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Thread: Post HarappaWorld results

  1. #2001
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    HarappaWorld Oracle results:
    23 April 2013 - Oracle reference population percentages revised.

    Kit Z236183 for DA125 Steppe YDNA=https://yfull.com/tree/T-Y13279/ (Found in IRAQ)

    Admix Results (sorted):

    # Population Percent
    1 NE-Euro 32.85
    2 Baloch 23.22
    3 Caucasian 15.37
    4 Mediterranean 9.13
    5 Siberian 7.49
    6 W-African 6.13
    7 S-Indian 3.03
    8 American 1.88
    9 SE-Asian 0.56
    10 Papuan 0.34

    Single Population Sharing:

    # Population (source) Distance
    1 tajik (yunusbayev) 21.08
    2 romanian-a (behar) 24.87
    3 chuvash (behar) 25.03
    4 bulgarian (yunusbayev) 26.23
    5 hungarian (behar) 26.93
    6 stalskoe (xing) 26.96
    7 nogai (yunusbayev) 27.37
    8 turkmen (yunusbayev) 27.61
    9 slovenian (xing) 27.64
    10 uzbek (behar) 29.11
    11 urkarah (xing) 29.14
    12 pashtun (harappa) 29.34
    13 romanian-b (behar) 30.15
    14 mordovian (yunusbayev) 30.22
    15 ukranian (yunusbayev) 30.42
    16 turk-aydin (hodoglugil) 30.69
    17 haryana-jatt (harappa) 30.74
    18 n-european (xing) 32.05
    19 french (hgdp) 32.16
    20 utahn-white (1000genomes) 32.54

    Mixed Mode Population Sharing:

    # Primary Population (source) Secondary Population (source) Distance
    1 60.1% tajik (yunusbayev) + 39.9% mordovian (yunusbayev) @ 8.54
    2 62.9% tajik (yunusbayev) + 37.1% russian (hgdp) @ 8.67
    3 60.4% tajik (yunusbayev) + 39.6% ukranian (yunusbayev) @ 9
    4 64.1% tajik (yunusbayev) + 35.9% belorussian (behar) @ 9.05
    5 67.8% tajik (yunusbayev) + 32.2% lithuanian (behar) @ 9.1
    6 63.6% tajik (yunusbayev) + 36.4% russian (behar) @ 9.14
    7 58.1% tajik (yunusbayev) + 41.9% slovenian (xing) @ 9.83
    8 62.1% tajik (yunusbayev) + 37.9% n-european (xing) @ 9.92
    9 59.3% mordovian (yunusbayev) + 40.7% makrani (hgdp) @ 9.93
    10 57.4% tajik (yunusbayev) + 42.6% hungarian (behar) @ 10.04
    11 55.3% tajik (yunusbayev) + 44.7% chuvash (behar) @ 10.04
    12 62.7% tajik (yunusbayev) + 37.3% utahn-white (hapmap) @ 10.09
    13 55.8% russian (behar) + 44.2% makrani (hgdp) @ 10.11
    14 72.6% tajik (yunusbayev) + 27.4% finnish (1000genomes) @ 10.3
    15 64.2% tajik (yunusbayev) + 35.8% orcadian (hgdp) @ 10.42
    16 62.8% tajik (yunusbayev) + 37.2% utahn-white (1000genomes) @ 10.51
    17 59.2% ukranian (yunusbayev) + 40.8% makrani (hgdp) @ 10.56
    18 64.6% chuvash (behar) + 35.4% makrani (hgdp) @ 10.63
    19 63.7% tajik (yunusbayev) + 36.3% british (1000genomes) @ 10.66
    20 59.2% mordovian (yunusbayev) + 40.8% balochi (hgdp) @ 10.7




    Kit Num: Z236183
    Threshold of components set to 1.000
    Threshold of method set to 0.25%
    Personal data has been read. 20 approximations mode.
    Gedmatch.Com
    HarappaWorld 4-Ancestors Oracle
    This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
    Questions about results should be sent to him at: [email protected]
    Original concept proposed by Sergey Kozlov.
    Many thanks to Alexandr for helping us get this web version developed.

    23 April 2013 - Oracle reference population percentages revised.

    Admix Results (sorted):

    # Population Percent
    1 NE-Euro 32.85
    2 Baloch 23.22
    3 Caucasian 15.37
    4 Mediterranean 9.13
    5 Siberian 7.49
    6 W-African 6.13
    7 S-Indian 3.03
    8 American 1.88


    Finished reading population data. 377 populations found.
    16 components mode.

    --------------------------------

    Least-squares method.

    Using 1 population approximation:
    1 tajik_yunusbayev @ 22.917536
    2 serbian_harappa @ 25.819839
    3 romanian-a_behar @ 26.908543
    4 chuvash_behar @ 27.145718
    5 bulgarian_yunusbayev @ 28.475445
    6 hungarian_behar @ 29.131565
    7 stalskoe_xing @ 29.891619
    8 slovenian_xing @ 29.973633
    9 nogai_yunusbayev @ 30.113710
    10 singapore-indian-d_sgvp @ 30.135750
    11 turkmen_yunusbayev @ 30.276859
    12 uzbek_behar @ 31.236523
    13 pashtun_harappa @ 32.059105
    14 urkarah_xing @ 32.260036
    15 romanian-b_behar @ 33.017643
    16 mordovian_yunusbayev @ 33.167374
    17 ukranian_yunusbayev @ 33.233849
    18 haryana-jatt_harappa @ 33.677639
    19 turk-aydin_hodoglugil @ 33.897556
    20 french_hgdp @ 34.484917

    Using 2 populations approximation:
    1 50% mordovian_yunusbayev +50% tajik_yunusbayev @ 10.249477


    Using 3 populations approximation:
    1 50% chuvash_behar +25% makrani_hgdp +25% romanian-a_behar @ 8.912832


    Using 4 populations approximation:
    ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++
    1 chuvash_behar + makrani_hgdp + orcadian_hgdp + stalskoe_xing @ 7.598769
    2 chuvash_behar + makrani_hgdp + n-european_xing + stalskoe_xing @ 7.613980
    3 chuvash_behar + makrani_hgdp + stalskoe_xing + utahn-white_hapmap @ 7.618148
    4 chuvash_behar + makrani_hgdp + orcadian_hgdp + urkarah_xing @ 7.619779
    5 chuvash_behar + makrani_hgdp + n-european_xing + urkarah_xing @ 7.678563
    6 chuvash_behar + makrani_hgdp + urkarah_xing + utahn-white_hapmap @ 7.681743
    7 chuvash_behar + kalash_hgdp + orcadian_hgdp + stalskoe_xing @ 7.703360
    8 balochi_hgdp + chuvash_behar + n-european_xing + stalskoe_xing @ 7.706440
    9 balochi_hgdp + chuvash_behar + stalskoe_xing + utahn-white_hapmap @ 7.729976
    10 british_1000genomes + chuvash_behar + makrani_hgdp + urkarah_xing @ 7.754705
    11 balochi_hgdp + chuvash_behar + orcadian_hgdp + stalskoe_xing @ 7.760089
    12 chuvash_behar + makrani_hgdp + nogai_yunusbayev + orcadian_hgdp @ 7.797308
    13 chuvash_behar + makrani_hgdp + urkarah_xing + utahn-white_1000genomes @ 7.806115
    14 balochi_hgdp + chuvash_behar + n-european_xing + urkarah_xing @ 7.811163
    15 british_1000genomes + chuvash_behar + makrani_hgdp + stalskoe_xing @ 7.811876
    16 balochi_hgdp + chuvash_behar + orcadian_hgdp + urkarah_xing @ 7.825466
    17 chuvash_behar + makrani_hgdp + stalskoe_xing + utahn-white_1000genomes @ 7.831983
    18 balochi_hgdp + chuvash_behar + urkarah_xing + utahn-white_hapmap @ 7.832841
    19 chuvash_behar + makrani_hgdp + russian_hgdp + stalskoe_xing @ 7.840527
    20 chuvash_behar + kalash_hgdp + orcadian_hgdp + urkarah_xing @ 7.857426

    I am only person matching Both the lactose persistence genes that this DA125 genome matches in the 1000 genomes DB

    rs4988243 2 136607703 Found in Korea, ITU, BEB, GIH, qatar, MiddleEast, finn, jewish, amerind/latinos (ITU=34%, GIH=32.8%)
    rs2236783 2 136594158 Found in Europe and among Amerind/Latinos (ITU=11.27% GIH=12.25%)
    Y: H-M69 -> H-M82 -> SK1225 -> H-Z5888 -> H-Z5890 -> H-CTS8144 [CTS8144/PF1741/M5498] -> Z34531 (H1a1a4b3b1a8~)
    found 2875 BCE -> Jiroft/IVC Periphery 11459 Shahr-i-Sokte BA2
    mtDNA:U2a1a

    G25 Ancients Dist 0.79 IND_Roopkund_A 51.05 IRN_Shahr_I_Sokhta_BA2 46.64 MAR_Iberomaurusian2.04PAK_Katelai_IA0.19 TKM_Gonur2_BA 0.08

    Lactose Persistence rs3213871 rs4988243 rs4988183 rs3769005 rs2236783
    found -> DA125, Kangju

  2. #2002
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    Quote Originally Posted by clocknative View Post
    That is so annoying that these companies do that, thats why a lot of SA's get weird results.They should be estimating from DNA not relatives lol. Do you think they will change this in the future?
    Not true they're probably not doing it using that method. Its just that they probably threw in all the samples from the area into the category which caused even southern shifted individuals to get such results.
    There is no shame in not knowing; the shame lies in not finding out-Russian proverb

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  4. #2003
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    Punjabi Khatri/J&K/Multan
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    U2b

    India United States of America India Punjab Jammu and Kashmir
    Quote Originally Posted by Censored View Post
    Not true they're probably not doing it using that method. Its just that they probably threw in all the samples from the area into the category which caused even southern shifted individuals to get such results.
    If you and others from your area claim to be from that area that is enough. They don't care much about ancient samples. If a bunch of Southern Indians were living in Rajasthan for 2 centuries it would be enough to fool their algorithms. That guy from Reddit is embarrassed about his PJL or Chamar like background. Now think about a bunch of people that do not like the truth, an algorithm that looks at recent ancestry keeps most people happy.

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  6. #2004
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    Quote Originally Posted by agent_lime View Post
    If you and others from your area claim to be from that area that is enough. They don't care much about ancient samples. If a bunch of Southern Indians were living in Rajasthan for 2 centuries it would be enough to fool their algorithms. That guy from Reddit is embarrassed about his PJL or Chamar like background. Now think about a bunch of people that do not like the truth, an algorithm that looks at recent ancestry keeps most people happy.
    What are you basing this on?
    There is no shame in not knowing; the shame lies in not finding out-Russian proverb

  7. #2005
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    LOL that person claims to be khatri wtf
    Quote Originally Posted by Censored View Post
    What are you basing this on?
    Read the Reddit post. They lie about their oracles. Something that would get you banned here.

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  9. #2006
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    Quote Originally Posted by agent_lime View Post
    Read the Reddit post. They lie about their oracles. Something that would get you banned here.
    He's probably a novice who doesn't understand how it works and saw a mixed oracle.
    There is no shame in not knowing; the shame lies in not finding out-Russian proverb

  10. #2007
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    Quote Originally Posted by Censored View Post
    He's probably a novice who doesn't understand how it works and saw a mixed oracle.
    from what i can remember nowhere in the oracle did it say khatri, which doesn't make sense when that reddit user mentioned it.

  11. #2008
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    U2b

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    Quote Originally Posted by Censored View Post
    He's probably a novice who doesn't understand how it works and saw a mixed oracle.
    Code:
    Admix Results (sorted):
    
    #	Population	Percent
    1 	S-Indian 	41.02
    2 	Baloch 	35.43
    3 	Caucasian 	9.71
    4 	NE-Euro 	7.79
    5 	Siberian 	2.94
    6 	SW-Asian 	1.51
    7 	American 	1.15
    8 	Beringian 	0.42
    9 	NE-Asian 	0.03
    
    Single Population Sharing:
    
    #	Population (source)	Distance
    1 	bihari-muslim (harappa) 	5.4
    2 	up-brahmin (harappa) 	6.14
    3 	bengali-brahmin (harappa) 	6.56
    4 	brahmin-uttar-pradesh (metspalu) 	6.62
    5 	meghawal (reich) 	6.79
    6 	maharashtrian (harappa) 	6.89
    7 	up-muslim (harappa) 	7
    8 	karnataka-brahmin (harappa) 	7.01
    9 	gujarati-b (hapmap) 	7.03
    10 	up-kshatriya (metspalu) 	7.11
    11 	vaish (reich) 	7.16
    12 	brahmin-tamil-nadu (metspalu) 	7.62
    13 	tn-brahmin (xing) 	7.85
    14 	gujarati (harappa) 	7.99
    15 	iyer-brahmin (harappa) 	8.54
    16 	rajasthani (harappa) 	8.57
    17 	punjabi (harappa) 	8.6
    18 	iyengar-brahmin (harappa) 	8.61
    19 	punjabi-brahmin (harappa) 	8.71
    20 	punjabi-ramgarhia (harappa) 	8.72
    
    Mixed Mode Population Sharing:
    
    #	 	Primary Population (source) 	Secondary Population (source) 	Distance
    1	  	59.6%	pathan (hgdp) 	+ 	40.4%	chamar (metspalu) 	@ 	2.3
    2	  	64.6%	pathan (hgdp) 	+ 	35.4%	tn-dalit (xing) 	@ 	2.31
    3	  	79.1%	kashmiri-pandit (reich) 	+ 	20.9%	mala (reich) 	@ 	2.34
    4	  	65%	pathan (hgdp) 	+ 	35%	mala (reich) 	@ 	2.36
    5	  	78.8%	kashmiri-pandit (reich) 	+ 	21.2%	tn-dalit (xing) 	@ 	2.4
    6	  	90.1%	meghawal (reich) 	+ 	9.9%	balkar (yunusbayev) 	@ 	2.43
    7	  	89.6%	meghawal (reich) 	+ 	10.4%	chechen (yunusbayev) 	@ 	2.43
    8	  	89.2%	meghawal (reich) 	+ 	10.8%	kumyk (yunusbayev) 	@ 	2.44
    9	  	90.2%	meghawal (reich) 	+ 	9.8%	north-ossetian (yunusbayev) 	@ 	2.45
    10	  	62.6%	pathan (hgdp) 	+ 	37.4%	madiga (reich) 	@ 	2.45
    11	  	90.2%	meghawal (reich) 	+ 	9.8%	adygei (hgdp) 	@ 	2.45
    12	  	56.6%	srivastava (reich) 	+ 	43.4%	sindhi (harappa) 	@ 	2.48
    13	  	60.6%	pathan (hgdp) 	+ 	39.4%	bhil (reich) 	@ 	2.48
    14	  	75.8%	kashmiri-pandit (reich) 	+ 	24.2%	bhil (reich) 	@ 	2.49
    15	  	77.8%	kashmiri-pandit (reich) 	+ 	22.2%	hakkipikki (metspalu) 	@ 	2.49
    16	  	77.2%	kashmiri-pandit (reich) 	+ 	22.8%	ap-madiga (xing) 	@ 	2.52
    17	  	62.4%	pathan (hgdp) 	+ 	37.6%	ap-madiga (xing) 	@ 	2.54
    18	  	86.2%	iyengar-brahmin (harappa) 	+ 	13.8%	lezgin (behar) 	@ 	2.55
    19	  	76.2%	kashmiri-pandit (reich) 	+ 	23.8%	tamil-vishwakarma (harappa) 	@ 	2.55
    20	  	58.8%	pathan (hgdp) 	+ 	41.2%	kamsali (reich) 	@ 	2.55

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  13. #2009
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    Quote Originally Posted by Censored View Post
    Not true they're probably not doing it using that method. Its just that they probably threw in all the samples from the area into the category which caused even southern shifted individuals to get such results.
    you have to look at the facts, that punjabi persons results from reddit showed typical results for a punjabi biradiri but their harappaworld results were a lot different and showed a more AASI shift compared to punjabi biradiri results. Their Southern South India was low compared to harappaworld results and probably is a possibility not an actual fact, if you are not sure no point stating probables.
    Last edited by clocknative; 01-24-2020 at 02:33 PM.

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  15. #2010
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    Punjabi Sikh Ramgarhia
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    Canadian
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    R1a-Y7 > Y2568*
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    M3a2
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    U2b2

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    Quote Originally Posted by agent_lime View Post
    Code:
    Admix Results (sorted):
    
    #	Population	Percent
    1 	S-Indian 	41.02
    2 	Baloch 	35.43
    3 	Caucasian 	9.71
    4 	NE-Euro 	7.79
    5 	Siberian 	2.94
    6 	SW-Asian 	1.51
    7 	American 	1.15
    8 	Beringian 	0.42
    9 	NE-Asian 	0.03
    
    Single Population Sharing:
    
    #	Population (source)	Distance
    1 	bihari-muslim (harappa) 	5.4
    2 	up-brahmin (harappa) 	6.14
    3 	bengali-brahmin (harappa) 	6.56
    4 	brahmin-uttar-pradesh (metspalu) 	6.62
    5 	meghawal (reich) 	6.79
    6 	maharashtrian (harappa) 	6.89
    7 	up-muslim (harappa) 	7
    8 	karnataka-brahmin (harappa) 	7.01
    9 	gujarati-b (hapmap) 	7.03
    10 	up-kshatriya (metspalu) 	7.11
    11 	vaish (reich) 	7.16
    12 	brahmin-tamil-nadu (metspalu) 	7.62
    13 	tn-brahmin (xing) 	7.85
    14 	gujarati (harappa) 	7.99
    15 	iyer-brahmin (harappa) 	8.54
    16 	rajasthani (harappa) 	8.57
    17 	punjabi (harappa) 	8.6
    18 	iyengar-brahmin (harappa) 	8.61
    19 	punjabi-brahmin (harappa) 	8.71
    20 	punjabi-ramgarhia (harappa) 	8.72
    
    Mixed Mode Population Sharing:
    
    #	 	Primary Population (source) 	Secondary Population (source) 	Distance
    1	  	59.6%	pathan (hgdp) 	+ 	40.4%	chamar (metspalu) 	@ 	2.3
    2	  	64.6%	pathan (hgdp) 	+ 	35.4%	tn-dalit (xing) 	@ 	2.31
    3	  	79.1%	kashmiri-pandit (reich) 	+ 	20.9%	mala (reich) 	@ 	2.34
    4	  	65%	pathan (hgdp) 	+ 	35%	mala (reich) 	@ 	2.36
    5	  	78.8%	kashmiri-pandit (reich) 	+ 	21.2%	tn-dalit (xing) 	@ 	2.4
    6	  	90.1%	meghawal (reich) 	+ 	9.9%	balkar (yunusbayev) 	@ 	2.43
    7	  	89.6%	meghawal (reich) 	+ 	10.4%	chechen (yunusbayev) 	@ 	2.43
    8	  	89.2%	meghawal (reich) 	+ 	10.8%	kumyk (yunusbayev) 	@ 	2.44
    9	  	90.2%	meghawal (reich) 	+ 	9.8%	north-ossetian (yunusbayev) 	@ 	2.45
    10	  	62.6%	pathan (hgdp) 	+ 	37.4%	madiga (reich) 	@ 	2.45
    11	  	90.2%	meghawal (reich) 	+ 	9.8%	adygei (hgdp) 	@ 	2.45
    12	  	56.6%	srivastava (reich) 	+ 	43.4%	sindhi (harappa) 	@ 	2.48
    13	  	60.6%	pathan (hgdp) 	+ 	39.4%	bhil (reich) 	@ 	2.48
    14	  	75.8%	kashmiri-pandit (reich) 	+ 	24.2%	bhil (reich) 	@ 	2.49
    15	  	77.8%	kashmiri-pandit (reich) 	+ 	22.2%	hakkipikki (metspalu) 	@ 	2.49
    16	  	77.2%	kashmiri-pandit (reich) 	+ 	22.8%	ap-madiga (xing) 	@ 	2.52
    17	  	62.4%	pathan (hgdp) 	+ 	37.6%	ap-madiga (xing) 	@ 	2.54
    18	  	86.2%	iyengar-brahmin (harappa) 	+ 	13.8%	lezgin (behar) 	@ 	2.55
    19	  	76.2%	kashmiri-pandit (reich) 	+ 	23.8%	tamil-vishwakarma (harappa) 	@ 	2.55
    20	  	58.8%	pathan (hgdp) 	+ 	41.2%	kamsali (reich) 	@ 	2.55
    It was sad when he kept saying punjabi Khatri again and again. I have Punjabi chamar sample with exact same results.
    Deg Teg Fateh - Victory to Charity and Arms

    Punjab, Punjabi, Fateh.

    Paternal Haplogroup: R1a1a Y7>Y2568*

    Maternal Haplogroup: M3a2

    Father's Maternal Haplogroup: U2b2

    Mother's Paternal Haplogroup (most likely): L1a2

    Paternal Grandmother Haplogroup: J-CTS5368

  16. The Following 2 Users Say Thank You to MonkeyDLuffy For This Useful Post:

     clocknative (01-24-2020),  Sapporo (01-29-2020)

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