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Received: 2,868/149 Given: 444/392 |
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Received: 2,785/34 Given: 9/0 |
A big problem with these GEDmatch calculators is that they're fucking noisy, there's no way a Chinese or Polish person really scores 1-2% SSA or Oceanian in the components. On Global25 this doesn't happen.
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Received: 7,319/30 Given: 2,681/16 |
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Received: 15,693/315 Given: 8,913/358 |
Luke, please add these, they're good enough
Code:Pamiri_Wakhan,31.54,5.87,0,1.18,3.47,21.98,13.53,0.10,0.78,5.85,15.68,0.03Code:Iranian_Zoroastrian,28.13,0.61,1.06,0.49,6.18,9.13,4.68,0.27,12.55,0.22,36.39,0.29Code:Iranian_Central,27.04,0.96,0.37,0.64,6.16,7.35,5.77,0.78,12.87,0.66,36.64,0.68
Last edited by Leto; 08-29-2021 at 04:40 PM.
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Received: 8,835/73 Given: 8,960/67 |
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Received: 612/3 Given: 2,311/12 |
Dear Lucas, please add these new Dzungaria and Tarim Basin ancient individuals into G25:
Code:CHN_Dzungaria_EBA1:AYIM22BN,0.111547,0.031481,0.051288,0.127909,-0.052933,0.049364,-0.014336,-0.015461,-0.039678,-0.073077,0.005034,-0.007943,0.004608,-0.038534,0.028501,0.021347,-0.004172,-0.004054,-0.007165,0.008379,-0.012852,0.000495,0.004683,0.020846,0.000718 CHN_Dzungaria_EBA1:AYIM22BY,0.104717,0.014217,0.050534,0.114343,-0.055703,0.036535,-0.012926,-0.008538,-0.046631,-0.073623,0.00747,-0.007044,0.010555,-0.042388,0.038002,0.012861,-0.018123,0.004814,0.000126,-0.003252,-0.008859,0.008408,0.01405,0.020244,-0.012933 CHN_Dzungaria_EBA1:SSGM16,0.119514,0.026404,0.052043,0.134369,-0.046778,0.041276,-0.00705,-0.017538,-0.050517,-0.078179,0.005359,0.00045,0.00773,-0.036057,0.03963,0.016176,-0.01343,-0.005321,-0.007039,0.005378,-0.01697,0.004081,0.012818,0.025425,-0.00455 CHN_Dzungaria_EBA2:G218M5-2,0.10927,-0.008124,0.056945,0.122418,-0.062781,0.041276,-0.011516,-0.023999,-0.044586,-0.071437,0.004872,0.003147,0.009663,-0.049269,0.029044,0.021745,-0.006389,0.00076,-0.011941,0.005503,-0.01697,0.008037,0.018241,0.022533,-0.003473 CHN_Dzungaria_EBA2:G218M5-3N,0.104717,-0.035544,0.054305,0.115958,-0.057549,0.035698,-0.022091,-0.019384,-0.037632,-0.072165,0.001624,0.001499,0.02438,-0.04225,0.030673,0.008221,-0.020079,0.002154,0.003771,0.005378,-0.024083,0.012365,0.012078,0.025907,-0.003952 CHN_Tarim_EMBA1:GMGM1,0.094473,-0.121864,0.067127,0.192832,-0.11356,0.038208,-0.043242,-0.060459,-0.045813,-0.100594,0.024521,-0.015137,0.025718,-0.068123,0.022801,0.027844,-0.025295,-0.004054,-0.006788,-0.001251,-0.040928,0.00136,0.021815,0.008555,-0.0097 CHN_Tarim_EMBA1:L5209,0.104717,-0.099522,0.075047,0.203814,-0.117868,0.047133,-0.053347,-0.063459,-0.042336,-0.097679,0.028418,-0.014087,0.033151,-0.074591,0.029451,0.024396,-0.017993,-0.00266,0.004525,-0.004002,-0.052158,0.012489,0.035126,0.020003,-0.003353 CHN_Tarim_EMBA1:L5213,0.101303,-0.103584,0.075424,0.198646,-0.115406,0.053268,-0.047237,-0.067382,-0.049086,-0.096767,0.026469,-0.01124,0.020367,-0.072802,0.030809,0.025325,-0.015125,-0.001014,0.003017,-0.011255,-0.05091,0.006677,0.019843,0.013616,-0.00479 CHN_Tarim_EMBA1:L6101,0.104717,-0.100537,0.078441,0.202845,-0.107712,0.029841,-0.055698,-0.057228,-0.043564,-0.08966,0.022572,-0.01169,0.020069,-0.06193,0.02253,0.031954,-0.01682,0.0019,0.008799,-0.00075,-0.057024,-0.00371,0.017378,0.007471,-0.006706 CHN_Tarim_EMBA1:L6103,0.104717,-0.101553,0.078818,0.201876,-0.109559,0.051037,-0.042537,-0.059997,-0.046427,-0.093487,0.027444,-0.015137,0.022448,-0.079271,0.022122,0.018828,-0.011604,-0.004687,0.003268,-0.013757,-0.052782,0.000866,0.020952,0.012773,-0.017244 CHN_Tarim_EMBA1:L6105,0.094473,-0.103584,0.072407,0.208336,-0.125562,0.051316,-0.048882,-0.061844,-0.039064,-0.093305,0.037512,-0.015736,0.026462,-0.074729,0.019272,0.01538,-0.029858,-0.003041,-0.005279,-0.012006,-0.05116,0.014096,0.025389,0.013737,-0.006227 CHN_Tarim_EMBA1:L6106,0.092197,-0.102568,0.072407,0.215119,-0.117868,0.054105,-0.051232,-0.058151,-0.036814,-0.089842,0.03264,-0.01139,0.029137,-0.071151,0.033387,0.019093,-0.01369,0.002027,0.008547,-0.01063,-0.052907,0.002968,0.025019,0.012652,-0.012454 CHN_Tarim_EMBA1:XHM75,0.110408,-0.09546,0.064865,0.207367,-0.118176,0.0502,-0.048412,-0.066228,-0.035178,-0.100594,0.028743,-0.013488,0.027651,-0.074454,0.02633,0.022408,-0.025425,-0.001014,-0.003142,-0.004002,-0.044921,0.018177,0.029086,0.020244,-0.014609 CHN_Tarim_EMBA1:XHM100,0.106994,-0.102568,0.070522,0.204783,-0.11356,0.044344,-0.047472,-0.063459,-0.034769,-0.104239,0.028418,-0.012139,0.022002,-0.071426,0.023072,0.022408,-0.019036,0.000633,-0.003771,-0.012631,-0.048914,0.014962,0.024157,0.015183,-0.003712 CHN_Tarim_EMBA1:XHM110,0.108132,-0.093429,0.067505,0.198,-0.109251,0.044344,-0.052877,-0.05169,-0.044791,-0.099319,0.022897,-0.014387,0.020069,-0.071977,0.030944,0.025855,-0.020992,-0.001267,0.005656,0.003752,-0.052033,0.005564,0.018117,0.013375,-0.008502 CHN_Tarim_EMBA1:XHM135,0.104717,-0.097491,0.074293,0.193155,-0.117253,0.051316,-0.046532,-0.058151,-0.046631,-0.097132,0.030367,-0.014387,0.023934,-0.061655,0.024565,0.021612,-0.019427,-0.004561,-0.001634,0,-0.049163,0.006183,0.024033,0.014701,-0.007784 CHN_Tarim_EMBA2:11KBM1,0.104717,-0.118817,0.078441,0.199938,-0.088016,0.05271,-0.041127,-0.053998,-0.035587,-0.086015,0.022572,-0.012739,0.02334,-0.052985,0.002443,0.02612,-0.003651,0.007095,-0.003771,-0.01013,-0.057773,0.011376,0.019843,0.02663,0.002155
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Received: 407/2 Given: 443/1 |
@Lucas, do you know that a huge amount of South and Central Asian G25 have been processed this week. Samples from GSA Chinese dataset and Reich Lab dataset were processed. https://ngdc.cncb.ac.cn/bioproject/browse/PRJCA000456
1. Sarikoli/Wakhi (Tajik group) from Xinjiang, China
2. Tajiks from Badakhshan, Tajikistan
https://drive.google.com/file/d/12US...ew?usp=sharing
3. Balti samples from North Pakistan (https://academic.oup.com/mbe/article/38/4/1529/6025184)
https://docs.google.com/document/d/1...it?usp=sharing
4. Kashmiri samples from Pakistan
5. HGDP Punjabi Lahore Pakistan samples
https://docs.google.com/document/d/1...t?usp=drivesdk
https://www.dropbox.com/s/e5t7nc71qg...n_G25.txt?dl=1
Finally
6. Gujaratis from Houston (GIH)
7. Indian Telugus from UK
8. Sri Lankan Tamils from UK
https://docs.google.com/document/d/1...it?usp=sharing
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Received: 2,785/34 Given: 9/0 |
Not only that: this morning the modern populations of Russian_Tver, Russian_Smolensk, Russian_Orel, Russian_Kursk were updated and new ones were added, such as Russian_Belgorod, Russian_Kaluga, Russian_Krasnoborsky, Russian_Leshukonsky, Russian_Pinezhsky, Russian_Pskov, Russian_Ryazan and Russian_Yaroslavl.
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Received: 7,319/30 Given: 2,681/16 |
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Received: 7,319/30 Given: 2,681/16 |
K36 Genetic Similarity Report & K36 Advanced Chromosomal Analysis (Automated)
https://lm-genetics.com
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