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william0509 william0509 - 人文地理愛(ài)好者 祖源分析

Eurogene K13常染排序

最近為一些網(wǎng)友做了Eurogene K13常染排序, 里邊的“東亞”的標(biāo)桿是傣族, 而西伯利亞的標(biāo)桿則是鄂文斯族。歡迎各地網(wǎng)友加入統(tǒng)計(jì)。
Eurogene_K13東亞類傣族降序.JPG Eurogene_K13西伯利亞類鄂文斯族降序.JPG
2017-05-12 ? IP屬地美國(guó)
按熱門排序    按默認(rèn)排序

23 個(gè)回復(fù)

樓主的一個(gè)地方需要糾正,傣族樣本的結(jié)果只代表更接近標(biāo)桿,還無(wú)法完全說(shuō)明就是標(biāo)桿。圖中的是王傳超教授的383個(gè)東亞現(xiàn)代人樣本里面的其中一個(gè)毛南族K13結(jié)果,東亞94%以上,比傣族更接近Eurogenes K13東亞(南東亞)標(biāo)桿。
QQ截圖20211222204854.png

由于缺少Nganassan人的原始數(shù)據(jù),所以暫時(shí)還沒(méi)法驗(yàn)證他們?cè)贙13的西伯利亞結(jié)果是否比埃文人和鄂溫克族更高,雖然他們?cè)谄渌?jì)算器里有數(shù)值最高的西伯利亞成分。
Population
North_Atlantic 1.71
Baltic -
West_Med 0.17
West_Asian 0.13
East_Med 1.76
Red_Sea -
South_Asian 15.52
East_Asian 51.60
Siberian 26.28
Amerindian 0.45
Oceanian 1.76
Northeast_African -
Sub-Saharan 0.59
\小阮子/ - 酒不好喝
整天發(fā)這種破東西!一兩個(gè)人能代表緯度什么的,感覺(jué)地域色彩很強(qiáng),不知道想表達(dá)些什么?!
tengke131 - hi
1 Siberian 45.02
2 East_Asian 41.55
3 Baltic 4.03
4 West_Asian 3.2
5 Amerindian 2.17
6 East_Med 2.12
7 Red_Sea 1.45
8 Oceanian 0.41
9 South_Asian 0.07
EK13.png

?
tsaiyutung - 。。。。
可以看出,我的成分在漢族里面是很高的。
?Eurogenes K13 Admixture Proportions
Wegene老用戶,在這個(gè)算法下沒(méi)有非洲成分。
#Population Percent
East_Asian 71.282
Siberian 26.753
Red_Sea 1.29
East_med 0.68
K13 Oracle
East_Asian 70.45
Siberian 26.54
West_Asian 2.51
Amerindian 0.5
威廉兄,這得注明了,gm和wg的k13差異很大啊!不能放一起比較了。
Population
North_Atlantic 0.06
Baltic -
West_Med 0.51
West_Asian -
East_Med -
Red_Sea 0.26
South_Asian -
East_Asian 70.81
Siberian 28.24
Amerindian -
Oceanian -
Northeast_African 0.13
Sub-Saharan -
威廉兄,這是我上gedmatch運(yùn)算出來(lái)的,有差異啊……
Eurogenes K13 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.

K13 Oracle ref data revised 21 Nov 2013

Admix Results (sorted):

# Population Percent
1 East_Asian 70.81
2 Siberian 28.24


Finished reading population data. 204 populations found.
13 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Naxi @ 4.702106
2 Yizu @ 5.815392
3 Japanese @ 6.111642
4 Tu @ 9.614325
5 Tujia @ 15.173395
6 Miaozu @ 17.989491
7 Xibo @ 19.003914
8 She @ 19.759180
9 Hezhen @ 20.369545
10 Lahu @ 21.996555
11 Tibeto-Burman_Burmese @ 25.639519
12 Vietnamese @ 28.366165
13 Cambodian @ 31.890591
14 Malay @ 33.278725
15 Dai @ 33.351139
16 Mongolian @ 45.657612
17 Kirgiz @ 50.259434
18 Kazakh @ 52.570118
19 Uygur @ 53.475315
20 Buryat @ 53.923840

Using 2 populations approximation:
1 50% Hezhen +50% She @ 1.466205


Using 3 populations approximation:
1 50% Japanese +25% Japanese +25% She @ 1.344311


Using 4 populations approximation:
++++++++++++++++++++++++++++
1 Oroqen + She + She + She @ 0.886430
2 Miaozu + Oroqen + She + She @ 1.324261
3 Japanese + Japanese + Japanese + She @ 1.344311
4 Hezhen + Hezhen + She + She @ 1.466205
5 Japanese + Japanese + Japanese + Tujia @ 1.509357
6 Japanese + Japanese + Japanese + Miaozu @ 1.581743
7 Hezhen + She + She + Xibo @ 1.632727
8 Oroqen + She + She + Tujia @ 1.666492
9 Hezhen + Japanese + Tujia + Tujia @ 1.740213
10 Miaozu + Miaozu + Oroqen + She @ 1.866019
11 Hezhen + Hezhen + Miaozu + She @ 1.899620
12 Hezhen + Miaozu + She + Xibo @ 1.957370
13 Hezhen + She + Tujia + Xibo @ 1.985816
14 She + She + Xibo + Xibo @ 1.998033
15 Hezhen + Hezhen + She + Tujia @ 2.066628
16 She + Tujia + Xibo + Xibo @ 2.094833
17 Japanese + Tujia + Tujia + Xibo @ 2.104618
18 Miaozu + Oroqen + She + Tujia @ 2.226981
19 Miaozu + She + Xibo + Xibo @ 2.230605
20 Japanese + Japanese + Naxi + Tujia @ 2.249621
就我個(gè)人結(jié)果而言,微機(jī)因和蓋麥哧計(jì)算的主成份差不多,北族成份幾乎一致,北漢成份倒是難對(duì)應(yīng)上。
布魯斯 - 好奇害死貓
以東亞80為界線,以上南方人,以下北方人。
Admix Results (sorted):

# Population Percent
1 East_Asian 82.28
2 Siberian 16.2
3 Oceanian 0.56
4 Red_Sea 0.52
5 Amerindian 0.22
6 Northeast_African 0.19
7 Sub-Saharan 0.02
bunnyfz - O1a1b
North_Atlantic -
Baltic -
West_Med -
West_Asian -
East_Med -
Red_Sea -
South_Asian -
East_Asian 78.94
Siberian 20.66
Amerindian -
Oceanian -
Northeast_African 0.06
Sub-Saharan 0.34
?
同一份樣本,洋大人網(wǎng)站的結(jié)果
bunnyfz - O1a1b
福建福州,微基因結(jié)果

西伯利亞: 18.1%
美國(guó)印第安人: 0.001%
西非: 0.001%
古非洲: 0.275%
西南亞: 0.001%
東亞: 81%
地中海: 0.001%
澳大利亞: 0.001%
北極: 0.239%
西亞: 0.428%
北歐: 0.001%
南亞: 0.001%
東非: 0.001%
我爸:襄陽(yáng)+上虞
1 East_Asian 76.81
2?Siberian ? 21.67
我:+興化+泰州
1 East_Asian 76.49
2 Siberian 21.5
3 West_Med 1.1
4 Amerindian 0.9
bunnyfz - O1a1b
為毛我兒子樣本在英文網(wǎng)站看到的20.66,微基因得只有18.1,難道是不一樣的?
william0509 - 人文地理愛(ài)好者
已更新。
safin - MtDNA-D2
# Population Percent
1 East_Asian 79.04
2 Siberian 17.9
3 Red_Sea 1.6
4 Amerindian 0.65
5 Oceanian 0.5
6 Northeast_African 0.28
7 West_Asian 0.02
Single Population Sharing:

# Population (source) Distance
1 Tujia 2.76
2 Miaozu 5.16
3 She
?
也不知道老用戶的數(shù)據(jù)什么時(shí)候能優(yōu)化
是這個(gè)嗎?這是我的結(jié)果:
?Eurogenes K13 4-Ancestors OracleThis 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.

K13 Oracle ref data revised 21 Nov 2013

Admix Results (sorted):

# Population Percent
1 East_Asian 84.97
2 Siberian 13.46

Finished reading population data. 204 populations found.
13 components mode.

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

Least-squares method.

Using 1 population approximation:
1 She @ 0.904933
2 Miaozu @ 3.006994
3 Tujia @ 5.380903
4 Lahu @ 7.071651
5 Vietnamese @ 9.911296
6 Dai @ 13.735746
7 Yizu @ 18.196348
8 Naxi @ 19.886772
9 Cambodian @ 21.270185
10 Malay @ 24.738157
11 Japanese @ 26.403515
12 Tu @ 28.024103
13 Tibeto-Burman_Burmese @ 30.525105
14 Xibo @ 39.260242
15 Hezhen @ 40.729614
16 Mongolian @ 64.938301
17 Uygur @ 65.912994
18 Kirgiz @ 67.260010
19 Kazakh @ 69.036385
20 Hazara @ 70.334961

Using 2 populations approximation:
1 50% She +50% She @ 0.904933


Using 3 populations approximation:
1 50% She +25% She +25% She @ 0.904933


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++
1 She + She + She + She @ 0.904933
2 Miaozu + She + She + She @ 1.304532
3 Miaozu + Miaozu + She + She @ 1.856705
4 Dai + She + Tujia + Tujia @ 1.862257
5 Lahu + She + She + She @ 1.902364
6 She + She + She + Tujia @ 1.942265
7 She + She + Tujia + Vietnamese @ 1.961243
8 Dai + Tujia + Tujia + Tujia @ 2.153396
9 Dai + Miaozu + Tujia + Tujia @ 2.190764
10 Dai + She + She + Tujia @ 2.216127
11 She + She + She + Vietnamese @ 2.239499
12 Dai + Miaozu + She + Tujia @ 2.261253
13 Miaozu + She + She + Vietnamese @ 2.285641
14 Miaozu + She + Tujia + Vietnamese @ 2.298950
15 She + Tujia + Tujia + Vietnamese @ 2.317131
16 Lahu + Miaozu + She + She @ 2.359868
17 Miaozu + Miaozu + Miaozu + She @ 2.429257
18 Dai + Miaozu + Miaozu + Tujia @ 2.440971
19 Miaozu + She + She + Tujia @ 2.441945
20 Miaozu + Miaozu + She + Vietnamese @ 2.486557

Done.
紫蔻 - 人類一思考,上帝就發(fā)笑
積極參與,圖片的數(shù)據(jù)主人:zikoupa,籍貫:湖北襄陽(yáng)
最接近的前三依次是彝族、納西、日本,說(shuō)明他們的樣本庫(kù)有問(wèn)題
?
wang - 哈佛醫(yī)學(xué)院、德國(guó)馬普所分子人類學(xué)博士后
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