K12b Dodecad K12b Ancient West Eurasia [by Eupedia Team]

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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 sequencinghttps://www.ebi.ac.uk/ena/browser/view/PRJEB28301*Unclear sample arrangement
Upper Palaeolithic genomes reveal deep roots of modern Eurasianshttps://www.ebi.ac.uk/ena/browser/view/PRJEB113643BAMs do not work with WGSextract
The Neolithic Transition in the Baltic Was Not Driven by Admixture with Early European Farmershttps://www.ebi.ac.uk/ena/browser/view/PRJEB180679BAMs do not work with WGSextract
The genetic history of admixture across inner Eurasiahttps://www.ebi.ac.uk/ena/browser/view/PRJEB311526BAMs do not work with WGSextract
Paleogenomic Evidence for Multi-generational Mixing between Neolithic Farmers and Mesolithic Hunter-Gatherers in the Lower Danube Basinhttps://www.ebi.ac.uk/ena/browser/view/PRJEB206166BAMs do not work with WGSextract
Extensive farming in Estonia started through a sex-biased migration from the Steppehttps://www.ebi.ac.uk/ena/browser/view/PRJEB210379BAMs do not work with WGSextract
Genomic signals of migration and continuity in Britain before the Anglo-Saxonshttps://www.ebi.ac.uk/ena/browser/view/PRJEB1100414BAMs do not work with WGSextract
The population genomics of archaeological transition in west Iberia: Investigation of ancient substructure using imputation and haplotype-based methodshttps://www.ebi.ac.uk/ena/browser/view/PRJEB1473714BAMs 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/PRJEB2918921BAMs do not work with WGSextract
The first horse herders and the impact of early Bronze Age steppe expansions into Asiahttps://www.ebi.ac.uk/ena/browser/view/PRJEB26349111BAMs do not work with WGSextract
Understanding 6th-century barbarian social organization and migration through paleogenomicshttps://www.ebi.ac.uk/ena/browser/view/PRJEB2722053No FTP BAMs
Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genomehttps://www.ebi.ac.uk/ena/browser/view/PRJEB1199528No FTP BAMs
A genomic Neolithic time transect of hunter-farmer admixture in central Polandhttps://www.ebi.ac.uk/ena/browser/view/PRJNA31823717No FTP BAMs
Ancient genomes from North Africa evidence prehistoric migrations to the Maghreb from both the Levant and Europehttps://www.ebi.ac.uk/ena/browser/view/PRJEB2269923No FTP BAMs
Continuity and Admixture in the Last Five Millennia of Levantine History from Ancient Canaanite and Present-Day Lebanese Genome Sequenceshttps://www.ebi.ac.uk/ena/browser/view/PRJEB21330100No FTP BAMs
A Transient Pulse of Genetic Admixture from the Crusaders in the Near East Identified from Ancient Genome Sequenceshttps://www.ebi.ac.uk/ena/browser/view/PRJEB31618116No FTP BAMs
The genetic prehistory of the Baltic Sea regionhttps://www.ebi.ac.uk/ena/browser/view/PRJNA42133380No FTP BAMs
Ancient Genomes Reveal Yamnaya-Related Ancestry and a Potential Source of Indo-European Speakers in Iron Age Tianshanhttps://www.ebi.ac.uk/ena/browser/view/PRJEB3233610No FTP BAMs
A Common Genetic Origin for Early Farmers from Mediterranean Cardial and Central European LBK Cultureshttps://www.ebi.ac.uk/ena/browser/view/PRJNA28081212No FTP BAMs
Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic Europeanhttps://www.ebi.ac.uk/ena/browser/view/PRJNA2306891No 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 92No 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/PRJEB691518No FTP BAMs
Genomic diversity and admixture differs for Stone-Age Scandinavian foragers and farmershttps://www.ebi.ac.uk/ena/browser/view/PRJEB609035No FTP BAMs
Paleogenomics. Genomic structure in Europeans dating back at least 36,200 yearshttps://www.ebi.ac.uk/ena/browser/view/PRJEB76181BAMs do not work with WGSextract
Unraveling ancestry, kinship, and violence in a Late Neolithic mass gravehttps://www.ebi.ac.uk/ena/browser/view/PRJEB2845124BAMs do not work with WGSextract
Ancient Egyptian mummy genomes suggest an increase of Sub-Saharan African ancestry in post-Roman periodshttps://www.ebi.ac.uk/ena/browser/view/PRJEB1546493Raw 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 Ibizaaccession numbers: MH43585-43559?Author to upload bams
 
Here are non-Homo Sapien studies, but I will not include them in the project.

A high-coverage genome sequence from an archaic Denisovan individualhttps://www.ebi.ac.uk/ena/browser/view/PRJEB3092
A high-coverage Neandertal genome from Vindija Cave in Croatiahttps://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 Mountainshttps://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 fatherhttps://www.ebi.ac.uk/ena/browser/view/PRJEB24663
Reconstructing the genetic history of late NeanderthalsPRJEB21870; PRJEB21875; PRJEB21881; PRJEB21882: PRJEB21883
 
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)
 
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 sequencinghttps://www.ebi.ac.uk/ena/browser/view/PRJEB28301*Unclear sample arrangement
Upper Palaeolithic genomes reveal deep roots of modern Eurasianshttps://www.ebi.ac.uk/ena/browser/view/PRJEB113643BAMs do not work with WGSextract
The Neolithic Transition in the Baltic Was Not Driven by Admixture with Early European Farmershttps://www.ebi.ac.uk/ena/browser/view/PRJEB180679BAMs do not work with WGSextract
The genetic history of admixture across inner Eurasiahttps://www.ebi.ac.uk/ena/browser/view/PRJEB311526BAMs do not work with WGSextract
Paleogenomic Evidence for Multi-generational Mixing between Neolithic Farmers and Mesolithic Hunter-Gatherers in the Lower Danube Basinhttps://www.ebi.ac.uk/ena/browser/view/PRJEB206166BAMs do not work with WGSextract
Extensive farming in Estonia started through a sex-biased migration from the Steppehttps://www.ebi.ac.uk/ena/browser/view/PRJEB210379BAMs do not work with WGSextract
Genomic signals of migration and continuity in Britain before the Anglo-Saxonshttps://www.ebi.ac.uk/ena/browser/view/PRJEB1100414BAMs do not work with WGSextract
The population genomics of archaeological transition in west Iberia: Investigation of ancient substructure using imputation and haplotype-based methodshttps://www.ebi.ac.uk/ena/browser/view/PRJEB1473714BAMs do not work with WGSextract
A western route of prehistoric human migration from Africa into the Iberian Peninsulahttps://www.ebi.ac.uk/ena/browser/view/PRJEB2918921BAMs do not work with WGSextract
The first horse herders and the impact of early Bronze Age steppe expansions into Asiahttps://www.ebi.ac.uk/ena/browser/view/PRJEB26349111BAMs do not work with WGSextract
Understanding 6th-century barbarian social organization and migration through paleogenomicshttps://www.ebi.ac.uk/ena/browser/view/PRJEB2722053No FTP BAMs
Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genomehttps://www.ebi.ac.uk/ena/browser/view/PRJEB1199528No FTP BAMs
A genomic Neolithic time transect of hunter-farmer admixture in central Polandhttps://www.ebi.ac.uk/ena/browser/view/PRJNA31823717No FTP BAMs
Ancient genomes from North Africa evidence prehistoric migrations to the Maghreb from both the Levant and Europehttps://www.ebi.ac.uk/ena/browser/view/PRJEB2269923No FTP BAMs
Continuity and Admixture in the Last Five Millennia of Levantine History from Ancient Canaanite and Present-Day Lebanese Genome Sequenceshttps://www.ebi.ac.uk/ena/browser/view/PRJEB21330100No FTP BAMs
A Transient Pulse of Genetic Admixture from the Crusaders in the Near East Identified from Ancient Genome Sequenceshttps://www.ebi.ac.uk/ena/browser/view/PRJEB31618116No FTP BAMs
The genetic prehistory of the Baltic Sea regionhttps://www.ebi.ac.uk/ena/browser/view/PRJNA42133380No FTP BAMs
Ancient Genomes Reveal Yamnaya-Related Ancestry and a Potential Source of Indo-European Speakers in Iron Age Tianshanhttps://www.ebi.ac.uk/ena/browser/view/PRJEB3233610No FTP BAMs
A Common Genetic Origin for Early Farmers from Mediterranean Cardial and Central European LBK Cultureshttps://www.ebi.ac.uk/ena/browser/view/PRJNA28081212No FTP BAMs
Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic Europeanhttps://www.ebi.ac.uk/ena/browser/view/PRJNA2306891No 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 92No 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/PRJEB691518No FTP BAMs
Genomic diversity and admixture differs for Stone-Age Scandinavian foragers and farmershttps://www.ebi.ac.uk/ena/browser/view/PRJEB609035No FTP BAMs
Paleogenomics. Genomic structure in Europeans dating back at least 36,200 yearshttps://www.ebi.ac.uk/ena/browser/view/PRJEB76181BAMs do not work with WGSextract
Unraveling ancestry, kinship, and violence in a Late Neolithic mass gravehttps://www.ebi.ac.uk/ena/browser/view/PRJEB2845124BAMs do not work with WGSextract
Ancient Egyptian mummy genomes suggest an increase of Sub-Saharan African ancestry in post-Roman periodshttps://www.ebi.ac.uk/ena/browser/view/PRJEB1546493Raw 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 Ibizaaccession 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.
 
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
 
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
12.51164258M_Krzewińska_et_al._2018_(Vikings):bns023-b1e1l1
12.94545480C_Valdiosera_et_al._2018_por003
14.56458719C_Valdiosera_et_al._2018:esp005
18.03420084AG_Nikitin_et_al:I6912_all
19.14299088C_Valdiosera_et_al._2018-pir001
20.44078521H_Malmström_et_al._2019:ros005
22.80863871M_Krzewińska_et_al._2018_(Vikings):gtm127-b1e1l1p1
24.51884989C_Valdiosera_et_al._2018:atp002
25.15568524C_Valdiosera_et_al._2018-por004
25.21904836H_Malmström_et_al._2019:ros3
25.64877190M_Krzewińska_et_al._2018_(Vikings):urm161
26.01182039M_Krzewińska_et_al._2018_(Vikings):nuf002-b1e1l1p1
26.03405462H_Malmström_et_al._2019_oll007
26.10459730M_Krzewińska_et_al._2018_(Vikings):grt035
26.12311046M_Krzewińska_et_al._2018_(Vikings):97002
26.16635244C_Valdiosera_et_al._2018-por002
26.62157584C_Valdiosera_et_al._2018_por003
27.53782308M_Krzewińska_et_al._2018_(Vikings):97026
27.69584445M_Krzewińska_et_al._2018_(Vikings):84035
27.82489533M_Krzewińska_et_al._2018_(Vikings):kls001-b1e1l1
28.51821698M_Krzewińska_et_al._2018_(Vikings):stg021
29.00167581C_Valdiosera_et_al._2018:c40331
29.68399737AG_Nikitin_et_al:I6913
29.81141728C_Valdiosera_et_al._2018:atp12-1420
30.85896466C_Valdiosera_et_al._2018:san216
Distance: 1.2657% / 1.26572987
Target: Duarte
31.0C_Valdiosera_et_al._2018:atp019
23.1C_Valdiosera_et_al._2018-por003
15.9M_Krzewińska_et_al._2018_(Vikings):2072
8.6R_Rodríguez-Varela_et_al._2018:gun012
7.1Broushaki_et_al._2016:AH2
6.4M_Krzewińska_et_al._2018_(Vikings):gtm021-b1e1l1p1
4.3M_Krzewińska_et_al._2018_(Vikings):urm045
3.6Z_Hofmanová_et_al._2016:Klei10


 
Distance: 0.5733% / 0.57330876
Target: Carlos
47.0AG_Nikitin_et_al

29.0C_Valdiosera_et_al._2018

20.8M_Krzewińska_et_al._2018_(Vikings)

2.8Broushaki_et_al._2016
0.4R_Rodríguez-Varela_et_al._2018


Code:
 [TABLE="class: distances"]
[TR]
[TH="align: right"]Distance to:[/TH]
[TH="align: left"]Carlos[/TH]
[/TR]
[TR]
[TD="bgcolor: #FF1700, align: right"]11.93520842[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):bns023-b1e1l1[/TD]
[/TR]
[TR]
[TD="bgcolor: #FF1400, align: right"]12.00195817[/TD]
[TD]C_Valdiosera_et_al._2018:esp005[/TD]
[/TR]
[TR]
[TD="bgcolor: #FF0A00, align: right"]12.25876013[/TD]
[TD]C_Valdiosera_et_al._2018:por003[/TD]
[/TR]
[TR]
[TD="bgcolor: #FF005D, align: right"]14.77451860[/TD]
[TD]AG_Nikitin_et_al:I6912_all[/TD]
[/TR]
[TR]
[TD="bgcolor: #FF00CD, align: right"]17.52231434[/TD]
[TD]C_Valdiosera_et_al._2018:pir001[/TD]
[/TR]
[TR]
[TD="bgcolor: #FF00F9, align: right"]18.60408289[/TD]
[TD]H_Malmström_et_al._2019:ros005[/TD]
[/TR]
[TR]
[TD="bgcolor: #E300FF, align: right"]19.44671180[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):gtm127-b1e1l1p1[/TD]
[/TR]
[TR]
[TD="bgcolor: #4C00FF, align: right"]23.14453715[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):grt035[/TD]
[/TR]
[TR]
[TD="bgcolor: #4100FF, align: right"]23.39565558[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):urm161[/TD]
[/TR]
[TR]
[TD="bgcolor: #3300FF, align: right"]23.75584770[/TD]
[TD]C_Valdiosera_et_al._2018:por004[/TD]
[/TR]
[TR]
[TD="bgcolor: #2500FF, align: right"]24.08419399[/TD]
[TD]H_Malmström_et_al._2019:oll007[/TD]
[/TR]
[TR]
[TD="bgcolor: #1F00FF, align: right"]24.23133921[/TD]
[TD]C_Valdiosera_et_al._2018:atp002[/TD]
[/TR]
[TR]
[TD="bgcolor: #1C00FF, align: right"]24.30774979[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):97002[/TD]
[/TR]
[TR]
[TD="bgcolor: #1B00FF, align: right"]24.34070665[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):nuf002-b1e1l1p1[/TD]
[/TR]
[TR]
[TD="bgcolor: #0F00FF, align: right"]24.64065746[/TD]
[TD]H_Malmström_et_al._2019:ros3[/TD]
[/TR]
[TR]
[TD="bgcolor: #0D00FF, align: right"]24.68898742[/TD]
[TD]C_Valdiosera_et_al._2018:por003[/TD]
[/TR]
[TR]
[TD="bgcolor: #0200FF, align: right"]24.95575284[/TD]
[TD]C_Valdiosera_et_al._2018:por002[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]25.18321068[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):97026[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]25.56117368[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):84035[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]25.57667101[/TD]
[TD]AG_Nikitin_et_al:I6913[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]25.92400818[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):kls001-b1e1l1[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]26.53891671[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):stg021[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]27.92243542[/TD]
[TD]C_Valdiosera_et_al._2018:c40331[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]28.20669601[/TD]
[TD]H_Malmström_et_al._2019:oll009[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]28.40673512[/TD]
[TD]C_Valdiosera_et_al._2018:atp12-1420[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]28.63582197[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):97029[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]29.23711682[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):84001[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]29.46974041[/TD]
[TD]H_Malmström_et_al._2019:oll010[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]30.02625351[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):grt036[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]30.06468526[/TD]
[TD]C_Valdiosera_et_al._2018:san216[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]31.87566470[/TD]
[TD]C_Valdiosera_et_al._2018:atp019[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]32.54940245[/TD]
[TD]C_Valdiosera_et_al._2018:atp016[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]32.55123346[/TD]
[TD]C_Valdiosera_et_al._2018:atp019[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]32.56987565[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):gtm021-b1e1l1p1[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]32.95237624[/TD]
[TD]C_Valdiosera_et_al._2018:mur[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]32.95280868[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):urm035[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]33.42753207[/TD]
[TD]C_Valdiosera_et_al._2018:atp005[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]34.07439655[/TD]
[TD]AG_Nikitin_et_al:I6914[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]34.23320902[/TD]
[TD]H_Malmström_et_al._2019:ber2F[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]34.58160060[/TD]
[TD]Z_Hofmanová_et_al._2016:Bar31[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]34.83264130[/TD]
[TD]Z_Hofmanová_et_al._2016:Rev5[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]34.87085316[/TD]
[TD]Z_Hofmanová_et_al._2016:Pal7[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]35.07657053[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):urm160[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]35.08963950[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):stg026[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]35.40174713[/TD]
[TD]Z_Hofmanová_et_al._2016:Bar8[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]36.85167703[/TD]
[TD]Z_Hofmanová_et_al._2016:Klei10[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]37.20194887[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):urm045[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]37.31044894[/TD]
[TD]R_Rodríguez-Varela_et_al._2018:gun005[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]38.84485423[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):84005[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]39.31218386[/TD]
[TD]R_Rodríguez-Varela_et_al._2018:gun008[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]43.54323598[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):stg020[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]44.66437954[/TD]
[TD]H_Malmström_et_al._2019:ajv54[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]45.00664729[/TD]
[TD]R_Rodríguez-Varela_et_al._2018:gun002[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]47.76471292[/TD]
[TD]H_Malmström_et_al._2019:poz44[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]48.35291822[/TD]
[TD]R_Rodríguez-Varela_et_al._2018:gun012[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]48.60912980[/TD]
[TD]R_Rodríguez-Varela_et_al._2018:gun011[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]49.62054312[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):2072[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]50.57897884[/TD]
[TD]T_Günther_et_al._‎2018:sf11[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]51.09880331[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):KAL006[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]55.68000090[/TD]
[TD]H_Malmström_et_al._2019:poz81[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]55.69369713[/TD]
[TD]Broushaki_et_al._2016:F38[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]56.35121028[/TD]
[TD]M_Krzewińska_et_al._2018_(Vikings):kal009[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]58.72826747[/TD]
[TD]Fu_etal._2015:Oase1[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]65.86880673[/TD]
[TD]T_Günther_et_al._‎2018:H26[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]67.95502998[/TD]
[TD]T_Günther_et_al._‎2018:stg001[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]68.83537898[/TD]
[TD]T_Günther_et_al._‎2018:sbj001[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]69.62579335[/TD]
[TD]T_Günther_et_al._‎2018:H22[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]75.44942081[/TD]
[TD]Broushaki_et_al._2016:WC1[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]79.25261636[/TD]
[TD]Broushaki_et_al._2016:AH4[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]79.35222429[/TD]
[TD]Broushaki_et_al._2016:AH2[/TD]
[/TR]
[TR]
[TD="bgcolor: #0000FF, align: right"]81.20734203[/TD]
[TD]Broushaki_et_al._2016:AH1

[/TD]
[/TR]
[/TABLE]
 
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.
 
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.
 
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:

31qMbhf.png
 
Vahaduo Dodecad K12b Ancient added of the coordinates produced by Jovialis and Salento at

https://www.ebi.ac.uk/ena/browser/view/PRJEB37660
... just a test, ... 1 by 4 locations:
I'm not sure my apps arefully compatible with these .bam(s), … that's all the samples I'm gonna post :)

dod k12
Code:
[COLOR=#222222][FONT=Verdana]BRC003_Dodecad_K12b,1.48,0.00,2.35,1.33,46.70,24.27,0.00,0.00,5.74,0.00,17.40,0.74[/FONT][/COLOR]
Code:
[B][COLOR=#000000][COLOR=#313131][FONT=-apple-system]
[/FONT][/COLOR][/COLOR][/B][COLOR=#000000][COLOR=#313131][FONT=-apple-system][COLOR=#222222][FONT=Verdana]GCP002A1_Dodecad_K12b,2.18,0.00,3.15,3.26,44.50,29.77,0.00,0.00,5.27,0.00,11.87,0.00[/FONT][/COLOR]
[COLOR=#222222][FONT=Verdana]GLR001A1_Dodecad_K12b,0.00,1.77,4.40,0.00,58.27,5.15,0.00,0.00,11.05,0.22,17.72,1.41[/FONT][/COLOR]
[COLOR=#222222][FONT=Verdana]LSC002_004_Dodecad_K12b,0.00,0.00,0.00,0.00,62.94,2.45,0.00,0.00,6.28,0.00,26.23,2.11[/FONT][/COLOR][/FONT][/COLOR][/COLOR][B][COLOR=#000000][COLOR=#313131][FONT=-apple-system]
[/FONT][/COLOR][/COLOR][/B]

dod k13
Code:
[COLOR=#222222][FONT=Verdana]BRC003_Dod_Globe13,0.00,0.00,1.53,0.00,7.15,2.00,46.64,0.00,0.00,6.54,36.15,0.00,0.00[/FONT][/COLOR]
[COLOR=#222222][FONT=Verdana]GCP002A1_Dod_Globe13,0.00,0.06,0.56,0.00,7.87,2.46,41.92,0.00,0.36,7.63,39.13,0.00,0.00[/FONT][/COLOR]
[COLOR=#222222][FONT=Verdana]GLR001A1_Dod_Globe13,0.00,0.00,2.04,0.00,13.48,0.00,59.66,0.13,0.96,4.05,19.69,0.00,0.00[/FONT][/COLOR]
[COLOR=#222222][FONT=Verdana]LSC002_004_Dod_Globe13,0.00,0.00,1.53,0.15,14.88,0.00,62.80,0.28,0.00,2.48,17.88,0.00,0.00[/FONT][/COLOR]


Special thanks to Salento for putting this on my radar:
Of the 35 samples, these are the ones that processed through Admixture Studio.
Code:
utigBRC002,0.87,0,1.36,0,45.47,25.27,2.32,0,4.39,0,18.99,1.33
utigBRC007_019,3.5,0,1.75,0.58,48.28,18.96,0,0,9.11,0.52,16.2,1.1
utigBRC010_018,0,0,5.13,0.5,47.79,19.51,0,0,7.86,0,18.69,0.51
utigBRC011,0,0,0,0,37.8,0,0,0,42.9,0,19.29,0
utigBRC012,0,15.45,0,0,40.8,0,0,0,43.74,0,0,0
utigBRC013,0,0,6.28,0,57.75,0,0,0,6.97,0,29,0
utigBRC022,0,0,0,0.94,62.87,3.14,0,0,10.14,0,22.91,0
utigBRC024,0,0,0,0,52.32,30.37,0,5.35,0,0,10.84,1.12
utigGCP002A1,2.18,0,3.15,3.26,44.5,29.77,0,0,5.27,0,11.87,0
utigGCP003A1,7.58,1.55,0.86,0,49.29,22.95,0,0,4.32,0,13.45,0
utigGCP004A1,22.15,0,0,0,37.5,23.7,6.64,0,10.01,0,0,0
utigGLR002A1,0,0,6.65,0,63.81,1.89,0,0,5.79,0,21.86,0
utigGLR003B1,0,0,9.49,4.97,65.66,0,0,0,0,0,17.94,1.93
utigLSC002_004,0,0,0,0,62.94,2.45,0,0,6.28,0,26.23,2.11
utigLSC007A1,0,0,0,0,95.95,0,0,0.6,3.45,0,0,0
utigLSC011A1,0,0,8.94,0,53.32,7.47,0,0,14.31,0,15.96,0
utigLSC012A1,0,0,0,0,97.48,0,0,0,0,2.52,0,0


Distance to:
Duarte
6.29654667GironaSantJuliadeRamis_I10892
6.83142738GironaSantJuliadeRamis_I10895
7.15328596EarlyMedievalAndalusia_I3585
7.40270896I12516_SE_Iberia_c.10-16CE
7.51741312I12514_SE_Iberia_c.10-16CE
7.79453013R63_Medieval_Era_Villa_Magna
7.87062895Roman-SoldierFN_2
7.96743999EarlyMedievalIberiaGranada_I3981
7.98827891GironaSantJuliadeRamis_I10852
8.29628230MedievalTaifaofValencia_I12649
8.57093927CrusaderKnightFrenchLebanonCrusaderSI40
8.65500433I3982_SE_Iberia_c.3-4CE
8.79383307I7675_NE_Iberia_c.6-8CE_ES
8.85043502GironaSantJuliadeRamis_I10853
8.99556557R110_Late_Antiquity_Crypta_Balbi
9.14401444I2215_Malak_Preslavets
9.16999455R1289_Medieval_Era_Cancelleria
9.54338514I7673_NE_Iberia_c.6-8CE_ES
9.68139453R474_Iron_Age_Civitavecchia
9.70848598CarthagoMaghrebiAndalusia_I7457
9.77754570I12515_SE_Iberia_c.10-16CE
9.77754570SpaniardCordobaCaliphate_I12515
9.78898360BRC003_Dodecad_K12b
9.85898575France_BA_NIED
10.09213060GalloRomanCeltMixIberia_I10866
Distance to:Duarte
2.6530217740.60% I8210_NE_Iberia_Greek_Empuries1 + 59.40% MoriscoConvertAndalusia_I7425
2.9285437639.80% I8202_NE_Iberia_RomP_Empuries1 + 60.20% MoriscoConvertAndalusia_I7425
3.0800683654.60% MoriscoConvertAndalusia_I7425 + 45.40% Pre-RomanGirona_I3324
3.1197563551.40% I8209_NE_Iberia_Greek_Empuries1 + 48.60% MoriscoConvertAndalusia_I7425
3.1197563548.60% MoriscoConvertAndalusia_I7425 + 51.40% VasconicTribe_I8209
3.1963219955.00% I8146_SE_Iberia_c.10-16CE + 45.00% I8210_NE_Iberia_Greek_Empuries1
3.2020339038.00% I8341_NE_Iberia_Greek_Empuries1 + 62.00% MoriscoConvertAndalusia_I7425
3.2506504353.80% MoriscoConvertAndalusia_I7425 + 46.20% VasconesTribeVasconia_I3759
3.4241419243.80% I8146_SE_Iberia_c.10-16CE + 56.20% I8209_NE_Iberia_Greek_Empuries1
3.4241419243.80% I8146_SE_Iberia_c.10-16CE + 56.20% VasconicTribe_I8209
3.4537515850.00% I8146_SE_Iberia_c.10-16CE + 50.00% Pre-RomanGirona_I3324
3.4709727349.80% MoriscoConvertAndalusia_I7425 + 50.20% VisigothIberianGirona_I12034
3.5120883153.00% MoriscoConvertAndalusia_I7425 + 47.00% VasconesTribeVasconia_I3758
3.5195364740.20% France_IA_NOR3-6 + 59.80% I3578_SE_Iberia_c.5-8CE
3.5788596055.80% I8146_SE_Iberia_c.10-16CE + 44.20% I8202_NE_Iberia_RomP_Empuries1
3.6371630756.00% CarthagoMaghrebiAndalusia_I7457 + 44.00% I8209_NE_Iberia_Greek_Empuries1
3.6371630756.00% CarthagoMaghrebiAndalusia_I7457 + 44.00% VasconicTribe_I8209
3.6477122537.40% I8344_NE_Iberia_Greek_Empuries1 + 62.60% MoriscoConvertAndalusia_I7425
3.6501531374.80% EarlyMedievalIberiaGranada_I3981 + 25.20% France_IA_ATT26
3.6732199152.00% MoriscoConvertAndalusia_I7425 + 48.00% RISE254_Szazhalombatta-Foldvar_Hungary_3631_years
3.6813184466.80% CarthagoMaghrebiAndalusia_I7457 + 33.20% I8210_NE_Iberia_Greek_Empuries1
3.682453429.60% I1951_GD39_Ganj_Dareh_Iran_Neolithic + 90.40% I2215_Malak_Preslavets
3.7125387478.00% EarlyMedievalIberiaGranada_I3981 + 22.00% NorthAlpineSouthDutch_AITI_50
3.7127084068.40% I3578_SE_Iberia_c.5-8CE + 31.60% RISE61_Kyndelose_Denmark_4071_years
3.7146185767.40% CarthagoMaghrebiAndalusia_I7457 + 32.60% I8202_NE_Iberia_RomP_Empuries1
Target: Duarte
Distance: 1.4918% / 1.49180577 | R3P | ADC: 0.25x RC
43.8MoriscoConvertAndalusia_I7425
33.4France_BA_NIED
22.8Bul8_Balkans_BronzeAge

Target: Duarte
Distance: 0.8209% / 0.82088388 | R4P | ADC: 0.25x RC
32.0I8146_SE_Iberia_c.10-16CE
29.4Bul8_Balkans_BronzeAge
19.9scy010_Scythian
18.7utigGLR003B1

Target: Duarte
Distance: 0.6776% / 0.67762082 | R5P | ADC: 0.25x RC
38.1I8146_SE_Iberia_c.10-16CE
20.0I12648_SE_Iberia_c.10-16CE
17.3Bul8_Balkans_BronzeAge
12.6CuevadelaPalomaSpain_I3243
12.0Roman-SoldierFN_2

Target: Duarte
Distance: 0.1931% / 0.19310011 | R6P | ADC: 0.25x RC
25.2I8146_SE_Iberia_c.10-16CE
24.6Bul8_Balkans_BronzeAge
17.6utigGLR003B1
14.7scy304_Scythian
11.6scy009_Scythian
6.3Anatolia_N_Rev5

Target: Duarte
Distance: 0.0662% / 0.06623697 | R7P | ADC: 0.25x RC
30.6I12648_SE_Iberia_c.10-16CE
20.3Bul8_Balkans_BronzeAge
20.3I8146_SE_Iberia_c.10-16CE
19.8MoriscoConvertAndalusia_I7425
5.6RISE145_Polwica_Poland_3677_years
3.4scy304_Scythian



 
Last edited:
Thanks Duarte, I'd upvote but I'm out of juice. I think it's high time we start updating this spreadsheet again. I have quite a few updates pending. With Salento's help we can try to ascertain all available samples. Also, with Maciamo's expertise, we can see these samples be utilized as coherent groups for the ethnicity Checker.
 
Thanks Duarte, I'd upvote but I'm out of juice. I think it's high time we start updating this spreadsheet again. I have quite a few updates pending. With Salento's help we can try to ascertain all available samples. Also, with Maciamo's expertise, we can see these samples be utilized as coherent groups for the ethnicity Checker.

I'm the one who thanks to you, Salento and Maciamo for the great work that allows us to make an ancestry assessment much beyond the commercial calculators.
 
I'm the one who thanks to you, Salento and Maciamo for the great work that allows us to make an ancestry assessment much beyond the commercial calculators.

Thanks Duarte for consolidating the various samples :)
 
from: ... Genetic structure of 15,000y old North Africans associated with the Iberomaurusian

Grotte des Pigeons, Taforalt, Morocco:

Code:
TAF009_Dod_K12b,0.00,3.54,60.38,2.05,0.00,0.00,2.48,18.95,8.83,0.00,0.00,3.78
TAF010_Dod_K12b,0.00,0.55,63.90,3.27,0.00,0.17,1.39,18.70,5.98,0.00,0.00,6.05
TAF011_Dod_K12b,0.00,1.28,64.11,2.45,0.00,0.07,0.70,18.22,5.74,0.18,0.00,7.24
TAF012_Dod_K12b,0.00,1.79,63.81,0.80,0.44,0.00,3.27,16.18,5.76,0.59,0.00,7.35
TAF013_Dod_K12b,0.00,1.07,61.84,2.72,0.00,0.02,1.89,18.58,6.99,0.00,0.00,6.89
TAF014_Dod_K12b,0.00,0.74,62.76,2.95,0.00,0.00,2.12,18.14,5.34,0.00,0.00,7.95
TAF015_Dod_K12b,0.00,0.00,62.82,1.87,0.00,0.90,0.00,15.76,6.67,3.45,0.00,8.52

https://science.sciencemag.org/content/360/6388/548
 
from: ... Genetic structure of 15,000y old North Africans associated with the Iberomaurusian

Grotte des Pigeons, Taforalt, Morocco:

Code:
TAF009_Dod_K12b,0.00,3.54,60.38,2.05,0.00,0.00,2.48,18.95,8.83,0.00,0.00,3.78
TAF010_Dod_K12b,0.00,0.55,63.90,3.27,0.00,0.17,1.39,18.70,5.98,0.00,0.00,6.05
TAF011_Dod_K12b,0.00,1.28,64.11,2.45,0.00,0.07,0.70,18.22,5.74,0.18,0.00,7.24
TAF012_Dod_K12b,0.00,1.79,63.81,0.80,0.44,0.00,3.27,16.18,5.76,0.59,0.00,7.35
TAF013_Dod_K12b,0.00,1.07,61.84,2.72,0.00,0.02,1.89,18.58,6.99,0.00,0.00,6.89
TAF014_Dod_K12b,0.00,0.74,62.76,2.95,0.00,0.00,2.12,18.14,5.34,0.00,0.00,7.95
TAF015_Dod_K12b,0.00,0.00,62.82,1.87,0.00,0.90,0.00,15.76,6.67,3.45,0.00,8.52


https://science.sciencemag.org/content/360/6388/548

This is a fantastic addition to the overall set! These Iberomaurusian form correctly near Maciamo's grouping for Epipalaeolithic North Africa.

MP0nHWL.png
 
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