Slavic Italian
08-08-2018, 11:20 PM
I thought I would share some of my results and to be honest they did a good job with identifying much of my recent ancestry. This is a lot of info and yes I have a good bit of German.
nMonte3 (all references and without pen=0)
"distance%=8.149"
ONLY RESULTS ABOVE 0.4
Hessen,35 Nordrhein-Westfalen,12 IT_Aosta,3.8 Central_Ost_Preussen,3.6 NL_Noord_Holland,3.2 Baden-Württemberg,2.6 Hungary,2 IT_Trentino,1.8 IT_Veneto,1.8 Saarland,1.8 NL_Gelderland,1.6 FR_North-East,1.4 IT_Friuli,1.4 IT_Piemonte,1.4 NL_Utrecht,1.4 Croatia,1.2 Croats_BIH,1.2 IT_Emilia-Romagna,1.2 Mecklenburg-Vorpommern,1.2 Sachsen-Anhalt,1.2 Saxony,1.2 Swiss_Italian,1.2 IT_Ladinia,1 IT_Liguria,1 Malta,0.8 NL_Friesland,0.8 Belarus_Polesye,0.6 IT_Abruzzo,0.6 IT_Apulia,0.6 IT_Calabria,0.6 IT_Lazio,0.6 IT_Tuscany,0.6 Slovakia,0.6 Slovenia,0.6 Greater_Poland_Wielkopolska),0.4 IT_Marche,0.4 Oberland(western_Ost_Preussen),0.4 PL_North,0.4 PL_Subcarpathia,0.4 Sicily_Katania,0.4 Sicily_Trapani,0.4
Admix4 oracle (two methods, one of them is usually more speculative) The oracle works in a similar way to the Gedmatch Oracles, though the estimates here are far more robust. One shouldn‘t take all of them literaly, but rather as extreme examples of possible distant admixtures. Admix4 is a different tool which is similar to the Gedmatch oracles. it compares your frequencies to the list of most similar averages ( The same process as nMonte single item distances) or models you as a combination (two-way, three-way, or four-way) of different populations. In some cases it will be in line with the actual ethnic combination you inherited from your parents and grandparents ancestries. It may be the case that different populations show up in each oracle, especially for people of a mixed background.
Least-squares method.
Using 1 population approximation: 1 Baden-Württemberg @ 10,179362 2 Hessen @ 10,292532 3 Swiss_German @ 10,764303 4 Rheinland-Pfalz @ 10,826221 5 FR_North-East @ 11,190601 6 Bayern @ 11,193135 7 Walloons @ 11,824337 8 Flemish @ 12,006354 9 Dutch_Limburg @ 12,361425 10 Austria @ 12,817408 500 iterations.
Using 2 populations approximation: 1 Nordrhein-Westfalen+IT_Friuli @ 8,001311 2 Nordrhein-Westfalen+Albanians_Montenegro @ 8,175475 3 Nordrhein-Westfalen+Kosovo @ 8,291596 4 Nordrhein-Westfalen+IT_Trentino @ 8,292668 5 Nordrhein-Westfalen+IT_Veneto @ 8,351352 6 Dutch_Noord_Holland+IT_Friuli @ 8,376815 7 Nordrhein-Westfalen+Macedonia_FYROM @ 8,389177 8 Nordrhein-Westfalen+Montenegro @ 8,39587 9 Central_Ost_Preussen+IT_Aosta @ 8,450401 10 Dutch_Noord_Holland+IT_Trentino @ 8,485339 125250 iterations.
Using 3 populations approximation: 1 50% Nordrhein-Westfalen +25% IT_Tuscany +25% Croats_BIH @ 7,048468 2 50% Nordrhein-Westfalen +25% IT_Tuscany +25% Western_Serbians @ 7,093756
1.08.2018
author: Lukasz Macuga - www.lm-genetics.ovh
3 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% Western_Serbians @ 7,096532 4 50% Nordrhein-Westfalen +25% IT_Tuscany +25% South-West_Romania @ 7,10531 5 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% South-West_Romania @ 7,108452 6 50% Nordrhein-Westfalen +25% IT_Trentino +25% South-West_Romania @ 7,115502 7 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% Croats_BIH @ 7,116998 8 50% Nordrhein-Westfalen +25% IT_Tuscany +25% Bosniaks @ 7,131739 9 50% Nordrhein-Westfalen +25% Swiss_Italian +25% South-West_Romania @ 7,146415 10 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% Bosniaks @ 7,148976 49347500 iterations.
Using 4 populations approximation: 1 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Croats_BIH @ 7,048468 2 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Western_Serbians @ 7,093756 3 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Western_Serbians @ 7,096532 4 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+South-West_Romania @ 7,10531 5 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+South-West_Romania @ 7,108452 6 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Trentino+South-West_Romania @ 7,115502 7 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Croats_BIH @ 7,116998 8 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Bosniaks @ 7,131739 9 Nordrhein-Westfalen+Nordrhein-Westfalen+Swiss_Italian+South-West_Romania @ 7,146415 10 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Bosniaks @ 7,148976 11 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Croatia @ 7,190228 12 Central_Ost_Preussen+Nordrhein-Westfalen+Hessen+South_Albania @ 7,211893 13 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+North-East_Romania @ 7,219668 14 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Trentino+Western_Serbians @ 7,226257 15 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+North-East_Romania @ 7,238871 16 Nordrhein-Westfalen+Dutch_Noord_Holland+IT_Tuscany+Croats_BI H @ 7,239132 17 Central_Ost_Preussen+Nordrhein-Westfalen+FR_North-East+South_Albania @ 7,240721 18 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Croatia @ 7,249407 19 Nordrhein-Westfalen+Dutch_Noord_Holland+IT_Tuscany+Western_S erbians @ 7,252974 20 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Piemonte+South-West_Romania @ 7,267658 1071504007 iterations.
Gaussian method. Noise dispersion set to 0,130062
Using 1 population approximation: 1 Rheinland-Pfalz @ 5,507125 2 Swiss_German @ 5,739956 3 Austria @ 5,747878 4 FR_North-East @ 5,786699 5 IT_Piemonte @ 5,856853 6 IT_Friuli @ 5,954004 7 Baden-Württemberg @ 6,08371 8 Bosniaks @ 6,095115 9 IT_Trentino @ 6,128045 10 Western_Serbians @ 6,135166 500 iterations.
Using 2 populations approximation: 1 Nordrhein-Westfalen+GR_Vlach @ 3,886429 2 Neumark_East_Brandenburg+Swiss_Italian @ 4,030941 3 Neumark_East_Brandenburg+IT_Piemonte @ 4,160111 4 Nordrhein-Westfalen+IT_Friuli @ 4,248472 5 Sachsen-Anhalt+IT_Piemonte @ 4,258963 6 Nordrhein-Westfalen+IT_Piemonte @ 4,261775 7 Central_Ost_Preussen+IT_Piemonte @ 4,281799 8 Central_Ost_Preussen+Swiss_Italian @ 4,302886 9 Nordrhein-Westfalen+Swiss_Italian @ 4,353769 10 Neumark_East_Brandenburg+IT_Emilia-Romagna @ 4,384599 125250 iterations.
Using 3 populations approximation: 1 50% Nordrhein-Westfalen +25% Swiss_Italian +25% GR_Vlach @ 3,859663 2 50% Swiss_Italian +25% Neumark_East_Brandenburg +25% Nordrhein-Westfalen @ 3,8823 3 50% Nordrhein-Westfalen +25% GR_Vlach +25% GR_Vlach @ 3,886429 4 50% Nordrhein-Westfalen +25% GR_Vlach +25% Bosniaks @ 3,891993 5 50% IT_Piemonte +25% Neumark_East_Brandenburg +25% Nordrhein-Westfalen @ 3,929749 6 50% Nordrhein-Westfalen +25% IT_Piemonte +25% GR_Vlach @ 3,93282 7 50% Nordrhein-Westfalen +25% GR_Vlach +25% Western_Serbians @ 3,935345 8 50% Nordrhein-Westfalen +25% GR_Vlach +25% Croats_BIH @ 3,951678 9 50% Swiss_Italian +25% Nordrhein-Westfalen +25% RU_Voronezh @ 3,959895
nMonte3 (all references and without pen=0)
"distance%=8.149"
ONLY RESULTS ABOVE 0.4
Hessen,35 Nordrhein-Westfalen,12 IT_Aosta,3.8 Central_Ost_Preussen,3.6 NL_Noord_Holland,3.2 Baden-Württemberg,2.6 Hungary,2 IT_Trentino,1.8 IT_Veneto,1.8 Saarland,1.8 NL_Gelderland,1.6 FR_North-East,1.4 IT_Friuli,1.4 IT_Piemonte,1.4 NL_Utrecht,1.4 Croatia,1.2 Croats_BIH,1.2 IT_Emilia-Romagna,1.2 Mecklenburg-Vorpommern,1.2 Sachsen-Anhalt,1.2 Saxony,1.2 Swiss_Italian,1.2 IT_Ladinia,1 IT_Liguria,1 Malta,0.8 NL_Friesland,0.8 Belarus_Polesye,0.6 IT_Abruzzo,0.6 IT_Apulia,0.6 IT_Calabria,0.6 IT_Lazio,0.6 IT_Tuscany,0.6 Slovakia,0.6 Slovenia,0.6 Greater_Poland_Wielkopolska),0.4 IT_Marche,0.4 Oberland(western_Ost_Preussen),0.4 PL_North,0.4 PL_Subcarpathia,0.4 Sicily_Katania,0.4 Sicily_Trapani,0.4
Admix4 oracle (two methods, one of them is usually more speculative) The oracle works in a similar way to the Gedmatch Oracles, though the estimates here are far more robust. One shouldn‘t take all of them literaly, but rather as extreme examples of possible distant admixtures. Admix4 is a different tool which is similar to the Gedmatch oracles. it compares your frequencies to the list of most similar averages ( The same process as nMonte single item distances) or models you as a combination (two-way, three-way, or four-way) of different populations. In some cases it will be in line with the actual ethnic combination you inherited from your parents and grandparents ancestries. It may be the case that different populations show up in each oracle, especially for people of a mixed background.
Least-squares method.
Using 1 population approximation: 1 Baden-Württemberg @ 10,179362 2 Hessen @ 10,292532 3 Swiss_German @ 10,764303 4 Rheinland-Pfalz @ 10,826221 5 FR_North-East @ 11,190601 6 Bayern @ 11,193135 7 Walloons @ 11,824337 8 Flemish @ 12,006354 9 Dutch_Limburg @ 12,361425 10 Austria @ 12,817408 500 iterations.
Using 2 populations approximation: 1 Nordrhein-Westfalen+IT_Friuli @ 8,001311 2 Nordrhein-Westfalen+Albanians_Montenegro @ 8,175475 3 Nordrhein-Westfalen+Kosovo @ 8,291596 4 Nordrhein-Westfalen+IT_Trentino @ 8,292668 5 Nordrhein-Westfalen+IT_Veneto @ 8,351352 6 Dutch_Noord_Holland+IT_Friuli @ 8,376815 7 Nordrhein-Westfalen+Macedonia_FYROM @ 8,389177 8 Nordrhein-Westfalen+Montenegro @ 8,39587 9 Central_Ost_Preussen+IT_Aosta @ 8,450401 10 Dutch_Noord_Holland+IT_Trentino @ 8,485339 125250 iterations.
Using 3 populations approximation: 1 50% Nordrhein-Westfalen +25% IT_Tuscany +25% Croats_BIH @ 7,048468 2 50% Nordrhein-Westfalen +25% IT_Tuscany +25% Western_Serbians @ 7,093756
1.08.2018
author: Lukasz Macuga - www.lm-genetics.ovh
3 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% Western_Serbians @ 7,096532 4 50% Nordrhein-Westfalen +25% IT_Tuscany +25% South-West_Romania @ 7,10531 5 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% South-West_Romania @ 7,108452 6 50% Nordrhein-Westfalen +25% IT_Trentino +25% South-West_Romania @ 7,115502 7 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% Croats_BIH @ 7,116998 8 50% Nordrhein-Westfalen +25% IT_Tuscany +25% Bosniaks @ 7,131739 9 50% Nordrhein-Westfalen +25% Swiss_Italian +25% South-West_Romania @ 7,146415 10 50% Nordrhein-Westfalen +25% IT_Emilia-Romagna +25% Bosniaks @ 7,148976 49347500 iterations.
Using 4 populations approximation: 1 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Croats_BIH @ 7,048468 2 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Western_Serbians @ 7,093756 3 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Western_Serbians @ 7,096532 4 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+South-West_Romania @ 7,10531 5 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+South-West_Romania @ 7,108452 6 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Trentino+South-West_Romania @ 7,115502 7 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Croats_BIH @ 7,116998 8 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Bosniaks @ 7,131739 9 Nordrhein-Westfalen+Nordrhein-Westfalen+Swiss_Italian+South-West_Romania @ 7,146415 10 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Bosniaks @ 7,148976 11 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+Croatia @ 7,190228 12 Central_Ost_Preussen+Nordrhein-Westfalen+Hessen+South_Albania @ 7,211893 13 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Tuscany+North-East_Romania @ 7,219668 14 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Trentino+Western_Serbians @ 7,226257 15 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+North-East_Romania @ 7,238871 16 Nordrhein-Westfalen+Dutch_Noord_Holland+IT_Tuscany+Croats_BI H @ 7,239132 17 Central_Ost_Preussen+Nordrhein-Westfalen+FR_North-East+South_Albania @ 7,240721 18 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Emilia-Romagna+Croatia @ 7,249407 19 Nordrhein-Westfalen+Dutch_Noord_Holland+IT_Tuscany+Western_S erbians @ 7,252974 20 Nordrhein-Westfalen+Nordrhein-Westfalen+IT_Piemonte+South-West_Romania @ 7,267658 1071504007 iterations.
Gaussian method. Noise dispersion set to 0,130062
Using 1 population approximation: 1 Rheinland-Pfalz @ 5,507125 2 Swiss_German @ 5,739956 3 Austria @ 5,747878 4 FR_North-East @ 5,786699 5 IT_Piemonte @ 5,856853 6 IT_Friuli @ 5,954004 7 Baden-Württemberg @ 6,08371 8 Bosniaks @ 6,095115 9 IT_Trentino @ 6,128045 10 Western_Serbians @ 6,135166 500 iterations.
Using 2 populations approximation: 1 Nordrhein-Westfalen+GR_Vlach @ 3,886429 2 Neumark_East_Brandenburg+Swiss_Italian @ 4,030941 3 Neumark_East_Brandenburg+IT_Piemonte @ 4,160111 4 Nordrhein-Westfalen+IT_Friuli @ 4,248472 5 Sachsen-Anhalt+IT_Piemonte @ 4,258963 6 Nordrhein-Westfalen+IT_Piemonte @ 4,261775 7 Central_Ost_Preussen+IT_Piemonte @ 4,281799 8 Central_Ost_Preussen+Swiss_Italian @ 4,302886 9 Nordrhein-Westfalen+Swiss_Italian @ 4,353769 10 Neumark_East_Brandenburg+IT_Emilia-Romagna @ 4,384599 125250 iterations.
Using 3 populations approximation: 1 50% Nordrhein-Westfalen +25% Swiss_Italian +25% GR_Vlach @ 3,859663 2 50% Swiss_Italian +25% Neumark_East_Brandenburg +25% Nordrhein-Westfalen @ 3,8823 3 50% Nordrhein-Westfalen +25% GR_Vlach +25% GR_Vlach @ 3,886429 4 50% Nordrhein-Westfalen +25% GR_Vlach +25% Bosniaks @ 3,891993 5 50% IT_Piemonte +25% Neumark_East_Brandenburg +25% Nordrhein-Westfalen @ 3,929749 6 50% Nordrhein-Westfalen +25% IT_Piemonte +25% GR_Vlach @ 3,93282 7 50% Nordrhein-Westfalen +25% GR_Vlach +25% Western_Serbians @ 3,935345 8 50% Nordrhein-Westfalen +25% GR_Vlach +25% Croats_BIH @ 3,951678 9 50% Swiss_Italian +25% Nordrhein-Westfalen +25% RU_Voronezh @ 3,959895