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Thread: Post your MDLP K23b calculator/Oracle/ ancestry here

  1. #61
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    U.S
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    Indian
    Y-DNA (P)
    Z30522+
    mtDNA (M)
    C4a1a (T195C!)

    India United States of America Chola Empire India Maratha Empire
    Breakdown:
     


    Population
    Amerindian -
    Ancestral_Altaic 3.63%
    South_Central_Asian 28.86%
    Arctic 0.42%
    South_Indian 50.84%
    Australoid -
    Austronesian 2.20%
    Caucasian 5.97%
    Archaic_Human 0.27%
    East_African -
    East_Siberian 0.61%
    European_Early_Farmers -
    Khoisan 0.15%
    Melano_Polynesian -
    Archaic_African -
    Near_East 1.40%
    North_African 1.38%
    Paleo_Siberian -
    African_Pygmy -
    South_East_Asian 0.38%
    Subsaharian -
    Tungus-Altaic -
    European_Hunters_Gatherers 3.87%



    Oracle:
     


    # Population (source) Distance
    1 Brahmins_UP ( ) 3.77
    2 Vaish ( ) 4.17
    3 TN_Brahmin ( ) 4.27
    4 Brahmin_Tamil ( ) 5.34
    5 GujaratiC_GIH ( ) 6
    6 Kshatriya ( ) 6.32
    7 Punjabi_Lahore_PJL ( ) 7.21
    8 Meghawal ( ) 7.68
    9 GujaratiB_GIH ( ) 8.48
    10 Tiwari ( ) 8.77
    11 Srivastava ( ) 9.3
    12 Dharkar ( ) 9.47
    13 Lambadi ( ) 9.63
    14 GujaratiD_GIH ( ) 11.31
    15 Muslim_India ( ) 11.4
    16 Kanjar ( ) 11.81
    17 Marwadi_Middle_caste ( ) 12.03
    18 Velama ( ) 12.89
    19 Velamas ( ) 13.25
    20 Dhaka_mixed_popul ( ) 13.7


    # Primary Population (source) Secondary Population (source) Distance
    1 74% Kanjar ( ) + 26% Pakistani_Pushtun ( ) @ 2.23
    2 63.9% Pakistani ( ) + 36.1% Chenchu ( ) @ 2.24
    3 54.6% Punjabi_Gujjar ( ) + 45.4% Chenchu ( ) @ 2.35
    4 55.1% Tharu ( ) + 44.9% Punjabi_Gujjar ( ) @ 2.37
    5 60.1% Dusadh ( ) + 39.9% Pathan ( ) @ 2.37
    6 77.6% Piramalai_Kallar ( ) + 22.4% Tajik_Yagnobi ( ) @ 2.41
    7 54.6% Pakistani ( ) + 45.4% Tharu ( ) @ 2.43
    8 68.8% Pakistani ( ) + 31.2% Nihali ( ) @ 2.48
    9 55.9% Vishwabrahmin ( ) + 44.1% Pathan ( ) @ 2.48
    10 76.7% Naidu ( ) + 23.3% Tajik_Yagnobi ( ) @ 2.49
    11 81.4% Muslim_India ( ) + 18.6% Makrani ( ) @ 2.52
    12 70% Lambadi ( ) + 30% Jatt_Haryana ( ) @ 2.52
    13 84.1% Kanjar ( ) + 15.9% Tajik_Yagnobi ( ) @ 2.52
    14 66.5% Pakistani ( ) + 33.5% Kurumba ( ) @ 2.52
    15 60.5% Scheduled_Caste_UP ( ) + 39.5% Pathan ( ) @ 2.53
    16 56.3% Kol ( ) + 43.7% Pathan ( ) @ 2.54
    17 78.1% Lambadi ( ) + 21.9% Pakistani_Pushtun ( ) @ 2.54
    18 79.7% Kanjar ( ) + 20.3% Afghan_Pushtun ( ) @ 2.55
    19 71.7% Pakistani ( ) + 28.3% Malayan ( ) @ 2.55

    Last edited by soulblighter; 09-13-2014 at 11:39 AM.
    Paternal YDNA: G-P303+ -> G-Z30522+
    Paternal mtDNA: U7a3b1
    Maternal YDNA: R-Z2123+ -> R-YP526+
    Maternal mtDNA: C4a1 (T195C!)

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  3. #62
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    United States of America Canada
    Quote Originally Posted by Dr_McNinja View Post
    Also for South Asians, a pattern seems to emerge in column AE (Near East, North African, Caucasian, and half of South Indian).

    The volatility is in Gedrosian/ANI. That's because of the ANE present within it. But the Caucasian half of S-Indian is mostly from our ENF-type admixture, which is why it's rather consistent across individuals in spite of the different S-Indian amounts. My S-Indian being high limits my Caucasian to way below everyone else. So it's almost like the South Indian takes priority for the software over Gedrosian as a South Asian component. The problem is that South Indian is dictated by an imprecise/ambiguous ASI element so it too varies, which forces Gedrosian to vary.

    I think the Pashtun affinity to Caucasian is what makes them a more stable and superior proxy for ANI than Baloch or Kalash. The Pashtun component swallows up the nearby Caucasian stuff and kind of ups its own priority as far as the software is concerned. But the main thing is that we know there is ANI ancestry for most people here (even the South Indians here are Brahmins). South Indian is just a bad choice because of its Caucasian component. It's extremely unlikely our Caucasian is from Southeast India rather than Southwest Asia.

    My result could also swap from 28% equivalent to HRP0341/HRP0353 to 31% equivalent to HRP0350/Kenji depending on if I treated EEF like Caucasian or European. On the PCA, EEF is next to Caucasian at the extreme end.
    To elaborate on this, the Caucasian half of S-Indian mostly resembles our generic ENF-type admixture the best, so it takes priority and as much of it as it can before it goes into other components. The problem comes from thinking a component signifies an "origin". It's why the same effect is achieved whether we use South Indians or Gujaratis or another Indian group, we should call it just "Indian" to mean our admixture resembles it and to symbolize the whole subcontinent/country. That makes sense. NW Indians should resemble South Indians almost as much as Gedrosian/Baloch/whatever, but both (NW Indians and S-Indians) got their admixture from ancestral SW-Asia/Near East. That's where it originated.

    Since we don't have a good ASI stand-in in any calculator aside from Eurogenes ANE K7, any kind of ambiguous East Eurasian is lumped in with ASI and attracts even more of our basal ENF admixture for a larger "Indian" resemblance. That wouldn't be a bad "strategy" for the software except we're labeling the component South Indian which seems to imply that our admixture is coming from there, when it just resembles it, the only Indian population in the group.

    Gedrosian is kind of a middle or leftover Caucasian signal which is next in resemblance/priority, but depending on ANE admixture, will take more or less priority. ANE however is fractured differently in different individuals, thus the many outliers in Gedrosian and excess Caucasian left over as West/North Caucasus (depending on how much ANE is used). (So in my case where some ANE seems to turn into ENA means less Gedrosian, more excess East Eurasian, more basal Caucasian, hence higher S-Indian priority, and still some East Eurasian left over in Arctic components and ENF-type left over in Atlantic-Mediterranean/West Europe/Near East)

    FTDNA using Pashtun avoided all that because they had a strong pull towards ANE and Gedrosian/Caucasus, even some Near East-type admixture so it pulls in excess ENF-type. We're left with two big scores, Indian, and whatever Pashtun represents. As Sein said, they are a great group to use to represent Central Asia but because they inherit the Indo-European affinities, "Eurasian Heartland" was pretty literally correct. They had plenty of attraction to Europe too. Their original idea to label South Asian (using Gujarati reference population) "Indian subcontinent" also was pretty good.

    S-Indian is fundamentally an incorrect component to use though because of these issues. Our ENF type admixture as I said above didn't come from SE-India, it came from SW-Asia/Near East. If we could isolate ASI we'd see even the South Indians getting pulled sharply to the Northwest with very low ASI scores relative to their current ENF (as is seen in ANE K7). That's also because modern South Indians likely have many autosomal genetic links to "ANI". Ideally we'd use South Indians as a stand-in for North India or India in general if we had to use it as a component at all. That's what the software's representing with it. Gujarati does the same in FTDNA but it winds up fighting whatever ANI component is used (whether Baloch, Kalash, or Pashtun).
    Last edited by Dr_McNinja; 09-13-2014 at 11:57 AM.
    Paternal - Y-DNA: J2b2* (J-M241) Z2432+ Z2433+ Y978+ (J2b2a2b1*) (Hidden Content ) (YFull: YF02959) (FTDNA Kit B6225), mtDNA: M18a* (FTDNA Kit 329180) (YFull: YF63773)
    Maternal- Y-DNA: R1a1a1b2a1a2c2d5a* L657+ Y7+ (R-Y16494*) (FTDNA Kit 311047) (YFull: YF68408), mtDNA: Hidden Content (FTDNA Kit B6225) (YFull: YF02959) (Mother's Mother's Father: R1a1a1b2a1a2c2* Y7+ Y29+ (R-Y29*) (FTDNA Kit 329181) (YFull: YF65256))

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  5. #63
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    United States of America Iran United States of America Iran
    Admix Results (sorted):

    Code:
    #	Population	Percent
    1	Caucasian	35.5
    2	South_Central_Asian	25.24
    3	Near_East	12.41
    4	South_Indian	6
    5	European_Early_Farmers	5.92
    6	European_Hunters_Gatherers	5.46
    7	Ancestral_Altaic	3.45
    8	South_East_Asian	2.06
    9	North_African	1.23
    10	Arctic	1.11
    11	Melano_Polynesian	0.58
    12	Archaic_Human	0.39
    13	African_Pygmy	0.32
    14	Australoid	0.16
    15	East_African	0.11
    16	East_Siberian	0.07
    Single Population Sharing:

    Code:
    #	Population (source)	Distance
    1	Iranian ( )	6.24
    2	Azeri ( )	9.38
    3	Kurd ( )	9.4
    4	Uzbek_Tashkent ( )	12.43
    5	Baku_WGA ( )	12.82
    6	Iraki ( )	12.99
    7	Turk_Adana ( )	13.51
    8	Uzbekistani_Jew ( )	15.21
    9	Stalskoe_Kumyk ( )	15.63
    10	Kurd_Jew ( )	16.33
    11	Turk ( )	17.32
    12	Ain_Touta_WGA ( )	17.45
    13	Turk_Kayseri ( )	17.6
    14	Azeri_Dagestan ( )	17.67
    15	Lak ( )	17.83
    16	Georgian_Jew ( )	17.89
    17	Tabassaran ( )	18.02
    18	Turk_Aydin ( )	18.05
    19	Iranian_Jew ( )	18.33
    20	Dargin_Urkarah ( )	18.45
    Mixed Mode Population Sharing:

    Code:
    #	 	Primary Population (source)	Secondary Population (source)	Distance
    1	 	78.1%	Uzbekistani_Jew ( )	+	21.9%	Burusho ( )	@	2.75
    2	 	66.3%	Georgian_Jew ( )	+	33.7%	Pashtun_Afghani ( )	@	2.87
    3	 	60.6%	Jew_Tat ( )	+	39.4%	Pashtun_Afghani ( )	@	2.94
    4	 	67%	Uzbekistani_Jew ( )	+	33%	Afghan_Pushtun ( )	@	3.19
    5	 	61.5%	Jew_Tat ( )	+	38.5%	Tajik_Pomiri_Ishkashim ( )	@	3.25
    6	 	75.9%	Uzbekistani_Jew ( )	+	24.1%	Pathan ( )	@	3.29
    7	 	70.1%	Uzbekistani_Jew ( )	+	29.9%	Pashtun_Afghani ( )	@	3.29
    8	 	60.9%	Iraqi_Jew ( )	+	39.1%	Pashtun_Afghani ( )	@	3.31
    9	 	90.8%	Kurd ( )	+	9.2%	Onge ( )	@	3.43
    10	 	63.3%	Georgian_Jew ( )	+	36.7%	Afghan_Pushtun ( )	@	3.44
    11	 	79.9%	Uzbekistani_Jew ( )	+	20.1%	Sindhi ( )	@	3.48
    12	 	91.7%	Kurd ( )	+	8.3%	Kharia ( )	@	3.56
    13	 	57.3%	Jew_Tat ( )	+	42.7%	Afghan_Pushtun ( )	@	3.56
    14	 	88.1%	Kurd ( )	+	11.9%	Nepalese ( )	@	3.56
    15	 	72.8%	Uzbekistani_Jew ( )	+	27.2%	Pakistani_Pushtun ( )	@	3.62
    16	 	92%	Kurd ( )	+	8%	Dhurwa ( )	@	3.69
    17	 	69.8%	Azeri ( )	+	30.2%	Parsi ( )	@	3.7
    18	 	78.7%	Uzbekistani_Jew ( )	+	21.3%	Punjabi_Gujjar ( )	@	3.71
    19	 	92%	Kurd ( )	+	8%	Bhunjia ( )	@	3.71
    20	 	72.8%	Georgian_Jew ( )	+	27.2%	Pathan ( )	@	3.71

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  7. #64
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    Quote Originally Posted by bored View Post
    I think this is where kenji plots - on the India-Pakistan border in South Punjab.

    https://www.google.ca/maps/place/30%...!3m1!1s0x0:0x0

    How can you tell this?
    is there some kinda tool for it?

  8. #65
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    جای کیان
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    Tajik-Pashtun
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    R0a2d

    Greater Khorasan Saffarid Dynasty Ghaznavid Dynasty Late United States of America Afghanistan Tajikistan
    Oracle 4 gave me this:

    Using 2 populations approximation:
    1 50% Pakistani_Pushtun +50% Tajik_Yagnobi @ 4.388344

    Which makes sense. I think my maternal side (Karlani Pashtun) is more South Asian shifted than your average Durrani, and my paternal (Panjshiri Tajik) less so, which is why my results tend to be Durrani-like with more of a North Eurasian pull.

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  10. #66
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    Nepalese
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    N1e'I

    Nepal United States of America
    Here's mine. I'm a Nepalese Brahmin:
    Code:
    Population	 
    Amerindian	0.57%
    Ancestral_Altaic	5.17%
    South_Central_Asian	31.05%
    Arctic	1.39%
    South_Indian	37.25%
    Australoid	-    
    Austronesian	0.81%
    Caucasian	9.98%
    Archaic_Human	-    
    East_African	-    
    East_Siberian	-    
    European_Early_Farmers	0.84%
    Khoisan	-    
    Melano_Polynesian	0.67%
    Archaic_African	-    
    Near_East	-    
    North_African	-    
    Paleo_Siberian	0.19%
    African_Pygmy	-    
    South_East_Asian	2.00%
    Subsaharian	-    
    Tungus-Altaic	2.35%
    European_Hunters_Gatherers	7.72%
    Oracle:
    Code:
    1 pop
    1 Jatt_Muslim @ 5.168109
    2 Jatt_Haryana @ 6.970958
    3 Tiwari @ 7.768763
    4 Jatt_Pahari @ 8.512095
    5 GujaratiA_GIH @ 8.520392
    6 Pakistani @ 9.104474
    7 GujaratiB_GIH @ 10.682746
    8 Vaish @ 12.760085
    9 Kshatriya @ 12.935912
    10 Punjabi_Gujjar @ 13.393120
    11 Brahmin_Tamil @ 13.546372
    12 Cochin_Jew @ 14.254344
    13 Brahmins_UP @ 14.573712
    14 Pakistani_Pushtun @ 14.621076
    15 Mumbai_Jew @ 14.828198
    16 Pathan @ 15.425746
    17 Burusho @ 15.508182
    18 TN_Brahmin @ 16.186518
    19 Sindhi @ 16.870111
    20 Meghawal @ 17.661121
    Using 2 populations approximation:
    1 50% Piramalai_Kallar +50% Tajik_Pomiri_Rushan @ 2.302516
    
    
    Using 3 populations approximation:
    1 50% Piramalai_Kallar +25% Tajik_Pomiri_Ishkashim +25% Tajik_Pomiri_Rushan @ 2.160800
    
    
    Using 4 populations approximation:
    1 Lambadi + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan + Vysya @ 1.899118
    2 GujaratiD_GIH + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan + Vishwabrahmin @ 2.048897
    3 Piramalai_Kallar + Tajik_Pomiri_Rushan + Tajik_Pomiri_Rushan + Vysya @ 2.087556
    4 Lambadi + Lodhi + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Ishkashim @ 2.090164
    5 Lambadi + Scheduled_Caste_UP + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Ishkashim @ 2.091657
    6 Scheduled_Caste_UP + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan + Velamas @ 2.106821
    7 Lambadi + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Shugnan + Vysya @ 2.126652
    8 Lodhi + Piramalai_Kallar + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan @ 2.133837
    9 Piramalai_Kallar + Piramalai_Kallar + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan @ 2.160800
    10 Bengali_Bangladesh_BEB + Pakistani + Tajik_Pomiri_Rushan + Tiwari @ 2.166755
    11 Scheduled_Caste_UP + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan + Velama @ 2.169428
    12 Dusadh + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan + Velamas @ 2.172720
    13 Kanjar + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan + Vysya @ 2.175790
    14 GujaratiD_GIH + Kamsali + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan @ 2.180608
    15 Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan + Velamas + Vishwabrahmin @ 2.183460
    16 Lambadi + Scheduled_Caste_Tamil_Nadu + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan @ 2.186034
    17 GujaratiD_GIH + Kol + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan @ 2.200183
    18 Kamsali + Lambadi + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Rushan @ 2.210428
    19 Dusadh + Lambadi + Tajik_Pomiri_Ishkashim + Tajik_Pomiri_Ishkashim @ 2.217819
    20 Naidu + Tajik_Pomiri_Rushan + Tajik_Pomiri_Rushan + Vysya @ 2.217962
    Last edited by everest59; 09-13-2014 at 04:33 PM.

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  12. #67
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    Ethnicity
    Human
    Nationality
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    U5a1

    Netherlands Italy Italy Two Sicilies
    This is what I get in 4-oracle when I use rawdata from 23andme.

    Admix Results (sorted):

    # Population Percent
    1 Caucasian 30.44
    2 European_Early_Farmers 27.71
    3 European_Hunters_Gatherers 23.63
    4 South_Central_Asian 7.36
    5 Near_East 4.61
    6 North_African 2.91
    7 Ancestral_Altaic 2.61

     
    Using 1 population approximation:
    1 Kosovar @ 8.074533
    2 Italian_Tuscan @ 9.960309
    3 Italian_Piedmont @ 10.037721
    4 Greek_Thessaly @ 10.776674
    5 Greek_Thessaloniki @ 11.394757
    6 Albanian_Tirana @ 11.635029
    7 Italian_Bergamo @ 11.827899
    8 Bulgarian @ 12.169189
    9 Central_Greek @ 13.478659
    10 Italian_Abruzzo @ 13.812310
    11 Greek_Peloponnesos @ 13.905783
    12 Macedonian @ 14.052575
    13 Montenegrian @ 14.622158
    14 Romanian @ 14.835368
    15 Sicilian_Trapani @ 15.229655
    16 French @ 15.529048
    17 Gagauz @ 15.753303
    18 Crimean_Tatar_Mountain @ 15.819877
    19 Ashkenazi_Jew @ 15.887488
    20 South_German @ 16.116692


     
    Using 2 populations approximation:
    1 50% Italian_South +50% Welsh @ 2.494922


    Using 3 populations approximation:
    1 50% English +25% Spanish_Andalucia_IBS +25% Turk_Trabzon @ 1.535988


    Using 4 populations approximation:
    1 Armenian_Yerevan + English_Cornwall_GBR + Sardinian + Ukrainian_East @ 1.136079
    2 Armenian + Croat_BH + French + Spanish_Cantabria_IBS @ 1.146280
    3 Armenian + Dutch + Sardinian + Sorb @ 1.148814
    4 Armenian_Yerevan + Dutch + Sardinian + Sorb @ 1.154213
    5 English + South_German + Spanish_Andalucia_IBS + Turk_Trabzon @ 1.171559
    6 1_LBK380 + Chechen + Lithuanian + Spanish_Andalucia_IBS @ 1.179159
    7 South_German + Spanish_Murcia_IBS + Turk_Trabzon + Welsh @ 1.201527
    8 South_German + Spanish_Extremadura_IBS + Turk_Trabzon + Welsh @ 1.218308
    9 Armenian_Yerevan + French_South + Pole_South + Spanish_Baleares_IBS @ 1.220609
    10 English + South_German + Spanish_Castilla_la_Mancha_IBS + Turk_Trabzon @ 1.221242
    11 1_Skoglund_farmer + Belarusian + Kakheti + Maltese @ 1.223299
    12 Armenian_Yerevan + English_Cornwall_GBR + Russian_South + Sardinian @ 1.229182
    13 1_Skoglund_farmer + Kakheti + Maltese + Pole @ 1.231377
    14 French + North_German + Spanish_Extremadura_IBS + Turk_Trabzon @ 1.232467
    15 Armenian + English_Cornwall_GBR + Russian_South + Sardinian @ 1.244985
    16 Armenian_Yerevan + English_Cornwall_GBR + Sardinian + Ukrainian_Russian @ 1.258378
    17 Armenian_Yerevan + Pole_South + Spanish_Cataluna_IBS + Spanish_Valencia_IBS @ 1.259799
    18 English_Kent_GBR + South_German + Spanish_Andalucia_IBS + Turk_Trabzon @ 1.264382
    19 CEU + South_German + Spanish_Andalucia_IBS + Turk_Trabzon @ 1.268688
    20 1_Skoglund_farmer + Belarusian_South + Kakheti + Maltese @ 1.278332
    Mc Donald:
    Most likely fit is 62.4% (+- 9.5%) Europe (various subcontinents)
    and 37.6% (+- 9.5%) Mideast (various subcontinents)
    Dodecad World9:
    1 50% S_Italian_Sicilian +50% Dutch @ 1.083
    2 50% German +50% S_Italian @ 1.126
    3 50% Dutch +50% S_Italian @ 1.148

  13. The Following 3 Users Say Thank You to Dimanto For This Useful Post:

     Scarlet Ibis (09-14-2014),  Táltos (09-14-2014),  Varun R (09-13-2014)

  14. #68
    Registered Users
    Posts
    745
    Sex
    Location
    Estonia
    Ethnicity
    Belarusian
    Y-DNA (P)
    I2-A1328
    mtDNA (M)
    J1c

    By the way, one can't blame "the calculator effect" for producing the strange results.

    There is no calculator effect in the K23b, because i created this calculator according to Polako's guidelines
    1) Set aside five of the most typical individuals from each of your reference populations.

    2) Run your ADMIXTURE analysis with the remaining samples.

    3) Use the allele frequencies from the ADMIXTURE run to test the individuals you set aside and produce population averages from their results only.
    This should fix all the problems. I set aside 3000 individials from my dataset and then i ran the ADMIXTURE analysis on the rest of my dataset (circa 2000 persons). After that i used the allele frequencies inferred from the ADMXTURE run for making DIY calculator and ran 2000 persons through this DIY calcultor to produce population averages from the results of people not included into the original ADMIXTURE run.

    Contrary to Polako's assertion, the last step of running thousands individuals through DIY calculator was not very time consuming, because i wrote a script to do this job and it took me only 30 hours to accomplish the task.

    Nevertheless, here is another effect of sampling that comes to play its crucial role in downplaying the K23b's accuracy. This is the effect of ascertainment bias that was explained by Dienekes's years ago: " for short clines (e.g., within Europe) that are not securely fastened (few individuals from outlying groups), we can expect relatively large systematic errors...increasing sample sizes will not overcome this issue because adding more individuals does not change the set of SNPs that the various groups/companies have genotyped over them."
    Last edited by Vadim Verenich; 09-13-2014 at 06:07 PM.

  15. The Following 8 Users Say Thank You to Vadim Verenich For This Useful Post:

     Anglecynn (09-13-2014),  Dimanto (09-13-2014),  Dr_McNinja (09-13-2014),  Rafe (09-04-2015),  Táltos (09-14-2014),  Varun R (09-13-2014),  vettor (09-13-2014),  ZephyrousMandaru (09-13-2014)

  16. #69
    Registered Users
    Posts
    2,681
    Sex
    Location
    New York
    Ethnicity
    South Asian
    Nationality
    American
    Y-DNA (P)
    J2b2-M241 (J-Y978*)
    mtDNA (M)
    M30b2a
    Y-DNA (M)
    R1a1-L657 (R-Y16494)
    mtDNA (P)
    M18a

    United States of America Canada
    https://docs.google.com/spreadsheet/...ive_web#gid=23

    Even the Bengali individual's total "basal" (probably ENF-like) Caucasian is similar to the rest of us at 28-31% though they have 54% South Indian.
    Last edited by Dr_McNinja; 09-13-2014 at 06:39 PM.
    Paternal - Y-DNA: J2b2* (J-M241) Z2432+ Z2433+ Y978+ (J2b2a2b1*) (Hidden Content ) (YFull: YF02959) (FTDNA Kit B6225), mtDNA: M18a* (FTDNA Kit 329180) (YFull: YF63773)
    Maternal- Y-DNA: R1a1a1b2a1a2c2d5a* L657+ Y7+ (R-Y16494*) (FTDNA Kit 311047) (YFull: YF68408), mtDNA: Hidden Content (FTDNA Kit B6225) (YFull: YF02959) (Mother's Mother's Father: R1a1a1b2a1a2c2* Y7+ Y29+ (R-Y29*) (FTDNA Kit 329181) (YFull: YF65256))

  17. #70
    Gold Class Member
    Posts
    448
    Sex
    Location
    Elegant Decay
    Ethnicity
    Brahmin Mixed S India
    Nationality
    American
    Y-DNA (P)
    R1a1a1b2a1a (Y7+)
    mtDNA (M)
    M5a2a

    United States of America India Myanmar
    # Population Percent
    1 South_Indian 45.85
    2 South_Central_Asian 32.09
    3 Caucasian 7.11
    4 European_Hunters_Gatherers 4.94
    5 Ancestral_Altaic 3.74
    6 South_East_Asian 2.1
    7 East_Siberian 0.95
    8 European_Early_Farmers 0.72
    9 Archaic_African 0.53
    10 Khoisan 0.53
    11 Tungus-Altaic 0.51
    12 Australoid 0.39
    13 Arctic 0.32
    14 Subsaharian 0.14
    15 African_Pygmy 0.05
    16 Paleo_Siberian 0.01

    Single Population Sharing:

    # Population (source) Distance
    1 Tiwari ( ) 4.07
    2 GujaratiB_GIH ( ) 4.12
    3 Brahmin_Tamil ( ) 4.26
    4 Vaish ( ) 4.91
    5 Kshatriya ( ) 6.34
    6 TN_Brahmin ( ) 6.99
    7 Brahmins_UP ( ) 7.21
    8 Jatt_Muslim ( ) 9.57
    9 GujaratiC_GIH ( ) 9.88
    10 Meghawal ( ) 10.16
    11 Pakistani ( ) 10.44
    12 GujaratiA_GIH ( ) 11.1
    13 Punjabi_Lahore_PJL ( ) 12.57
    14 Dharkar ( ) 15.25
    15 Srivastava ( ) 15.33
    16 Lambadi ( ) 15.42
    17 GujaratiD_GIH ( ) 15.66
    18 Jatt_Haryana ( ) 16.28
    19 Jatt_Pahari ( ) 16.78
    20 Muslim_India ( ) 17.52

    Mixed Mode Population Sharing:

    # Primary Population (source) Secondary Population (source) Distance
    1 81.3% Brahmin_Tamil ( ) + 18.7% Jatt_Haryana ( ) @ 2.06
    2 95.3% Brahmin_Tamil ( ) + 4.7% Dargin_Urkarah ( ) @ 2.09
    3 95.1% Brahmin_Tamil ( ) + 4.9% Nogai ( ) @ 2.09
    4 80.7% Pakistani ( ) + 19.3% Nihali ( ) @ 2.1
    5 95.4% Brahmin_Tamil ( ) + 4.6% Lak ( ) @ 2.12
    6 86.8% TN_Brahmin ( ) + 13.2% Tajik_Afghan ( ) @ 2.13
    7 71.8% Velamas ( ) + 28.2% Tajik_Pomiri_Rushan ( ) @ 2.13
    8 68.8% Velama ( ) + 31.2% Tajik_Pomiri_Ishkashim ( ) @ 2.14
    9 95.5% Brahmin_Tamil ( ) + 4.5% Avar ( ) @ 2.15
    10 51.7% Pathan ( ) + 48.3% Scheduled_Caste_UP ( ) @ 2.16
    11 95.3% Brahmin_Tamil ( ) + 4.7% Stalskoe_Kumyk ( ) @ 2.17
    12 95.5% Brahmin_Tamil ( ) + 4.5% Lezgin ( ) @ 2.17
    13 93.8% Brahmin_Tamil ( ) + 6.2% Tajik_Yagnobi ( ) @ 2.18
    14 86.7% TN_Brahmin ( ) + 13.3% Uzbek_Afghan ( ) @ 2.18
    15 95.5% Brahmin_Tamil ( ) + 4.5% Tabassaran ( ) @ 2.19
    16 84.2% Pakistani ( ) + 15.8% Paniya ( ) @ 2.2
    17 62.1% Naidu ( ) + 37.9% Tajik_Pomiri_Ishkashim ( ) @ 2.22
    18 92.4% Brahmin_Tamil ( ) + 7.6% Tajik_Afghan ( ) @ 2.22
    19 87.5% TN_Brahmin ( ) + 12.5% Tajik_Pomiri_Rushan ( ) @ 2.23
    20 55.3% Pathan ( ) + 44.7% Vishwabrahmin ( ) @ 2.24

    Using 2 populations approximation:
    1 50% Brahmin_Tamil +50% Tiwari @ 2.448662


    Using 3 populations approximation:
    1 50% Brahmin_Tamil +25% GujaratiC_GIH +25% Jatt_Haryana @ 2.190094


    Using 4 populations approximation:
    1 Bengali_Bangladesh_BEB + GujaratiD_GIH + Jatt_Haryana + Punjabi_Gujjar @ 1.898012
    2 Tajik_Pomiri_Ishkashim + Vaish + Velama + Velama @ 2.020669
    3 Brahmin_Tamil + Kanjar + Tajik_Pomiri_Ishkashim + Velama @ 2.075948
    4 Lambadi + Tajik_Pomiri_Ishkashim + TN_Brahmin + Velama @ 2.086072
    5 Tajik_Pomiri_Ishkashim + Vaish + Velama + Velamas @ 2.092729
    6 Brahmin_Tamil + Tajik_Pomiri_Ishkashim + TN_Brahmin + Vysya @ 2.102603
    Last edited by Varun R; 09-13-2014 at 07:29 PM.

  18. The Following 5 Users Say Thank You to Varun R For This Useful Post:

     Dimanto (09-14-2014),  NK19191 (09-13-2014),  Rukha (09-13-2014),  Scarlet Ibis (09-14-2014),  Táltos (09-14-2014)

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