Krzewińska_et_al._2018_(Vikings):97002,8.35,0,0,0,30.82,44.64,0,2.78,0,2.55,10.66,0.22
    M_Krzewińska_et_al._2018_(Vikings):97026,4.44,1.68,0,1.21,33.29,47.72,0,0,0,0,10.01,1.65
    M_Krzewińska_et_al._2018_(Vikings):97029,7.96,2.39,0,1.6,35.05,49.29,0,1.84,0,0,1.03,0.84
    M_Krzewińska_et_al._2018_(Vikings):bns023-b1e1l1,13.9,0,0,0,45.45,23.47,0,0,0,3.56,12.26,1.37
    M_Krzewińska_et_al._2018_(Vikings):grt035,7.88,0.67,1.24,0.27,40.98,45.48,0.1,0.95,0,0,2.16,0.26
    M_Krzewińska_et_al._2018_(Vikings):grt036,6.86,0.27,0,0.88,30.92,51.42,0.55,0.39,0.7,0,6.36,1.65
    M_Krzewińska_et_al._2018_(Vikings):gtm021-b1e1l1p1,4.76,0,0,1.49,29.3,53.64,0,0,0.71,0.78,6.76,2.57
    M_Krzewińska_et_al._2018_(Vikings):gtm127-b1e1l1p1,6.03,0.69,1.8,1.82,43.75,42.39,0,0,0,0,3.51,0
    M_Krzewińska_et_al._2018_(Vikings):KAL006,4.13,4.31,0,0.21,17.24,67.71,1.68,0.62,0,0,3.32,0.78
    M_Krzewińska_et_al._2018_(Vikings):kal009,0,0,0,0,16.54,74.03,2.91,0,0.24,0,6.28,0
    M_Krzewińska_et_al._2018_(Vikings):kls001-b1e1l1,12.63,0,0,0,35.55,45.7,0,0,0,1.6,2.62,1.89
    M_Krzewińska_et_al._2018_(Vikings):nuf002-b1e1l1p1,10.38,0.78,0,0,30.78,44.55,0,0,0,0,11.76,1.74
    M_Krzewińska_et_al._2018_(Vikings):stg020,6.31,4.05,0,0,24.59,62.45,0,0,0,0,1.35,1.24
    M_Krzewińska_et_al._2018_(Vikings):stg021,6.5,1.37,1.24,0.86,32.69,47.88,1.72,0.66,0,0,5.2,1.88
    M_Krzewińska_et_al._2018_(Vikings):stg026,2.73,1.13,0,0.57,30.6,56.82,0,0,0,0,5.41,2.75
    M_Krzewińska_et_al._2018_(Vikings):urm035,5.96,1.19,0.38,0,31.32,53.92,2.69,0.03,0,0,2.91,1.59
    M_Krzewińska_et_al._2018_(Vikings):urm045,3.21,0,0.51,0,24.75,57.23,0,2.18,0,0.05,12.06,0
    M_Krzewińska_et_al._2018_(Vikings):urm160,5.95,1.97,0.49,0.85,28.25,55.52,0,0.46,0,0,4.58,1.92
    M_Krzewińska_et_al._2018_(Vikings):urm161,8.81,0,0,0,41.48,43.45,3.12,0,0,0,0,3.14
    C_Valdiosera_et_al._2018:atp002,0,0.03,5.12,0.55,62.93,13.54,0,0.48,4.78,1.62,6.7,4.26
    C_Valdiosera_et_al._2018:atp005,0,2.01,1.09,0,60.84,0.31,0,0,11.22,0,20.99,3.54
    C_Valdiosera_et_al._2018:atp12-1420,0,0,5.74,0.83,68.17,15.8,0.24,0,5.32,0.38,2.75,0.76
    C_Valdiosera_et_al._2018:atp016,0,0,5.35,0.42,68.81,5.51,0,0.33,7.06,0,12.38,0.13
    C_Valdiosera_et_al._2018:atp019,0,1.8,4.25,0,57.46,0.34,0,0,5.16,0.73,26.62,3.63
    C_Valdiosera_et_al._2018:atp019,0,0,7.52,0.71,62.29,1.56,0,0,7.84,0,19.26,0.81
    C_Valdiosera_et_al._2018:c40331,0,0,3.16,1.06,67.38,11.19,0,0,4.72,0,11.94,0.56
    C_Valdiosera_et_al._2018:esp005,3.66,0.8,3.69,1.65,53.52,26.43,0,0,2.04,0.18,5.89,2.13
    C_Valdiosera_et_al._2018:mur,0,0,5.67,0,66.23,2.59,0,0.46,8.21,1.52,14.45,0.87
    C_Valdiosera_et_al._2018:pir001,0,0.66,1.98,0.37,55.66,23.52,3.77,0,8.17,0,3.33,2.54
    C_Valdiosera_et_al._2018:por002,0,0,5.37,0.02,64.98,15.06,0,0,6.18,0.7,6.47,1.23
    C_Valdiosera_et_al._2018:por003,0,0,3.03,0,63.76,26.93,0,0,0.23,0,0,6.05
    C_Valdiosera_et_al._2018:por003,3.94,0,5.6,0,52.18,18.95,0.66,2.75,6.57,0,8.92,0.42
    C_Valdiosera_et_al._2018:por004,0,0.67,1.47,0.21,63.5,15.9,0,0.26,9.07,0,8.05,0.87
    C_Valdiosera_et_al._2018:san216,0,0,1.47,1.06,68.69,11.03,0,0.37,7.4,0,7.71,2.27
    T_Günther_et_al._‎2018:H22,0,7.17,0,0,7.56,82.86,0,0,0,0,0,2.41
    T_Günther_et_al._‎2018:H26,0,5.15,0,0,11.42,80.94,0.61,0,0,0.2,0,1.68
    T_Günther_et_al._‎2018:sbj001,0,3.12,0,0,11.18,84.49,0,0.19,0,0,0,1.03
    T_Günther_et_al._‎2018:sf11,0,3.86,0,0,22.4,68.89,2.74,0,0,0,0,2.11
    T_Günther_et_al._‎2018:stg001,0,4.84,0,0,11.19,83.35,0,0,0,0,0,0.62
    AG_Nikitin_et_al:I6912_all,6.42,0,7.58,0,46.18,36.28,0,0,0.2,0,3.33,0
    AG_Nikitin_et_al:I6913,0,0,0,0,58.75,41.25,0,0,0,0,0,0
    AG_Nikitin_et_al:I6914,0,0,4.67,0.17,50.82,0,0,0.03,14.5,0,29.81,0
    R_Rodríguez-Varela_et_al._2018:gun002,0,1.31,31.56,0,24.78,1.36,2.41,8.3,15.17,0,8.59,6.52
    R_Rodríguez-Varela_et_al._2018:gun005,0,0,23.21,1.53,28.6,4.15,1.69,7.18,17.37,0,11.07,5.21
    R_Rodríguez-Varela_et_al._2018:gun008,0,1.97,26.93,0,30.43,2.24,0,10.25,14.64,0,9.75,3.78
    R_Rodríguez-Varela_et_al._2018:gun011,0,0,34.12,1.26,20.39,1.62,1.13,8.15,16.3,0,10.26,6.77
    R_Rodríguez-Varela_et_al._2018:gun012,0,0,35.63,0,21.14,1.91,0.21,10.49,12.35,1.01,11.28,5.98
    Z_Hofmanová_et_al._2016:Bar8,0,0,4.96,0,45.12,0,0,0,13.39,0.45,33.88,2.2
    Z_Hofmanová_et_al._2016:Bar31,0,0,4.68,0.92,45.75,0,0,0,14.24,0,31.86,2.55
    Z_Hofmanová_et_al._2016:Klei10,0,0,2.1,0.17,46.06,0,0,0,14.18,0,35.73,1.76
    Z_Hofmanová_et_al._2016:Pal7,0,0,4.41,0.01,47.42,0,0,0,13.07,0.67,32.97,1.44
    Z_Hofmanová_et_al._2016:Rev5,0,0,4.74,0,48.42,0,0,0,12.15,0.13,33.21,1.35
    Fu_etal._2015:Oase1,9.78,0.91,0.43,14.51,2.67,12.1,29.17,11.2,1.93,7.17,1.73,8.39

  7. #307
    Regular Member Duarte's Avatar
    Join Date
    08-01-19
    Location
    Belo Horizonte
    Posts
    1,811

    Y-DNA haplogroup
    R1b-DF27-FGC35133

    Ethnic group
    Portuguese-Brazilian
    Country: Brazil



    2 members found this post helpful.
    Quote Originally Posted by Jovialis View Post
    In addition to the 400 new samples from the Bell Beaker paper, here are the coordinates for the new studies I have included. I will give the appropriate archeological information, once I am done. These 8 studies didn't have that many samples, but many of the files were huge. I still have 15 studies to go, but with over a thousand samples left:

    Code:
    H_Malmström_et_al._2019:ajv54,0,1.42,0,0,30.67,65.9,0,0,0,0,0,2
    H_Malmström_et_al._2019:ber2F,11.14,1.77,0,0,23.35,51.06,2.05,0.31,0,0,8.25,2.08
    H_Malmström_et_al._2019:oll007,9.45,0.02,0,1.38,33.34,45.34,0.49,0.86,0.97,0,7.12,1.04
    H_Malmström_et_al._2019:oll009,8.29,0.29,0,0,36.86,50.43,0.3,0.04,0,0,2.85,0.94
    H_Malmström_et_al._2019:oll010,9.85,0,0,0.58,31.76,50.61,0,0,0,0,5.99,1.22
    H_Malmström_et_al._2019:poz44,17.34,1.17,0,0,13.69,58.69,3.48,0.76,0,0,4.73,0.15
    H_Malmström_et_al._2019:poz81,26.07,1.99,0,0,9.07,60.49,0.24,0,0,0,0,2.14
    H_Malmström_et_al._2019:ros3,0,1.06,1.29,0,61.05,11.23,0,0,11.51,0.12,12.95,0.8
    H_Malmström_et_al._2019:ros005,0,0,2.25,0.84,59.11,19.45,0.02,0,9.18,0,8.87,0.28
    Broushaki_et_al._2016:AH1,66.39,0,0,1.02,0,0.09,7.83,1.19,3.06,0,16.99,3.44
    Broushaki_et_al._2016:AH2,63.99,0,0,2.76,0,0,6.41,2.52,5.04,0,16.65,2.63
    Broushaki_et_al._2016:AH4,63.77,2.47,0,0,0,0,6.51,0.34,7.73,0,15.36,3.81
    Broushaki_et_al._2016:F38,25.65,0.25,0,0,9.04,4.5,3.43,0,14.62,0,40.6,1.91
    Broushaki_et_al._2016:WC1,57.56,0,0,0,0,0,8.04,0.57,6.98,0,23.25,3.6
    M_Krzewińska_et_al._2018_(Vikings):2072,3.04,0,4.72,4.28,19.03,66.26,0,0,0,0,0,2.67
    M_Krzewińska_et_al._2018_(Vikings):84001,6.89,1.42,0.83,0.41,33.37,50.53,0,0,0,0.4,3.08,3.06
    M_Krzewińska_et_al._2018_(Vikings):84005,5.44,0.75,0.46,1.13,26.1,58.18,1.65,0,2.34,0,2.13,1.82
    M_Krzewińska_et_al._2018_(Vikings):84035,7.41,2.36,0,0,32.78,46.42,2.82,0,2.47,0,5.13,0.62
    M_Krzewińska_et_al._2018_(Vikings):97002,8.35,0,0,0,30.82,44.64,0,2.78,0,2.55,10.66,0.22
    M_Krzewińska_et_al._2018_(Vikings):97026,4.44,1.68,0,1.21,33.29,47.72,0,0,0,0,10.01,1.65
    M_Krzewińska_et_al._2018_(Vikings):97029,7.96,2.39,0,1.6,35.05,49.29,0,1.84,0,0,1.03,0.84
    M_Krzewińska_et_al._2018_(Vikings):bns023-b1e1l1,13.9,0,0,0,45.45,23.47,0,0,0,3.56,12.26,1.37
    M_Krzewińska_et_al._2018_(Vikings):grt035,7.88,0.67,1.24,0.27,40.98,45.48,0.1,0.95,0,0,2.16,0.26
    M_Krzewińska_et_al._2018_(Vikings):grt036,6.86,0.27,0,0.88,30.92,51.42,0.55,0.39,0.7,0,6.36,1.65
    M_Krzewińska_et_al._2018_(Vikings):gtm021-b1e1l1p1,4.76,0,0,1.49,29.3,53.64,0,0,0.71,0.78,6.76,2.57
    M_Krzewińska_et_al._2018_(Vikings):gtm127-b1e1l1p1,6.03,0.69,1.8,1.82,43.75,42.39,0,0,0,0,3.51,0
    M_Krzewińska_et_al._2018_(Vikings):KAL006,4.13,4.31,0,0.21,17.24,67.71,1.68,0.62,0,0,3.32,0.78
    M_Krzewińska_et_al._2018_(Vikings):kal009,0,0,0,0,16.54,74.03,2.91,0,0.24,0,6.28,0
    M_Krzewińska_et_al._2018_(Vikings):kls001-b1e1l1,12.63,0,0,0,35.55,45.7,0,0,0,1.6,2.62,1.89
    M_Krzewińska_et_al._2018_(Vikings):nuf002-b1e1l1p1,10.38,0.78,0,0,30.78,44.55,0,0,0,0,11.76,1.74
    M_Krzewińska_et_al._2018_(Vikings):stg020,6.31,4.05,0,0,24.59,62.45,0,0,0,0,1.35,1.24
    M_Krzewińska_et_al._2018_(Vikings):stg021,6.5,1.37,1.24,0.86,32.69,47.88,1.72,0.66,0,0,5.2,1.88
    M_Krzewińska_et_al._2018_(Vikings):stg026,2.73,1.13,0,0.57,30.6,56.82,0,0,0,0,5.41,2.75
    M_Krzewińska_et_al._2018_(Vikings):urm035,5.96,1.19,0.38,0,31.32,53.92,2.69,0.03,0,0,2.91,1.59
    M_Krzewińska_et_al._2018_(Vikings):urm045,3.21,0,0.51,0,24.75,57.23,0,2.18,0,0.05,12.06,0
    M_Krzewińska_et_al._2018_(Vikings):urm160,5.95,1.97,0.49,0.85,28.25,55.52,0,0.46,0,0,4.58,1.92
    M_Krzewińska_et_al._2018_(Vikings):urm161,8.81,0,0,0,41.48,43.45,3.12,0,0,0,0,3.14
    C_Valdiosera_et_al._2018:atp002,0,0.03,5.12,0.55,62.93,13.54,0,0.48,4.78,1.62,6.7,4.26
    C_Valdiosera_et_al._2018:atp005,0,2.01,1.09,0,60.84,0.31,0,0,11.22,0,20.99,3.54
    C_Valdiosera_et_al._2018:atp12-1420,0,0,5.74,0.83,68.17,15.8,0.24,0,5.32,0.38,2.75,0.76
    C_Valdiosera_et_al._2018:atp016,0,0,5.35,0.42,68.81,5.51,0,0.33,7.06,0,12.38,0.13
    C_Valdiosera_et_al._2018:atp019,0,1.8,4.25,0,57.46,0.34,0,0,5.16,0.73,26.62,3.63
    C_Valdiosera_et_al._2018:atp019,0,0,7.52,0.71,62.29,1.56,0,0,7.84,0,19.26,0.81
    C_Valdiosera_et_al._2018:c40331,0,0,3.16,1.06,67.38,11.19,0,0,4.72,0,11.94,0.56
    C_Valdiosera_et_al._2018:esp005,3.66,0.8,3.69,1.65,53.52,26.43,0,0,2.04,0.18,5.89,2.13
    C_Valdiosera_et_al._2018:mur,0,0,5.67,0,66.23,2.59,0,0.46,8.21,1.52,14.45,0.87
    C_Valdiosera_et_al._2018:pir001,0,0.66,1.98,0.37,55.66,23.52,3.77,0,8.17,0,3.33,2.54
    C_Valdiosera_et_al._2018:por002,0,0,5.37,0.02,64.98,15.06,0,0,6.18,0.7,6.47,1.23
    C_Valdiosera_et_al._2018:por003,0,0,3.03,0,63.76,26.93,0,0,0.23,0,0,6.05
    C_Valdiosera_et_al._2018:por003,3.94,0,5.6,0,52.18,18.95,0.66,2.75,6.57,0,8.92,0.42
    C_Valdiosera_et_al._2018:por004,0,0.67,1.47,0.21,63.5,15.9,0,0.26,9.07,0,8.05,0.87
    C_Valdiosera_et_al._2018:san216,0,0,1.47,1.06,68.69,11.03,0,0.37,7.4,0,7.71,2.27
    T_Günther_et_al._‎2018:H22,0,7.17,0,0,7.56,82.86,0,0,0,0,0,2.41
    T_Günther_et_al._‎2018:H26,0,5.15,0,0,11.42,80.94,0.61,0,0,0.2,0,1.68
    T_Günther_et_al._‎2018:sbj001,0,3.12,0,0,11.18,84.49,0,0.19,0,0,0,1.03
    T_Günther_et_al._‎2018:sf11,0,3.86,0,0,22.4,68.89,2.74,0,0,0,0,2.11
    T_Günther_et_al._‎2018:stg001,0,4.84,0,0,11.19,83.35,0,0,0,0,0,0.62
    AG_Nikitin_et_al:I6912_all,6.42,0,7.58,0,46.18,36.28,0,0,0.2,0,3.33,0
    AG_Nikitin_et_al:I6913,0,0,0,0,58.75,41.25,0,0,0,0,0,0
    AG_Nikitin_et_al:I6914,0,0,4.67,0.17,50.82,0,0,0.03,14.5,0,29.81,0
    R_Rodríguez-Varela_et_al._2018:gun002,0,1.31,31.56,0,24.78,1.36,2.41,8.3,15.17,0,8.59,6.52
    R_Rodríguez-Varela_et_al._2018:gun005,0,0,23.21,1.53,28.6,4.15,1.69,7.18,17.37,0,11.07,5.21
    R_Rodríguez-Varela_et_al._2018:gun008,0,1.97,26.93,0,30.43,2.24,0,10.25,14.64,0,9.75,3.78
    R_Rodríguez-Varela_et_al._2018:gun011,0,0,34.12,1.26,20.39,1.62,1.13,8.15,16.3,0,10.26,6.77
    R_Rodríguez-Varela_et_al._2018:gun012,0,0,35.63,0,21.14,1.91,0.21,10.49,12.35,1.01,11.28,5.98
    Z_Hofmanová_et_al._2016:Bar8,0,0,4.96,0,45.12,0,0,0,13.39,0.45,33.88,2.2
    Z_Hofmanová_et_al._2016:Bar31,0,0,4.68,0.92,45.75,0,0,0,14.24,0,31.86,2.55
    Z_Hofmanová_et_al._2016:Klei10,0,0,2.1,0.17,46.06,0,0,0,14.18,0,35.73,1.76
    Z_Hofmanová_et_al._2016:Pal7,0,0,4.41,0.01,47.42,0,0,0,13.07,0.67,32.97,1.44
    Z_Hofmanová_et_al._2016:Rev5,0,0,4.74,0,48.42,0,0,0,12.15,0.13,33.21,1.35
    Fu_etal._2015:Oase1,9.78,0.91,0.43,14.51,2.67,12.1,29.17,11.2,1.93,7.17,1.73,8.39
    Thanks Jovialis. Great work.

    Distance to: Duarte
    12.51164258 M_Krzewińska_et_al._2018_(Vikings):bns023-b1e1l1
    12.94545480 C_Valdiosera_et_al._2018_por003
    14.56458719 C_Valdiosera_et_al._2018:esp005
    18.03420084 AG_Nikitin_et_al:I6912_all
    19.14299088 C_Valdiosera_et_al._2018-pir001
    20.44078521 H_Malmström_et_al._2019:ros005
    22.80863871 M_Krzewińska_et_al._2018_(Vikings):gtm127-b1e1l1p1
    24.51884989 C_Valdiosera_et_al._2018:atp002
    25.15568524 C_Valdiosera_et_al._2018-por004
    25.21904836 H_Malmström_et_al._2019:ros3
    25.64877190 M_Krzewińska_et_al._2018_(Vikings):urm161
    26.01182039 M_Krzewińska_et_al._2018_(Vikings):nuf002-b1e1l1p1
    26.03405462 H_Malmström_et_al._2019_oll007
    26.10459730 M_Krzewińska_et_al._2018_(Vikings):grt035
    26.12311046 M_Krzewińska_et_al._2018_(Vikings):97002
    26.16635244 C_Valdiosera_et_al._2018-por002
    26.62157584 C_Valdiosera_et_al._2018_por003
    27.53782308 M_Krzewińska_et_al._2018_(Vikings):97026
    27.69584445 M_Krzewińska_et_al._2018_(Vikings):84035
    27.82489533 M_Krzewińska_et_al._2018_(Vikings):kls001-b1e1l1
    28.51821698 M_Krzewińska_et_al._2018_(Vikings):stg021
    29.00167581 C_Valdiosera_et_al._2018:c40331
    29.68399737 AG_Nikitin_et_al:I6913
    29.81141728 C_Valdiosera_et_al._2018:atp12-1420
    30.85896466 C_Valdiosera_et_al._2018:san216
    Distance: 1.2657% / 1.26572987
    Target: Duarte
    31.0 C_Valdiosera_et_al._2018:atp019
    23.1 C_Valdiosera_et_al._2018-por003
    15.9 M_Krzewińska_et_al._2018_(Vikings):2072
    8.6 R_Rodríguez-Varela_et_al._2018:gun012
    7.1 Broushaki_et_al._2016:AH2
    6.4 M_Krzewińska_et_al._2018_(Vikings):gtm021-b1e1l1p1
    4.3 M_Krzewińska_et_al._2018_(Vikings):urm045
    3.6 Z_Hofmanová_et_al._2016:Klei10



  8. #308
    Regular Member Carlos's Avatar
    Join Date
    26-09-11
    Posts
    2,605


    Country: Spain



    1 members found this post helpful.
    Distance: 0.5733% / 0.57330876
    Target: Carlos
    47.0 AG_Nikitin_et_al

    29.0 C_Valdiosera_et_al._2018

    20.8 M_Krzewińska_et_al._2018_(Vikings)

    2.8 Broushaki_et_al._2016
    0.4 R_Rodríguez-Varela_et_al._2018


    Code:
     
    Distance to: Carlos
    11.93520842 M_Krzewińska_et_al._2018_(Vikings):bns023-b1e1l1
    12.00195817 C_Valdiosera_et_al._2018:esp005
    12.25876013 C_Valdiosera_et_al._2018:por003
    14.77451860 AG_Nikitin_et_al:I6912_all
    17.52231434 C_Valdiosera_et_al._2018:pir001
    18.60408289 H_Malmström_et_al._2019:ros005
    19.44671180 M_Krzewińska_et_al._2018_(Vikings):gtm127-b1e1l1p1
    23.14453715 M_Krzewińska_et_al._2018_(Vikings):grt035
    23.39565558 M_Krzewińska_et_al._2018_(Vikings):urm161
    23.75584770 C_Valdiosera_et_al._2018:por004
    24.08419399 H_Malmström_et_al._2019:oll007
    24.23133921 C_Valdiosera_et_al._2018:atp002
    24.30774979 M_Krzewińska_et_al._2018_(Vikings):97002
    24.34070665 M_Krzewińska_et_al._2018_(Vikings):nuf002-b1e1l1p1
    24.64065746 H_Malmström_et_al._2019:ros3
    24.68898742 C_Valdiosera_et_al._2018:por003
    24.95575284 C_Valdiosera_et_al._2018:por002
    25.18321068 M_Krzewińska_et_al._2018_(Vikings):97026
    25.56117368 M_Krzewińska_et_al._2018_(Vikings):84035
    25.57667101 AG_Nikitin_et_al:I6913
    25.92400818 M_Krzewińska_et_al._2018_(Vikings):kls001-b1e1l1
    26.53891671 M_Krzewińska_et_al._2018_(Vikings):stg021
    27.92243542 C_Valdiosera_et_al._2018:c40331
    28.20669601 H_Malmström_et_al._2019:oll009
    28.40673512 C_Valdiosera_et_al._2018:atp12-1420
    28.63582197 M_Krzewińska_et_al._2018_(Vikings):97029
    29.23711682 M_Krzewińska_et_al._2018_(Vikings):84001
    29.46974041 H_Malmström_et_al._2019:oll010
    30.02625351 M_Krzewińska_et_al._2018_(Vikings):grt036
    30.06468526 C_Valdiosera_et_al._2018:san216
    31.87566470 C_Valdiosera_et_al._2018:atp019
    32.54940245 C_Valdiosera_et_al._2018:atp016
    32.55123346 C_Valdiosera_et_al._2018:atp019
    32.56987565 M_Krzewińska_et_al._2018_(Vikings):gtm021-b1e1l1p1
    32.95237624 C_Valdiosera_et_al._2018:mur
    32.95280868 M_Krzewińska_et_al._2018_(Vikings):urm035
    33.42753207 C_Valdiosera_et_al._2018:atp005
    34.07439655 AG_Nikitin_et_al:I6914
    34.23320902 H_Malmström_et_al._2019:ber2F
    34.58160060 Z_Hofmanová_et_al._2016:Bar31
    34.83264130 Z_Hofmanová_et_al._2016:Rev5
    34.87085316 Z_Hofmanová_et_al._2016:Pal7
    35.07657053 M_Krzewińska_et_al._2018_(Vikings):urm160
    35.08963950 M_Krzewińska_et_al._2018_(Vikings):stg026
    35.40174713 Z_Hofmanová_et_al._2016:Bar8
    36.85167703 Z_Hofmanová_et_al._2016:Klei10
    37.20194887 M_Krzewińska_et_al._2018_(Vikings):urm045
    37.31044894 R_Rodríguez-Varela_et_al._2018:gun005
    38.84485423 M_Krzewińska_et_al._2018_(Vikings):84005
    39.31218386 R_Rodríguez-Varela_et_al._2018:gun008
    43.54323598 M_Krzewińska_et_al._2018_(Vikings):stg020
    44.66437954 H_Malmström_et_al._2019:ajv54
    45.00664729 R_Rodríguez-Varela_et_al._2018:gun002
    47.76471292 H_Malmström_et_al._2019:poz44
    48.35291822 R_Rodríguez-Varela_et_al._2018:gun012
    48.60912980 R_Rodríguez-Varela_et_al._2018:gun011
    49.62054312 M_Krzewińska_et_al._2018_(Vikings):2072
    50.57897884 T_Günther_et_al._‎2018:sf11
    51.09880331 M_Krzewińska_et_al._2018_(Vikings):KAL006
    55.68000090 H_Malmström_et_al._2019:poz81
    55.69369713 Broushaki_et_al._2016:F38
    56.35121028 M_Krzewińska_et_al._2018_(Vikings):kal009
    58.72826747 Fu_etal._2015:Oase1
    65.86880673 T_Günther_et_al._‎2018:H26
    67.95502998 T_Günther_et_al._‎2018:stg001
    68.83537898 T_Günther_et_al._‎2018:sbj001
    69.62579335 T_Günther_et_al._‎2018:H22
    75.44942081 Broushaki_et_al._2016:WC1
    79.25261636 Broushaki_et_al._2016:AH4
    79.35222429 Broushaki_et_al._2016:AH2
    81.20734203 Broushaki_et_al._2016:AH1

  9. #309
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    Hmmm, it seems that certain samples, or putting too many samples into the 3D PCA breaks it. The algorithm goes out of whack, and the samples are projected wrong. I noticed this happens if you put in the Broushaki samples. I also noticed it happened when putting in the Balkan samples with the new additions, along with the rest. Perhaps it has to do with the high number of HGs, but it didn't happen previously. It is a shame because I would have liked to see all of the samples together.

  10. #310
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    1 members found this post helpful.
    Quote Originally Posted by Jovialis View Post
    Hmmm, it seems that certain samples, or putting too many samples into the 3D PCA breaks it. The algorithm goes out of whack, and the samples are projected wrong. I noticed this happens if you put in the Broushaki samples. I also noticed it happened when putting in the Balkan samples with the new additions, along with the rest. Perhaps it has to do with the high number of HGs, but it didn't happen previously. It is a shame because I would have liked to see all of the samples together.
    This is why I would love to run these samples through a calculator that is made for analyzing ancient DNA specifically, rather than one made with modern DNA source components.

  11. #311
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    1 members found this post helpful.
    Luckily this issue doesn't seem to be happening with Dodecad Globe 13. So far, so good.

  12. #312
    Advisor Jovialis's Avatar
    Join Date
    04-05-17
    Location
    New York City
    Posts
    4,560

    Y-DNA haplogroup
    R1b1a1a2b1 (R-F1794)
    MtDNA haplogroup
    H6a1b

    Ethnic group
    Italian
    Country: United States



    1 members found this post helpful.
    Quote Originally Posted by Jovialis View Post
    Luckily this issue doesn't seem to be happening with Dodecad Globe 13. So far, so good.
    Here is a preview of the 3D PCA for globe 13, projected over modern populations. All of the new samples are included, and the PCA remains accurate. This brings the total up from 1,315, to 1,859. More to come:


Page 13 of 13 FirstFirst ... 3111213

Tags for this Thread

Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts
  •