wang - 哈佛医学院、德国马普所分子人类学博士后祖源分析

Gedrosia K12说我们有印度成分，但这是不对的。。。

如图，这是我的结果，卧槽，我一99%北方汉啥时候变成了印度（S_INDIAN、INDO_TIBETAN）和东南亚（SE_ASIAN）混血了！

本着科学研究认真负责、严谨求实的精神，我去查了这个Gedrosia K12所用的参考群体：
S_INDIAN：Hakkipikki, Nihali,UP_Chamar
SE_ASIAN: Ami
INDO_TIBETAN: Kusunda
W_SIBERIAN: Nganasan
E_SIBERIAN: Itelmen, Koryak

首先，Hakkipikki, Nihali,UP_Chamar取自论文Metspalu M, et al. American Journal of Human Genetics. 2011 Dec 9;89(6):731-44，那我们回到原始论文中去看这几个人群的遗传背景，很明显，它们有着不同程度的中国人群的混血,所以不适合作为“S_INDIAN”来划分中国人群：

其次，Ami是台湾原住民，是东亚人群啊，啥时候被你换成东南亚了？东南亚的土著代表人群是Papuan，而Ami是来自东亚大陆的，几乎没有受到东南亚土著影响的。

再次，Kusunda来自尼泊尔，是典型的东西方混合族群，约是90%东亚+10%的印欧，所以会显示我们有高频的这一成分，但这是说明你来自东亚人群啊，为啥老是往印度靠拢取名“INDO_TIBETAN”？

最后，我想说，在不清楚群体遗传背景的情况下，Gedmatch能不能别乱用“祖先群体”？在地理没学好的情况下，能不能别乱取名（此处我又想起了K36的East_Central_Asian：达斡尔、赫哲、蒙古、鄂伦春和土族）？

2017-01-21 • IP属地德国

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13 个回复

wakaimono

出现韩国、日本本来就不奇怪，日本主体民族血缘大都来自中国，韩国也是，不论是箕子朝鲜还是卫满朝鲜时期大量中国血统的融入，以及历代中国人进入朝鲜，所以被验到有日韩血统，往往不是日韩人与你祖先发生了关系，而是你祖先的亲戚后来的小孩留在了日韩。东南亚也一样，除了早期迁徙路线外，更多被验到东南亚血统的也是这样，先秦的百越甚至楚国人被融合被驱离了中国本土，去了东南亚而已。印度北部尼泊尔有很多长相类似汉人的，可能查到的印度基因来自于这些你祖先的亲戚罢了

独立的ROBO1基因

事体重大，等待大牛们解答。

william0509 - 人文地理爱好者

在这个计算器中，我自己也是好几种成分的组成的。最接近的是呼伦贝尔蒙古人。看来汉族的主体成分是类阿美族的SE Asian.

Admix Results (sorted):

# Population Percent
1 SE_ASIAN 53.74
2 W_SIBERIAN 17.96
3 INDO_TIBETAN 15.75
4 E_SIBERIAN 8.76
5 S_INDIAN 3.53

Finished reading population data. 87 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Mongola @ 8.546090
2 Naga @ 17.189821
3 Ulchi @ 31.183672
4 Uzbek @ 49.860725
5 Ami @ 52.900059
6 Turkmen_Afghan @ 55.268719
7 Yukagir @ 58.566460
8 Yukagir @ 58.566460
9 Tajik_Afghan @ 61.500229
10 Uzbek_Afghan @ 62.638397
11 Turks_Aydin @ 69.676689
12 Turks_Balikesir @ 71.316429
13 Tajik_Pomiri @ 72.663643
14 Kurds_SE @ 73.255203
15 Turks_Istanbul @ 73.315674
16 Pashtun_Afghan @ 73.449036
17 Kurds_C @ 74.038696
18 Kurds_N @ 74.722733
19 Turks_Adana @ 74.722801
20 Kurds_F @ 74.858879

Using 2 populations approximation:
1 50% Mongola +50% Mongola @ 8.546090

Using 3 populations approximation:
1 50% Mongola +25% Mongola +25% Mongola @ 8.546090

Using 4 populations approximation:
++++++++++++++++++++
1 Ami + Naga + Naga + Yukagir @ 5.680217
2 Ami + Naga + Naga + Yukagir @ 5.680217
3 Ami + Mongola + Naga + Yukagir @ 7.604910
4 Ami + Mongola + Naga + Yukagir @ 7.604910
5 Ami + Naga + Naga + Ulchi @ 7.773861
6 Mongola + Mongola + Mongola + Mongola @ 8.546090
7 Mongola + Mongola + Mongola + Naga @ 8.849555
8 Ami + Mongola + Naga + Ulchi @ 9.030851
9 Ami + Ami + Kusunda + Yukagir @ 9.705093
10 Ami + Ami + Kusunda + Yukagir @ 9.705093
11 Ami + Kusunda + Ulchi + Ulchi @ 10.062571
12 Ami + Mongola + Naga + Uzbek @ 10.478352
13 Ami + Naga + Ulchi + Uzbek @ 10.514200
14 Ami + Mongola + Mongola + Naga @ 10.598746
15 Ami + Mongola + Mongola + Yukagir @ 10.816162
16 Ami + Mongola + Mongola + Yukagir @ 10.816162
17 Mongola + Mongola + Naga + Naga @ 10.824735
18 Ami + Naga + Naga + Uzbek @ 10.990318
19 Mongola + Naga + Naga + Ulchi @ 11.053302
20 Ami + Mongola + Mongola + Mongola @ 11.108327

萩野谷樹

Population
S_INDIAN 3.43
SUB_SAHARAN 0.13
EARLY_EUROPEAN_FARMERS -
SW_ASIAN -
W_SIBERIAN 18.68
SE_ASIAN 55.63
BALOCHI -
SINTASHTA_STEPPE_HERDERS 0.27
INDO_TIBETAN 15.35
CAUCASUS -
E_AFRICAN 0.10
E_SIBERIAN 6.4

我也来一波

請輸入用戶名

{"result":[{"race_desc":"\u4e2d\u534e\u6c11\u65cf","race_en":"chinese_nation","race_probality":"0.842224","area":[{"block":"chinese_nation","race_desc":"\u8499\u53e4\u8bed\u65cf\u7fa4","race_en":"mongolian","race_probality":"0.546612"},{"block":"chinese_nation","race_desc":"\u5357\u65b9\u6c49\u65cf","race_en":"han_southern","race_probality":"0.159010"},{"block":"chinese_nation","race_desc":"\u7eb3\u897f\/\u5f5d\u65cf","race_en":"ny","race_probality":"0.085570"},{"block":"chinese_nation","race_desc":"\u7572\u65cf","race_en":"she","race_probality":"0.029563"},{"block":"chinese_nation","race_desc":"\u62c9\u795c\u65cf","race_en":"lahu","race_probality":"0.011460"},{"block":"chinese_nation","race_desc":"\u9ad8\u5c71\u65cf","race_en":"gaoshan","race_probality":"0.008584"},{"block":"chinese_nation","race_desc":"\u5176\u4ed6","race_en":"other","race_probality":"0.0017"}]},{"race_desc":"\u4e1c\u5317\u4e9a","race_en":"ne_asian","race_probality":"0.157505","area":[{"block":"ne_asian","race_desc":"\u65e5\u672c","race_en":"japanese","race_probality":"0.093987"},{"block":"ne_asian","race_desc":"\u97e9\u56fd","race_en":"korean","race_probality":"0.063508"},{"block":"ne_asian","race_desc":"\u5176\u4ed6","race_en":"other","race_probality":"0.0001"}]},{"race_desc":"\u5176\u4ed6","race_en":"other","race_probality":"0.0003","area":[]}],"case_id":"ANCESTRY","prefix":null,"description":"\u7956\u6e90\u5206\u6790","color":null,"detail_url":"\/report2\/ancestry\/"}

感觉微基因针对北方人的祖源分类也很混乱，我这个山东裔东北人祖源分裂了，并且北方汉族0%。另外希望微基因能取消以国籍定义族群的分类方式！

ctlbj

除此之外，Gedrosia K12号称是给南亚和西亚人设计的，主要用于查看有没有Gedosian Balochi祖先。解释计算结果的第一段说：This calculator has been designed for individuals of predominately South Asian and West Asian ancestry for inferring gedrosian Balochi admixture. Since those populations were mostly used to source allele frequencies, individuals with majority ancestry from outside those regions will most likely find this calculator less accurate and informative.

william0509 - 人文地理爱好者

作为台湾对岸的汉族，在这个计算器里我和4500公里远的乌兹别克族比200公里的阿美族更近。这个确实是颠覆了我以前的想法。

yixiaolan

为啥Wegene也给了我印度和藏族？胡建人表示，瑟瑟发抖啊。

是不是你们算法问题？dna.land没给我任何南亚的祖源成分。

yixiaolan

Population
S_INDIAN 2.49
SUB_SAHARAN 1.22
EARLY_EUROPEAN_FARMERS 1.04
SW_ASIAN -
W_SIBERIAN 20.57
SE_ASIAN 53.31
BALOCHI 0.05
SINTASHTA_STEPPE_HERDERS -
INDO_TIBETAN 16.51
CAUCASUS -
E_AFRICAN -
E_SIBERIAN 4.79

所以它的算法给我的印度成分和Wegene真的差不多欸

kaji - 无

gedmatch部分计算器不适用东亚人，具体可以看计算器内的表格参照。南印度是棕色人种与暗白人种（少量）混合的成分，参照样本是南印度的一个民族（忘了叫啥）

稳重的AJAP1基因

印度的计算器没几个准的，也就哈拉帕、World25等值得参考

礼貌的CDH12基因

S_INDIAN应该用一些南亚土著成分高的印度泰米尔纳德邦，安德拉邦等南部人群，南亚约占7成以上。

Papuan和澳洲土著同为大洋洲的代表人群，和东南亚没有关系。东南亚本来就是东亚的一个子集。

Kusunda是东亚和南亚人群的混血，它的南亚祖先人群可能保留了比较多的南亚土著成分，南亚约占3成以上。

阿悦1990

K36是指Eurogenes K36吗？里面East_Central_Asian居然是达斡尔、赫哲、蒙古、鄂伦春和土族？

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Gedrosia K12说我们有印度成分，但这是不对的。。。

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13 个回复