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okarinaofsteiner
07-29-2021, 01:10 AM
Creating a separate thread for this from my East Eurasian megathread (https://anthrogenica.com/showthread.php?20657-okarinaofsteiner-s-East-Eurasian-GEDmatch-megathread&p=783117&viewfull=1#post783117): https://anthrogenica.com/showthread.php?20657-okarinaofsteiner-s-East-Eurasian-GEDmatch-megathread

Anthroscape user @kushkush made some autosomal DNA (HarappaWorld) maps of Chinese provinces around the end of 2019, which were interesting but didn't seem completely accurate to me, since they weren't weighted by population distribution within specific provinces. I think these are just averages of random samples from specific provinces, they don't seem to be specific to Han Chinese.

Posting their findings here for reference:

HarappaWorld NE Asian
https://i.imgur.com/XXiQ5jM.png

HarappaWorld SE Asian
https://i.imgur.com/AlrCqsi.png

HarappaWorld Siberian
https://i.imgur.com/e0vq3KL.png

HarappaWorld table
https://i.imgur.com/Rg3PgpF.png

okarinaofsteiner
07-29-2021, 01:14 AM
Reposting my own version of @kushkush's maps with MDLP K23b results (https://anthrogenica.com/showthread.php?20657-okarinaofsteiner-s-East-Eurasian-GEDmatch-megathread&p=783117&viewfull=1#post783117) here for comparison.

This was based on the DNAConnect.org dataset as well as other samples found on GEDmatch and the WeGene forum. I'd like to think this is more representative of the Han in each province, since I tried to weigh my assigned samples for each province I had more than 10 samples for according to the population distibution for that province.

The first 4 maps are of the 4 largest MDLP K23b East Eurasian ancestry components found among Chinese samples. The 5th one is of a North-South cline I created for East Asian MDLP K23b results. Basically "Tungus_Altaic" = northern, "Austronesian" = southern, while "South_East_Asian" and the 2 "Siberian" components are defined relative to T_A and AN. The original idea was that a Han Chinese person who scores the same amount of T_A and AN will score 0.5 on my North-South cline.

https://i.imgur.com/cw2QvTF.png

https://i.imgur.com/hwr2amo.png

https://i.imgur.com/rT227Kd.png

https://i.imgur.com/IbsfvhK.png

https://i.imgur.com/EQjAhu7.png

Original methodology post (link is defunct)- https://www.tapatalk.com/groups/anthroscape/mdlp-k23b-results-and-pca-plots-for-east-asians-t85446-s120.html#p1848187

TL;DR- I tried to weigh my available data according to the actual population distribution within each province (the DNAConnect.org data was geographically biased for most of the provinces- especially Jiangxi, Guangdong, Hunan, and Chongqing- which make up most of the DNAConnect.org dataset). Most of the samples in my original dataset and from DNAConnect.org were from the southern provinces, with very few from the northern provinces, so I had to use whatever I could get my hands on. The samples I used in my original dataset were just the ones of known regional/provincial ancestry.

I weighed the Fujian, Jiangxi, Hunan, and Anhui DNAConnect.org subsets according to the population distribution of each province to make them more representative. The Guangdong and Shaanxi subsets only represented more remote parts of the provinces, and the Guizhou subset was mostly from minority-heavy areas. The only northern province represented in the DNAConnect.org dataset was Henan.

Kaazi
07-29-2021, 04:46 AM
Creating a separate thread for this from my East Eurasian megathread (https://anthrogenica.com/showthread.php?20657-okarinaofsteiner-s-East-Eurasian-GEDmatch-megathread&p=783117&viewfull=1#post783117): https://anthrogenica.com/showthread.php?20657-okarinaofsteiner-s-East-Eurasian-GEDmatch-megathread

Anthroscape user @kushkush made some autosomal DNA (HarappaWorld) maps of Chinese provinces around the end of 2019, which were interesting but didn't seem completely accurate to me, since they weren't weighted by population distribution within specific provinces. I think these are just averages of random samples from specific provinces, they don't seem to be specific to Han Chinese.

Posting their findings here for reference:

HarappaWorld NE Asian
https://i.imgur.com/XXiQ5jM.png

HarappaWorld SE Asian
https://i.imgur.com/AlrCqsi.png

HarappaWorld Siberian
https://i.imgur.com/e0vq3KL.png

HarappaWorld table
https://i.imgur.com/Rg3PgpF.png

That's pretty outdated table.

You should create new average based on the large no. of Tibetan, Han samples available in genoplot. Tibet surely isn't 78% NE-Asian on average. It would be sth around early 70s.


SampleNE-AsianPapuanSE-AsianS-IndianSiberianSW-AsianBeringianSanNE-EuroAmericanCaucasianBalochMediterraneanE-AfricanPygmyW-AfricanTibetan Xinlong ► XL7699.760.180.060000000000000
Tibetan Xinlong ► XL6080.430.6207.4111.20000000000.030.31
Tibetan Yajiang ► YJ14080.031.051.324.311.060.010.4001.130000.490.21 0
Tibetan Chamdo ► T27479.971.7205.1410.640.541.020.1000.8600000
Tibetan Yajiang ► YJ11179.81.382.573.7111.140000.2300.0400.71000.4
Tibetan Yajiang ► YJ3779.32.5603.9411.810.490001.50.250000.140
Tibetan Chamdo ► T24778.991.090.347.8711.290.410000000000
Tibetan Chamdo ► T7478.421.1406.5813.300.55000000000
Tibetan Yajiang ► YJ0178.310.421.594.0212.5900.45000.86000.510.3200. 94
Tibetan Yajiang ► YJ2578.140.310.935.0411.540.551.990.14000.1700.020 .1101.06
Tibetan Yajiang ► YJ10478.012.13.023.8812.010.03000.4300000.5100
Tibetan Chamdo ► T28377.911.071.225.4312.2800.810.28000.9300.060.01 00
Tibetan Chamdo ► T27377.661.2914.8711.040100.591.230.950.370000
Tibetan Lhasa ► T7677.641.1905.7111.2101.990000.841.060.35000
Tibetan Chamdo ► T19477.642.212.494.512.5800.05000.17000.36000
Tibetan Chamdo ► T17377.581.2806.6412.4901.840.1700000000
Tibetan Xinlong ► XL0577.420.8808.312.810.18000.120.29000000
Tibetan Chamdo ► T14477.421.9105.3812.5500.840010.900000
Tibetan Chamdo ► T19677.412.172.72.9511.230.22.9800.310.05000000
Tibetan Nagqu ► T23877.341.060.94.1612.490.591.840.081.530000000
Tibetan Nagqu ► T32077.261.971.14.6511.960.490.5701.4600.010.3100. 2200
Tibetan Chamdo ► T14177.151.090.715.9713.5600.3600.750.43000000
Tibetan Yajiang ► YJ1277.010.626.456.346.98000.320.261.2500.030.310. 4300
Tibetan Lhasa ► T18576.4710.198.3411.7600000.720.491.030000
Tibetan Chamdo ► T36376.261.660.595.813.5900.51000.1301.14000.340
Tibetan Lhasa ► T16576.210.8808.1111.301.410002.0900000
Tibetan Shigatse ► T8076.182.120.798.289.640.510.61001.1400.5400.1800
Tibetan Nagqu ► T6776.092.11.436.7511.7100.530.170.4700.7600000
Tibetan Nagqu ► T12175.651.6507.8711.80.481.03001.0500.100.3600
Tibetan Lhasa ► T18375.431.191.425.613.04000002.130.960.22000
Tibetan Nagqu ► T9175.271.3806.8113.550.310.770.3600.230.93000.410 0
Tibetan Shannan ► T12775.242.70.257.8311.0600.530.0600.940.360.660.3 5000
Tibetan Shigatse ► T2275.082.031.297.0211.710000.021.181.310.370000
Tibetan Nagqu ► T31274.921.1909.3114.060000.30.0600.170000
Tibetan Chamdo ► T28274.921.980.526.212.800.08001.241.7800.360.0900
Tibetan Shigatse ► T21574.71.830.927.4412.300.9800.1700.61.050000
Tibetan Shannan ► T28974.592.1608.2610.9800.9400.890.3401.840000
Tibetan Xinlong ► XL6174.41.0710.964.288.25000.1200.840000.050.020
Tibetan Lhasa ► T17074.342.381.17.7910.811.521.060.090.440.28000.2 000
Tibetan Shannan ► T20074.281.7907.9612.840.030000.7901.6800.6400
Tibetan Shannan ► T18874.052.010.178.5110.4600.7200.751.431.8200.060 00
Tibetan Shigatse ► T7873.822.860.596.0413.790.30.040.1400.650.541.210 000
Tibetan Lhasa ► T18173.781.361.566.9312.2400.7101.81.1800.440000
Tibetan Lhasa ► T12573.781.880.527.1411.240.492.92000.3801.660000
Tibetan Shannan ► T24273.62.920.766.2120.211.65000.970.70.75000.230
Tibetan Xinlong ► XL12073.531.590.436.1613.350.232.0100.130.930.860. 130.100.30.25
Tibetan Nagqu ► T18773.521.652.266.5613.1400.71000.6101.560000
Tibetan Shigatse ► T29773.52.560.846.513.5400.34000.6202.10000
Tibetan Gangcha ► QH473.351.7805.3912.6102.1601.020.6501.951.09000
Tibetan Lhasa ► T2173.231.412.17.4412.7301.390.1201.2600.320000
Tibetan Gangcha ► QH2073.210.860.34.6715.2100001.41.532.810000
Tibetan Shigatse ► T19272.681.172.997.0611.4901.8901.650.2800.4500.35 00
Tibetan Lhasa ► T1872.451.34.326.1112.741.560000.170.510.830000
Tibetan Yajiang ► YJ1472.291.0613.073.458.710.52000.050.230.1100000. 5
Tibetan Shigatse ► T291721.681.957.6313.8100000.7801.3700.7800
Tibetan Shigatse ► T7771.921.791.158.3311.3101.2901.511.3101.410000
Tibetan Xunhua ► XHTB771.821.155.63.5410.732.2100.041.800.072.45000 .210.38
Tibetan Gangcha ► QH1171.811.862.314.1914.60.560.450.111.1901.030.90 00
Tibetan Gangcha ► QH171.711.730.545.9712.270.91001.432.30.262.890000
Tibetan Gangcha ► QH571.70.380.795.2514.513.610.180.181.121.30.180.3 90.3300.070
Tibetan Shigatse ► T4171.482.321.168.1113.53000.030.612.11000.66000
Tibetan Shannan ► T19071.281.893.036.8813.030.7800.110.731.261.01000 00
Tibetan Gangcha ► QH1771.241.760.265.1214.370.922.5700.6301.980.320. 83000
Tibetan Gangcha ► QH1271.160.483.154.7115.4401.0502.021.370.6200000
Tibetan Nagqu ► T27871.041.743.517.6513.330.640.4700.061.550000.01 00
Tibetan Shannan ► T24870.551.773.617.612.470.91.260.0800.8200.930000
Tibetan Gangcha ► QH870.52.560.185.3814.301.7202.6200.31.930.51000
Tibetan Shigatse ► T18970.22.243.589.1913.410.010.13000.30.510.31000. 110
Tibetan Shannan ► T19970.141.932.187.7212.3302.0500.060.630.432.1000 .430
Tibetan Gangcha ► QH1070.11.560.884.6314.6700011.121.513.320.96000.2 6
Tibetan Yajiang ► YJ3969.980.9814.613.368.970000.881.09000000.13
Tibetan Gangcha ► QH1969.880.874.344.9615.1800.4700.6102.830.860000
Tibetan Gangcha ► QH1869.871.50.514.7415.40.481.0801.080.913.291.130 000
Tibetan Gangcha ► QH669.732.173.224.0514.050.932.8200.1600.421.211.2 3000
Tibetan Xinlong ► XL4769.48014.484.138.4700.980.150.9400.330.750.050 00.25
Tibetan Gangcha ► QH1569.481.013.026.515.420000.350.932.500.300.490
Tibetan Shannan ► T12669.351.542.816.1115.250.630.9800.2202.470.5100 00.13
Tibetan Xinlong ► XL9268.9021.660.817.330.280.570000.1800000.25
Tibetan Xunhua ► XHTB2068.851.644.196.3510.6800.980.523.17000.820.2 9002.53
Tibetan Gangcha ► QH1468.751.982.512.6816.4701.8300.9503.141.150.530 00
Tibetan Gangcha ► QH768.450.72.83.3816.4601.810.161.0800.962.51.6800 0
Tibetan Xinlong ► XL3768.270.7424.880.195.1400.78000000000
Tibetan Gannan ► GN1968.1907.23.3710.420.61.970.061.080.783.331.910 .4300.650
Tibetan Xunhua ► XHTB568.071.165.416.8412.3901.160.230.931.121.830. 79000.060
Tibetan Gannan ► GN0168.020.449.072.189.95000.4301.371.494.722.3400 0
Tibetan Gangcha ► QH1667.941.362.257.1213.2201.0100.091.582.151.511. 76000
Tibetan Gangcha ► QH967.760.965.323.8615.5500.350.141.7400.913.41000 0
Tibetan Gangcha ► QH1367.30.3411.232.2410.010.721.5401.411.982.330.7 800.1300
Tibetan Gannan ► GN1067.18012.150.8110.1300.803.0101.792.821.10.200
Tibetan Xinlong ► XL2266.940.727.690.052.5101.520.1100.34000000.14
Tibetan Gannan ► GN1765.980.3712.023.028.780.51.2103.6402.571.050.8 7000
Tibetan Gannan ► GN0365.580.9512.131.768.851.190.301.2702.085.040.1 30.4100.31
Tibetan Gangcha ► QH364.671.422.65.9217.520.531.7302.70.940.870.660. 45000
Tibetan Xunhua ► XHTB1763.941.3814.61010.790.430.0401.1701.42.791.7 40.501.22
Tibetan Yajiang ► YJ8663.290.6612.512.257.161.191.450.081.170.616.87 2.760000
Tibetan Gangcha ► QH262.371.561.724.4318.981.161.760.020.961.911.683 .460000
Tibetan Xinlong ► XL2059.360.1736.450.172.490.8800.100.140.12000.120 0

Shuzam87
08-05-2021, 12:30 AM
That's pretty outdated table.

You should create new average based on the large no. of Tibetan, Han samples available in genoplot. Tibet surely isn't 78% NE-Asian on average. It would be sth around early 70s.


SampleNE-AsianPapuanSE-AsianS-IndianSiberianSW-AsianBeringianSanNE-EuroAmericanCaucasianBalochMediterraneanE-AfricanPygmyW-AfricanTibetan Xinlong ► XL7699.760.180.060000000000000
Tibetan Xinlong ► XL6080.430.6207.4111.20000000000.030.31
Tibetan Yajiang ► YJ14080.031.051.324.311.060.010.4001.130000.490.21 0
Tibetan Chamdo ► T27479.971.7205.1410.640.541.020.1000.8600000
Tibetan Yajiang ► YJ11179.81.382.573.7111.140000.2300.0400.71000.4
Tibetan Yajiang ► YJ3779.32.5603.9411.810.490001.50.250000.140
Tibetan Chamdo ► T24778.991.090.347.8711.290.410000000000
Tibetan Chamdo ► T7478.421.1406.5813.300.55000000000
Tibetan Yajiang ► YJ0178.310.421.594.0212.5900.45000.86000.510.3200. 94
Tibetan Yajiang ► YJ2578.140.310.935.0411.540.551.990.14000.1700.020 .1101.06
Tibetan Yajiang ► YJ10478.012.13.023.8812.010.03000.4300000.5100
Tibetan Chamdo ► T28377.911.071.225.4312.2800.810.28000.9300.060.01 00
Tibetan Chamdo ► T27377.661.2914.8711.040100.591.230.950.370000
Tibetan Lhasa ► T7677.641.1905.7111.2101.990000.841.060.35000
Tibetan Chamdo ► T19477.642.212.494.512.5800.05000.17000.36000
Tibetan Chamdo ► T17377.581.2806.6412.4901.840.1700000000
Tibetan Xinlong ► XL0577.420.8808.312.810.18000.120.29000000
Tibetan Chamdo ► T14477.421.9105.3812.5500.840010.900000
Tibetan Chamdo ► T19677.412.172.72.9511.230.22.9800.310.05000000
Tibetan Nagqu ► T23877.341.060.94.1612.490.591.840.081.530000000
Tibetan Nagqu ► T32077.261.971.14.6511.960.490.5701.4600.010.3100. 2200
Tibetan Chamdo ► T14177.151.090.715.9713.5600.3600.750.43000000
Tibetan Yajiang ► YJ1277.010.626.456.346.98000.320.261.2500.030.310. 4300
Tibetan Lhasa ► T18576.4710.198.3411.7600000.720.491.030000
Tibetan Chamdo ► T36376.261.660.595.813.5900.51000.1301.14000.340
Tibetan Lhasa ► T16576.210.8808.1111.301.410002.0900000
Tibetan Shigatse ► T8076.182.120.798.289.640.510.61001.1400.5400.1800
Tibetan Nagqu ► T6776.092.11.436.7511.7100.530.170.4700.7600000
Tibetan Nagqu ► T12175.651.6507.8711.80.481.03001.0500.100.3600
Tibetan Lhasa ► T18375.431.191.425.613.04000002.130.960.22000
Tibetan Nagqu ► T9175.271.3806.8113.550.310.770.3600.230.93000.410 0
Tibetan Shannan ► T12775.242.70.257.8311.0600.530.0600.940.360.660.3 5000
Tibetan Shigatse ► T2275.082.031.297.0211.710000.021.181.310.370000
Tibetan Nagqu ► T31274.921.1909.3114.060000.30.0600.170000
Tibetan Chamdo ► T28274.921.980.526.212.800.08001.241.7800.360.0900
Tibetan Shigatse ► T21574.71.830.927.4412.300.9800.1700.61.050000
Tibetan Shannan ► T28974.592.1608.2610.9800.9400.890.3401.840000
Tibetan Xinlong ► XL6174.41.0710.964.288.25000.1200.840000.050.020
Tibetan Lhasa ► T17074.342.381.17.7910.811.521.060.090.440.28000.2 000
Tibetan Shannan ► T20074.281.7907.9612.840.030000.7901.6800.6400
Tibetan Shannan ► T18874.052.010.178.5110.4600.7200.751.431.8200.060 00
Tibetan Shigatse ► T7873.822.860.596.0413.790.30.040.1400.650.541.210 000
Tibetan Lhasa ► T18173.781.361.566.9312.2400.7101.81.1800.440000
Tibetan Lhasa ► T12573.781.880.527.1411.240.492.92000.3801.660000
Tibetan Shannan ► T24273.62.920.766.2120.211.65000.970.70.75000.230
Tibetan Xinlong ► XL12073.531.590.436.1613.350.232.0100.130.930.860. 130.100.30.25
Tibetan Nagqu ► T18773.521.652.266.5613.1400.71000.6101.560000
Tibetan Shigatse ► T29773.52.560.846.513.5400.34000.6202.10000
Tibetan Gangcha ► QH473.351.7805.3912.6102.1601.020.6501.951.09000
Tibetan Lhasa ► T2173.231.412.17.4412.7301.390.1201.2600.320000
Tibetan Gangcha ► QH2073.210.860.34.6715.2100001.41.532.810000
Tibetan Shigatse ► T19272.681.172.997.0611.4901.8901.650.2800.4500.35 00
Tibetan Lhasa ► T1872.451.34.326.1112.741.560000.170.510.830000
Tibetan Yajiang ► YJ1472.291.0613.073.458.710.52000.050.230.1100000. 5
Tibetan Shigatse ► T291721.681.957.6313.8100000.7801.3700.7800
Tibetan Shigatse ► T7771.921.791.158.3311.3101.2901.511.3101.410000
Tibetan Xunhua ► XHTB771.821.155.63.5410.732.2100.041.800.072.45000 .210.38
Tibetan Gangcha ► QH1171.811.862.314.1914.60.560.450.111.1901.030.90 00
Tibetan Gangcha ► QH171.711.730.545.9712.270.91001.432.30.262.890000
Tibetan Gangcha ► QH571.70.380.795.2514.513.610.180.181.121.30.180.3 90.3300.070
Tibetan Shigatse ► T4171.482.321.168.1113.53000.030.612.11000.66000
Tibetan Shannan ► T19071.281.893.036.8813.030.7800.110.731.261.01000 00
Tibetan Gangcha ► QH1771.241.760.265.1214.370.922.5700.6301.980.320. 83000
Tibetan Gangcha ► QH1271.160.483.154.7115.4401.0502.021.370.6200000
Tibetan Nagqu ► T27871.041.743.517.6513.330.640.4700.061.550000.01 00
Tibetan Shannan ► T24870.551.773.617.612.470.91.260.0800.8200.930000
Tibetan Gangcha ► QH870.52.560.185.3814.301.7202.6200.31.930.51000
Tibetan Shigatse ► T18970.22.243.589.1913.410.010.13000.30.510.31000. 110
Tibetan Shannan ► T19970.141.932.187.7212.3302.0500.060.630.432.1000 .430
Tibetan Gangcha ► QH1070.11.560.884.6314.6700011.121.513.320.96000.2 6
Tibetan Yajiang ► YJ3969.980.9814.613.368.970000.881.09000000.13
Tibetan Gangcha ► QH1969.880.874.344.9615.1800.4700.6102.830.860000
Tibetan Gangcha ► QH1869.871.50.514.7415.40.481.0801.080.913.291.130 000
Tibetan Gangcha ► QH669.732.173.224.0514.050.932.8200.1600.421.211.2 3000
Tibetan Xinlong ► XL4769.48014.484.138.4700.980.150.9400.330.750.050 00.25
Tibetan Gangcha ► QH1569.481.013.026.515.420000.350.932.500.300.490
Tibetan Shannan ► T12669.351.542.816.1115.250.630.9800.2202.470.5100 00.13
Tibetan Xinlong ► XL9268.9021.660.817.330.280.570000.1800000.25
Tibetan Xunhua ► XHTB2068.851.644.196.3510.6800.980.523.17000.820.2 9002.53
Tibetan Gangcha ► QH1468.751.982.512.6816.4701.8300.9503.141.150.530 00
Tibetan Gangcha ► QH768.450.72.83.3816.4601.810.161.0800.962.51.6800 0
Tibetan Xinlong ► XL3768.270.7424.880.195.1400.78000000000
Tibetan Gannan ► GN1968.1907.23.3710.420.61.970.061.080.783.331.910 .4300.650
Tibetan Xunhua ► XHTB568.071.165.416.8412.3901.160.230.931.121.830. 79000.060
Tibetan Gannan ► GN0168.020.449.072.189.95000.4301.371.494.722.3400 0
Tibetan Gangcha ► QH1667.941.362.257.1213.2201.0100.091.582.151.511. 76000
Tibetan Gangcha ► QH967.760.965.323.8615.5500.350.141.7400.913.41000 0
Tibetan Gangcha ► QH1367.30.3411.232.2410.010.721.5401.411.982.330.7 800.1300
Tibetan Gannan ► GN1067.18012.150.8110.1300.803.0101.792.821.10.200
Tibetan Xinlong ► XL2266.940.727.690.052.5101.520.1100.34000000.14
Tibetan Gannan ► GN1765.980.3712.023.028.780.51.2103.6402.571.050.8 7000
Tibetan Gannan ► GN0365.580.9512.131.768.851.190.301.2702.085.040.1 30.4100.31
Tibetan Gangcha ► QH364.671.422.65.9217.520.531.7302.70.940.870.660. 45000
Tibetan Xunhua ► XHTB1763.941.3814.61010.790.430.0401.1701.42.791.7 40.501.22
Tibetan Yajiang ► YJ8663.290.6612.512.257.161.191.450.081.170.616.87 2.760000
Tibetan Gangcha ► QH262.371.561.724.4318.981.161.760.020.961.911.683 .460000
Tibetan Xinlong ► XL2059.360.1736.450.172.490.8800.100.140.12000.120 0


Yeah, it would be cool if we can have an update.

okarinaofsteiner
08-10-2021, 11:54 PM
Yeah, it would be cool if we can have an update.

That was all Anthroscape user @kushkush- I have no idea if he's still into this stuff or have time for that. I don't even know how he found all those Tibetan GEDmatch samples back in the day.

I've considered making a HarappaWorld version of my MDLP K23b maps, but idk if the kits I used to calibrate results for different provinces are still publicly available. I'm guessing most have been deleted or removed from public access by now.

Kaazi
08-13-2021, 06:37 PM
Yeah, it would be cool if we can have an update.

Just made 100 Tibetans' average from genoplot.
https://anthrogenica.com/showthread.php?15471-South-Asian-HarappaWorld-results&p=791994&viewfull=1#post791994

https://i.imgur.com/SxAoANf.png