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william0509 william0509 - 人文地理愛好者 祖源分析

Gedmatch MDLP World 常染色體的結(jié)果

自己的World 常染色體結(jié)果與大家分享一下。感覺每一個(gè)計(jì)算器出來的結(jié)果對應(yīng)的人群都有區(qū)別。希望大家也可以做個(gè)對比。
World_Admixture2.JPG My_World_admixture1.JPG My_World_Admixture.JPG World_Admixture常染色體表.JPG
2016-07-16 ? IP屬地美國
按熱門排序    按默認(rèn)排序

24 個(gè)回復(fù)

wang - 哈佛醫(yī)學(xué)院、德國馬普所分子人類學(xué)博士后
取決于參考人群的選擇
xiaoyuvax - We are but codes
每個(gè)人就是一本巨量文字的書,只是很少的文字有差別,但還是可以進(jìn)行大數(shù)據(jù)分析的。
MDLP-WORLD.png

?
anderson675 - 天啦嚕
Admix Results (sorted):

#?? ?Population?? ?Percent
1 ?? ?East_Asian ?? ?86.67
2 ?? ?North_Asian ?? ?7.35
3 ?? ?South_and_West_European ?? ?1.49
4 ?? ?Arctic_Amerind ?? ?1.19
5 ?? ?Caucaus_Parsia ?? ?1.01


Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Naxi @ 3.875278
2 Yizu @ 4.642924
3 Han-Beijing @ 6.307268
4 Indian-East @ 6.341590
5 Han @ 8.113599
6 Japanese @ 8.114583
7 Tu @ 10.339836
8 Tujia @ 10.739298
9 Chinese-South @ 12.298640
10 Dai @ 13.175763
11 Lahu @ 13.183367
12 Miaozu @ 14.321996
13 She @ 14.904116
14 Khmer @ 17.554035
15 Indian_East @ 17.717155
16 Xibo @ 21.709564
17 Buma @ 22.380676
18 Mongola @ 30.491014
19 Daur @ 35.022030
20 Hezhen @ 35.141853

Using 2 populations approximation:
1 50% Tu +50% Tujia @ 2.214031


Using 3 populations approximation:
1 50% Tu +25% Han +25% Chinese-South @ 2.182795


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++
1 Lahu + Tu + Tu + Han @ 2.125771
2 Dai + Tu + Tu + Han @ 2.145180
3 Tu + Tu + Han + Chinese-South @ 2.182795
4 Tu + Tu + Han + Miaozu @ 2.182801
5 Lahu + Tu + Tu + Han-Beijing @ 2.191858
6 Tu + Tu + Han-Beijing + She @ 2.202248
7 Tu + Tu + Yizu + She @ 2.205316
8 Tu + Tu + Han-Beijing + Miaozu @ 2.207904
9 Dai + Tu + Tu + Han-Beijing @ 2.212484
10 Tu + Tu + Tujia + Tujia @ 2.214031
11 Tu + Tu + Han + She @ 2.217184
12 Lahu + Xibo + Tu + She @ 2.224907
13 Tu + Tu + Tujia + Chinese-South @ 2.229834
14 Lahu + Tu + Tu + Tujia @ 2.233624
15 Dai + Xibo + Tu + She @ 2.240576
16 Tu + Tu + Yizu + Miaozu @ 2.248847
17 Dai + Tu + Tu + Tujia @ 2.249811
18 Tu + Tu + Naxi + She @ 2.276966
19 Xibo + Tu + She + She @ 2.278899
20 Tu + Tu + Han + Tujia @ 2.284968

Done.
# ? Primary Population (source) Secondary Population (source) Distance
1 ? 86.5% Han + 13.5% Yukagir @ 1.66
2 ? 83% Han-Beijing + 17% Nivhi @ 1.85
3 ? 84.3% Tujia + 15.7% Yukagir @ 1.87
4 ? 88.6% Han-Beijing + 11.4% Yukagir @ 1.99
5 ? 80.3% Han + 19.7% Nivhi @ 2.07
tengke131 - hi
Admix Results (sorted):

# Population Percent
1 East_Asian 54.39
2 North_Asian 31.39
3 Caucaus_Parsia 4.91
4 North_and_East_European 4.39
5 Indian 2.05
6 Mesoamerican 1.07
7 Arctic_Amerind 1.05

Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Daur @ 11.217883
2 Mongol @ 11.539383
3 Mongola @ 11.784863
4 Hezhen @ 12.075744
5 Kalmyk @ 13.770287
6 Xibo @ 19.459421
7 Oroqen @ 21.495102
8 Kyrgyz @ 22.352797
9 Buryat @ 22.406982
10 Nivhi @ 25.654823
11 Tuva @ 25.971899
12 Altaic @ 29.138899
13 Kazakh @ 29.445772
14 Tu @ 30.617411
15 Uygur @ 33.430264
16 Karakalpak @ 33.826492
17 Indian_East @ 34.572300
18 Japanese @ 34.596020
19 Hakas @ 36.661667
20 Buma @ 37.182114

Using 2 populations approximation:
1 50% Tuva +50% Tu @ 3.168563


Using 3 populations approximation:
1 50% Tuva +25% Xibo +25% Indian_East @ 2.526473


Using 4 populations approximation:
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 Oroqen + Shor + Daur + Indian-East @ 1.703684
2 Oroqen + Shor + Hezhen + Indian-East @ 1.883983
3 Even + Shor + Indian-East + Tujia @ 2.030458
4 Even + Shor + Indian-East + Chinese-South @ 2.056814
5 Even + Shor + Indian-East + Han @ 2.124114
6 Oroqen + Shor + Mongola + Indian-East @ 2.162207
7 Dai + Even + Shor + Indian-East @ 2.189627
8 Even + Shor + Indian-East + Miaozu @ 2.189987
9 Lahu + Even + Shor + Indian-East @ 2.195616
10 Even + Shor + Indian-East + She @ 2.249596
11 Oroqen + Shor + Daur + Naxi @ 2.426283
12 Oroqen + Shor + Mongola + Japanese @ 2.479083
13 Dai + Even + Shor + Naxi @ 2.490507
14 Oroqen + Shor + Daur + Yizu @ 2.499054
15 Even + Shor + Han-Beijing + Indian-East @ 2.508698
16 Lahu + Even + Shor + Naxi @ 2.514628
17 Tuva + Altaic + Hezhen + Indian-East @ 2.519620
18 Tuva + Tuva + Xibo + Indian_East @ 2.526473
19 Even + Shor + Yizu + Han @ 2.559130
20 Tuva + Kalmyk + Hezhen + Indian_East @ 2.565771
lingsan - 我是生物 我是活物
有點(diǎn)的西北中亞民族血統(tǒng)?
william0509 - 人文地理愛好者
這里的東亞標(biāo)桿是測試者有多接近畬族。
xiaoyuvax - We are but codes
這有點(diǎn)像計(jì)算機(jī)科學(xué)中的文件版本比較
好純粹的東亞
這個(gè)常染說明什么?@wang
Admix Results (sorted):

# Population Percent
1 East_Asian 86.26
2 North_Asian 11.75

Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Japanese @ 3.928002
2 Naxi @ 5.137372
3 Yizu @ 6.288549
4 Han-Beijing @ 7.807037
5 Indian-East @ 8.189871
6 Tu @ 8.585198
7 Han @ 10.390596
8 Tujia @ 13.075595
9 Chinese-South @ 14.815032
10 Dai @ 16.193455
11 Lahu @ 16.204473
12 Miaozu @ 16.990820
13 She @ 17.568169
14 Indian_East @ 18.479399
15 Xibo @ 18.776203
16 Khmer @ 19.837954
17 Buma @ 23.390381
18 Mongola @ 27.344442
19 Daur @ 31.554127
20 Hezhen @ 31.594673

Using 2 populations approximation:
1 50% Japanese +50% Naxi @ 1.383810


Using 3 populations approximation:
1 50% Japanese +25% Tu +25% Tujia @ 1.014225


Using 4 populations approximation:
+++++++++++++++++++++++++++++++++++++++++++++++++++
1 Mongola + Japanese + Tujia + Miaozu @ 0.529328
2 Mongola + Japanese + Tujia + She @ 0.529328
3 Mongola + Japanese + Chinese-South + Miaozu @ 0.529328
4 Xibo + Japanese + Han-Beijing + Chinese-South @ 0.596820
5 Mongola + Japanese + Chinese-South + Chinese-South @ 0.600183
6 Mongola + Japanese + Chinese-South + She @ 0.609576
7 Mongola + Yizu + Han-Beijing + Tujia @ 0.625423
8 Mongola + Naxi + Han-Beijing + Chinese-South @ 0.632904
9 Mongola + Han-Beijing + Han-Beijing + Tujia @ 0.650218
10 Xibo + Japanese + Han-Beijing + Tujia @ 0.699835
11 Mongola + Han-Beijing + Han-Beijing + Han @ 0.702838
12 Daur + Han + Han + Han @ 0.709576
13 Mongola + Yizu + Han-Beijing + Chinese-South @ 0.747762
14 Daur + Yizu + Han + Chinese-South @ 0.748012
15 Xibo + Japanese + Han + Tujia @ 0.753191
16 Mongola + Naxi + Han-Beijing + Tujia @ 0.769320
17 Lahu + Daur + Han-Beijing + Han-Beijing @ 0.786165
18 Daur + Naxi + Han + Miaozu @ 0.792574
19 Daur + Naxi + Han + She @ 0.801721
20 Dai + Daur + Han-Beijing + Han-Beijing @ 0.805419
MDLP World 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.

Admix Results (sorted):

# Population Percent
1 East_Asian 92.86
2 North_Asian 6.03

Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Han-Beijing @ 1.332438
2 Han @ 1.757091
3 Yizu @ 2.882827
4 Naxi @ 4.135703
5 Tujia @ 4.377304
6 Chinese-South @ 6.087163
7 Lahu @ 7.574567
8 Dai @ 7.577645
9 Miaozu @ 8.254684
10 She @ 8.836677
11 Indian-East @ 8.861727
12 Japanese @ 12.495280
13 Tu @ 16.372877
14 Khmer @ 19.862423
15 Indian_East @ 22.343887
16 Buma @ 26.421247
17 Xibo @ 27.446014
18 Mongola @ 36.072075
19 Daur @ 40.281719
20 Hezhen @ 40.308205

Using 2 populations approximation:
1 50% Naxi +50% Tujia @ 0.480489


Using 3 populations approximation:
1 50% Naxi +25% Han-Beijing +25% Miaozu @ 0.403527


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++
1 Lahu + Japanese + Han-Beijing + Chinese-South @ 0.000000
2 Lahu + Japanese + Han + Tujia @ 0.000000
3 Dai + Japanese + Han-Beijing + Chinese-South @ 0.000000
4 Dai + Japanese + Han + Tujia @ 0.000000
5 Japanese + Yizu + Chinese-South + Miaozu @ 0.317587
6 Japanese + Yizu + Chinese-South + She @ 0.347837
7 Japanese + Naxi + Miaozu + Miaozu @ 0.379020
8 Japanese + Yizu + Miaozu + Miaozu @ 0.402237
9 Japanese + Naxi + Miaozu + She @ 0.402250
10 Naxi + Naxi + Han-Beijing + Miaozu @ 0.403527
11 Naxi + Naxi + Han + Chinese-South @ 0.403527
12 Naxi + Han-Beijing + Han-Beijing + Chinese-South @ 0.436587
13 Yizu + Han-Beijing + Han + Han @ 0.446588
14 Japanese + Han + Han + She @ 0.460336
15 Naxi + Han + Han + Han @ 0.471130
16 Naxi + Yizu + Han-Beijing + Miaozu @ 0.475186
17 Naxi + Yizu + Han + Tujia @ 0.479104
18 Naxi + Naxi + Han-Beijing + She @ 0.479812
19 Naxi + Naxi + Tujia + Tujia @ 0.480489
20 Dai + Japanese + Han-Beijing + Tujia @ 0.480985
?
我媽的MDLP World 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.

Admix Results (sorted):

# Population Percent
1 East_Asian 92.76
2 North_Asian 5.20

Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Han @ 1.587291
2 Han-Beijing @ 2.153147
3 Yizu @ 3.468164
4 Tujia @ 4.126021
5 Naxi @ 4.661023
6 Chinese-South @ 5.743306
7 Lahu @ 7.098085
8 Dai @ 7.105506
9 Miaozu @ 7.852849
10 She @ 8.440804
11 Indian-East @ 9.050411
12 Japanese @ 13.031852
13 Tu @ 16.603674
14 Khmer @ 19.757084
15 Indian_East @ 22.403452
16 Buma @ 26.460455
17 Xibo @ 27.805330
18 Mongola @ 36.497517
19 Daur @ 40.782127
20 Hezhen @ 40.823566

Using 2 populations approximation:
1 50% Naxi +50% Tujia @ 1.222931


Using 3 populations approximation:
1 50% Naxi +25% Han +25% Miaozu @ 1.043894


Using 4 populations approximation:
+++++++++++++++++++++++++++++++++++++++++++++++++++
1 Tu + Tujia + Tujia + Miaozu @ 0.883263
2 Tu + Tujia + Chinese-South + Chinese-South @ 0.883775
3 Tu + Tujia + Tujia + She @ 0.899134
4 Tu + Han-Beijing + She + She @ 0.915226
5 Tu + Chinese-South + Chinese-South + Chinese-South @ 0.923779
6 Tu + Tujia + Chinese-South + Miaozu @ 0.951827
7 Tu + Han-Beijing + Miaozu + She @ 0.961832
8 Lahu + Japanese + Han + Chinese-South @ 0.983166
9 Dai + Japanese + Han + Chinese-South @ 0.993006
10 Naxi + Han + Han + Han @ 1.009674
11 Xibo + She + She + She @ 1.011147
12 Tu + Han + Chinese-South + She @ 1.014786
13 Tu + Tujia + Chinese-South + She @ 1.028809
14 Lahu + Japanese + Han + Tujia @ 1.030989
15 Yizu + Han + Han + Han @ 1.034026
16 Tu + Han-Beijing + Miaozu + Miaozu @ 1.040097
17 Naxi + Naxi + Han + Miaozu @ 1.043894
18 Dai + Japanese + Han + Tujia @ 1.044335
19 Naxi + Naxi + Han + She @ 1.053641
20 Lahu + Japanese + Han-Beijing + Miaozu @ 1.070324
?
我爸的,果然更南
MDLP World 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.

Admix Results (sorted):

# Population Percent
1 East_Asian 93.64
2 North_Asian 3.85

Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Han @ 1.623089
2 Tujia @ 3.009002
3 Han-Beijing @ 3.654518
4 Chinese-South @ 4.402368
5 Yizu @ 4.814742
6 Lahu @ 5.406756
7 Dai @ 5.409063
8 Naxi @ 6.050895
9 Miaozu @ 6.406124
10 She @ 7.001539
11 Indian-East @ 9.622622
12 Japanese @ 14.609097
13 Tu @ 18.005180
14 Khmer @ 19.571127
15 Indian_East @ 22.926605
16 Buma @ 26.747023
17 Xibo @ 29.341808
18 Mongola @ 38.051678
19 Daur @ 42.358753
20 Hezhen @ 42.402771

Using 2 populations approximation:
1 50% Lahu +50% Yizu @ 1.061754


Using 3 populations approximation:
1 50% Lahu +25% Japanese +25% Chinese-South @ 0.832444


Using 4 populations approximation:
+++++++++++++++++++++++++++++++++++++++++++++++++++++
1 Lahu + Lahu + Japanese + Chinese-South @ 0.832444
2 Lahu + Dai + Japanese + Chinese-South @ 0.840075
3 Dai + Dai + Japanese + Chinese-South @ 0.848957
4 Lahu + Naxi + Naxi + Miaozu @ 0.869740
5 Dai + Tu + Miaozu + Miaozu @ 0.879543
6 Dai + Naxi + Naxi + Miaozu @ 0.888823
7 Lahu + Naxi + Yizu + Miaozu @ 0.891739
8 Dai + Yizu + Han + Han @ 0.895079
9 Lahu + Naxi + Naxi + She @ 0.896081
10 Lahu + Yizu + Han + Han @ 0.901356
11 Dai + Naxi + Yizu + Miaozu @ 0.905193
12 Lahu + Lahu + Lahu + Japanese @ 0.907917
13 Dai + Naxi + Naxi + She @ 0.911431
14 Lahu + Tu + Miaozu + Miaozu @ 0.918467
15 Dai + Tu + Miaozu + She @ 0.919600
16 Lahu + Tu + Miaozu + She @ 0.922875
17 Dai + Naxi + Han + Han @ 0.930114
18 Lahu + Lahu + Dai + Japanese @ 0.932146
19 Lahu + Naxi + Han + Han @ 0.932214
20 Lahu + Yizu + Yizu + Chinese-South @ 0.936043
柏貝勒 - Bi Manju niyalma inu
東北滿族
?Admix Results (sorted):

# Population Percent
1 East_Asian 85.42
2 North_Asian 11.79

Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Japanese @ 3.400607
2 Naxi @ 5.676271
3 Yizu @ 6.912380
4 Tu @ 7.711836
5 Indian-East @ 8.044635
6 Han-Beijing @ 8.578842
7 Han @ 11.086595
8 Tujia @ 13.802629
9 Chinese-South @ 15.523245
10 Dai @ 16.782103
11 Lahu @ 16.792765
12 Miaozu @ 17.688972
13 Indian_East @ 17.755722
14 Xibo @ 18.073689
15 She @ 18.268095
16 Khmer @ 19.462755
17 Buma @ 22.756683
18 Mongola @ 26.630926
19 Daur @ 30.919571
20 Hezhen @ 30.968674

Using 2 populations approximation:
1 50% Xibo +50% She @ 1.611572


Using 3 populations approximation:
1 50% Japanese +25% Tu +25% Han @ 0.632500


Using 4 populations approximation:
+++++++++++++++++++++++++++++++++++++++++++++++++++
1 Lahu + Mongola + Japanese + Tujia @ 0.435496
2 Dai + Mongola + Japanese + Tujia @ 0.459746
3 Mongola + Naxi + Han + Han @ 0.526997
4 Lahu + Mongola + Japanese + Han @ 0.587254
5 Dai + Mongola + Japanese + Han @ 0.611459
6 Mongola + Naxi + Naxi + Chinese-South @ 0.631069
7 Japanese + Japanese + Tu + Han @ 0.632500
8 Mongola + Japanese + Han + She @ 0.636445
9 Japanese + Japanese + Tu + Tujia @ 0.643408
10 Mongola + Japanese + Han + Miaozu @ 0.662239
11 Mongola + Naxi + Yizu + Chinese-South @ 0.662717
12 Mongola + Yizu + Han-Beijing + Han @ 0.663327
13 Hezhen + Tu + Miaozu + She @ 0.672426
14 Mongola + Naxi + Yizu + Tujia @ 0.673596
15 Hezhen + Tu + She + She @ 0.686626
16 Mongola + Yizu + Yizu + Tujia @ 0.708834
17 Mongola + Naxi + Han-Beijing + Han @ 0.720177
18 Mongola + Naxi + Han-Beijing + Tujia @ 0.739760
19 Lahu + Mongola + Japanese + Chinese-South @ 0.759329
20 Hezhen + Tu + Miaozu + Miaozu @ 0.760808

Done.
?
?
?Admix Results (sorted):

# Population Percent
1 East_Asian 91.49
2 North_Asian 5.95
3 Mesoamerican 1.37
4 South_and_West_European 1.02

Finished reading population data. 257 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Han-Beijing @ 2.248422
2 Yizu @ 2.692622
3 Han @ 3.239853
4 Naxi @ 3.714446
5 Tujia @ 5.735874
6 Chinese-South @ 7.338343
7 Indian-East @ 8.275607
8 Lahu @ 8.628464
9 Dai @ 8.632698
10 Miaozu @ 9.405438
11 She @ 10.002427
12 Japanese @ 11.719130
13 Tu @ 15.256307
14 Khmer @ 19.312702
15 Indian_East @ 21.463482
16 Buma @ 25.605345
17 Xibo @ 26.406408
18 Mongola @ 35.086258
19 Daur @ 39.370712
20 Hezhen @ 39.426918
?
?
?
驚奇,竟然分配到beijing的Han了,也不知道是不是樣本還是便南的緣故?
# Population Percent
1 East_Asian 79.75
2 North_Asian 12.79
3 Indian 3.26
4 Caucaus_Parsia 1.15
5 Arctic_Amerind 1
6 North_and_East_European 0.98
7 South_and_West_European 0.73
8 Melanesian 0.35
?
1 Tu 3.21
2 Japanese 5.24
3 Indian-East 9.1
4 Naxi 10.24
5 Yizu 11.4
6 Indian_East 11.89
7 Xibo 12.47
8 Han-Beijing 13.3
9 Han 15.46
?
1 ? 57.9% Indian-East + 42.1% Xibo @ 1.15
2 ? 94.5% Japanese + 5.5% Indian @ 1.45
3 ? 94.7% Japanese + 5.3% Jew_India @ 1.68
4 ? 69.7% Indian-East + 30.3% Mongola @ 1.71
5 ? 70.7% Japanese + 29.3% Indian_East @ 1.94
6 ? 89.6% Japanese + 10.4% Kusunda @ 2
7 ? 72.7% Dai + 27.3% Tuva @ 2.06
8 ? 72.7% Lahu + 27.3% Tuva @ 2.11
9 ? 94.9% Japanese + 5.1% Sindhi @ 2.12
10 ? 94.5% Japanese + 5.5% Burusho @ 2.17
11 ? 71.3% Dai + 28.7% Buryat @ 2.2
12 ? 94.8% Japanese + 5.2% Pathan @ 2.23
13 ? 94.7% Japanese + 5.3% Roma @ 2.25
14 ? 71.3% Lahu + 28.7% Buryat @ 2.25
15 ? 77.6% Japanese + 22.4% Buma @ 2.26
16 ? 73.9% Indian-East + 26.1% Daur @ 2.27
17 ? 80.6% Naxi + 19.4% Kalmyk @ 2.31
18 ? 79.1% Dai + 20.9% Dolgan @ 2.31
19 ? 84.4% Naxi + 15.6% Altaic @ 2.32
20 ? 79.1% Lahu + 20.9% Dolgan @ 2.33
SR4EVER -
5.25%印度??
SR4EVER -
5.25%印度??
anderson675 - 天啦嚕
更新跟上

WechatIMG237.jpeg

?
內(nèi)蒙古興安盟科爾沁右翼中旗蒙古族。# Population Percent
1 East_Asian 66.49
2 North_Asian 24.87
3 Indian 4.37
4 Caucaus_Parsia 2.16
5 Arctic_Amerind 0.84
6 Paleo_African 0.65
7 Sub_Saharian 0.35
8 Melanesian 0.17
9 North_and_East_European 0.09
Single Population Sharing:

# Population (source) Distance
1 Mongola 5.7
2 Xibo 6.68
3 Daur 9.7
4 Hezhen 10.12
5 Tu 16.3
6 Japanese 19.14
7 Indian_East 21.04
8 Mongol 23.79
9 Buma 24.07
10 Indian-East 25.42
11 Kalmyk 26.02
12 Naxi 26.66
13 Yizu 27.84
14 Khmer 29.03
15 Han-Beijing 29.56
16 Oroqen 30.3
17 Han 31.92
18 Kyrgyz 31.96
19 Buryat 33.85
20 Tujia 34.4
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