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HLA » Allele Frequency Search
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| Line | Allele | Population | % of individuals that have the allele |
Allele Frequency |
Sample Size |
Location |
|---|---|---|---|---|---|---|
| 1 | A*11:01 | American Samoa | 0.1600 | 51 | 14_18_S_170_42_W | |
| 2 | A*11:01 | Argentina Rosario Toba | 1.2 | 0.0060 | 86 | 32_57_S_60_39_W |
| 3 | A*11:01 | Armenia combined Regions | 0.0800 | 100 | 40_11_N_44_31_E | |
| 4 | A*11:01 | Australia Cape York Peninsula Aborigine | 0.1800 | 103 | 10_41_S_142_32_E | |
| 5 | A*11:01 | Australia Groote Eylandt Aborigine | 0.2400 | 75 | 13_58_S_136_35_E | |
| 6 | A*11:01 | Australia Kimberly Aborigine | 0.0970 | 41 | 15_46_S_128_44_E | |
| 7 | A*11:01 | Australia New South Wales Caucasian | 0.0670 | 134 | 33_0_S_146_0_E | |
| 8 | A*11:01 | Australia Yuendumu Aborigine | 0.0760 | 191 | 22_15_S_131_47_E | |
| 9 | A*11:01 | Austria | 6.5 | 0.0320 | 200 | 48_13_N_16_21_E |
| 10 | A*11:01 | Azores Central Islands | 0.0540 | 59 | 38_0_N_28_0_W | |
| 11 | A*11:01 | Azores Oriental Islands | 0.0380 | 43 | 36_58_N_25_6_W | |
| 12 | A*11:01 | Azores Terceira Island | 0.0700 | 130 | 38_44_N_27_19_W | |
| 13 | A*11:01 | Belgium | 9.4 | 0.0470 | 99 | 50_50_N_4_21_E |
| 14 | A*11:01 | Brazil Puyanawa | 10.7 | 0.0530 | 150 | 10_52_S_53_5_W |
| 15 | A*11:01 | Brazil Belo Horizonte Caucasian | 4.2 | 0.0260 | 95 | 19_55_S_43_56_W |
| 16 | A*11:01 | Brazil Mixed | 0.0610 | 108 | 23_10_S_47_48_W | |
| 17 | A*11:01 | Brazil Vale do Ribeira Quilombos | 0.0 | 0.0000 | 144 | 24_36_S_48_15_W |
| 18 | A*11:01 | Bulgaria Romani | 0.2080 | 13 | 42_44_N_23_20_E | |
| 19 | A*11:01 | Chile Easter Island | 0.3810 | 21 | 27_7_S_109_22_W | |
| 20 | A*11:01 | Chile Mapuche | 0.0154 | 66 | 37_48_S_73_23_W | |
| 21 | A*11:01 | Chile Santiago Mixed | 2.0 | 70 | 33_26_S_70_39_W | |
| 22 | A*11:01 | China Beijing | 0.1640 | 67 | 39_58_N_116_24_E | |
| 23 | A*11:01 | China Beijing Shijiazhuang Tianjian Han | 0.2020 | 618 | 39_54_N_116_24_E | |
| 24 | A*11:01 | China Canton Han | 0.2670 | 264 | 23_6_N_113_15_E | |
| 25 | A*11:01 | China Guangxi Region Maonan | 0.3520 | 108 | 23_48_N_108_59_E | |
| 26 | A*11:01 | China Guangzhou | 0.3380 | 102 | 23_6_N_113_15_E | |
| 27 | A*11:01 | China Guizhou Province Bouyei | 0.3140 | 109 | 26_50_N_106_50_E | |
| 28 | A*11:01 | China Guizhou Province Miao pop 2 | 0.3590 | 85 | 26_50_N_106_50_E | |
| 29 | A*11:01 | China Guizhou Province Shui | 0.2950 | 153 | 26_50_N_106_50_E | |
| 30 | A*11:01 | China Han HIV negative | 0.0940 | 72 | 36_34_N_103_49_E | |
| 31 | A*11:01 | China Henan HIV negative | 0.0940 | 16 | 34_0_N_113_40_E | |
| 32 | A*11:01 | China Hubei Han | 52.3 | 0.2617 | 3,732 | 30_45_N_114_15_E |
| 33 | A*11:01 | China Inner Mongolia Region | 0.1620 | 102 | 36_0_N_102_0_E | |
| 34 | A*11:01 | China Jiangsu Han | 0.1650 | 3,238 | 32_54_N_119_48_E | |
| 35 | A*11:01 | China Jiangsu Province Han | 0.1777 | 334 | 32_54_N_119_48_E | |
| 36 | A*11:01 | China Marrow Donor Registry | 0.2700 | 600 | 39_54_N_116_23_E | |
| 37 | A*11:01 | China North Han | 0.0000 | 105 | 39_54_N_116_24_E | |
| 38 | A*11:01 | China Qinghai Province Hui | 0.1590 | 110 | 36_0_N_102_0_E | |
| 39 | A*11:01 | China Shanxi HIV negative | 0.1820 | 22 | 36_5_N_111_50_E | |
| 40 | A*11:01 | China Sichuan HIV negative | 0.1760 | 34 | 30_50_N_102_49_E | |
| 41 | A*11:01 | China South Han | 0.2770 | 284 | 23_1_N_113_3_E | |
| 42 | A*11:01 | China Southwest Dai | 0.3910 | 124 | 22_0_N_100_48_E | |
| 43 | A*11:01 | China Uyghur HIV negative | 0.1050 | 19 | 36_34_N_103_49_E | |
| 44 | A*11:01 | China Yunnan Bulang | 0.5430 | 116 | 21_57_N_100_27_E | |
| 45 | A*11:01 | China Yunnan Hani | 0.6130 | 150 | 21_59_N_100_49_E | |
| 46 | A*11:01 | China Yunnan Province Han | 0.3170 | 101 | 24_2_N_105_3_E | |
| 47 | A*11:01 | Colombia Bogotá Cord Blood | 8.5 | 0.0427 | 1,463 | 4_39_N_73_52_W |
| 48 | A*11:01 | Colombia North Wiwa El Encanto | 0.0192 | 52 | 10_10_N_73_53_W | |
| 49 | A*11:01 | Croatia | 0.0400 | 150 | 45_0_N_15_0_E | |
| 50 | A*11:01 | Croatia pop 4 | 0.0691 | 4,000 | 45_48_N_15_57_E | |
| 51 | A*11:01 | Cuba Caucasian | 10.0 | 0.0570 | 70 | 23_8_N_82_22_W |
| 52 | A*11:01 | Cuba Mixed Race | 0.0 | 0.0000 | 42 | 23_8_N_82_22_W |
| 53 | A*11:01 | Czech Republic | 0.0330 | 106 | 50_0_N_14_0_E | |
| 54 | A*11:01 | Czech Republic NMDR | 0.0566 | 5,099 | 49_48_N_15_30_E | |
| 55 | A*11:01 | Ecuador Amerindians | 0.0476 | 63 | 0_13_S_78_30_W | |
| 56 | A*11:01 | England North West | 13.1 | 0.0700 | 298 | 53_0_N_3_0_W |
| 57 | A*11:01 | Finland | 0.0500 | 91 | 63_29_N_25_16_E | |
| 58 | A*11:01 | France French Bone Marrow Donor Registry | 0.0500 | 42,623 | 48_51_N_2_21_E | |
| 59 | A*11:01 | France Southeast | 8.5 | 0.0430 | 130 | 46_0_N_5_0_E |
| 60 | A*11:01 | Gaza | 14.3 | 0.0714 | 42 | 31_22_N_34_18_E |
| 61 | A*11:01 | Georgia Svaneti Region Svan | 0.1250 | 80 | 42_54_N_43_0_E | |
| 62 | A*11:01 | Georgia Tibilisi | 0.0620 | 109 | 41_41_N_44_57_E | |
| 63 | A*11:01 | Georgia Tibilisi Kurd | 0.1000 | 31 | 41_41_N_44_57_E | |
| 64 | A*11:01 | Germany DKMS - Austria minority | 0.0558 | 1,698 | 48_31_N_9_3_E | |
| 65 | A*11:01 | Germany DKMS - Bosnia and Herzegovina minority | 0.0627 | 1,028 | 48_31_N_9_3_E | |
| 66 | A*11:01 | Germany DKMS - China minority | 0.1929 | 1,282 | 48_31_N_9_3_E | |
| 67 | A*11:01 | Germany DKMS - Croatia minority | 0.0756 | 2,057 | 48_31_N_9_3_E | |
| 68 | A*11:01 | Germany DKMS - France minority | 0.0594 | 1,406 | 48_31_N_9_3_E | |
| 69 | A*11:01 | Germany DKMS - German donors | 0.0528 | 3,456,066 | 48_31_N_9_3_E | |
| 70 | A*11:01 | Germany DKMS - Greece minority | 0.0628 | 1,894 | 48_31_N_9_3_E | |
| 71 | A*11:01 | Germany DKMS - Italy minority | 0.0542 | 1,159 | 48_31_N_9_3_E | |
| 72 | A*11:01 | Germany DKMS - Netherlands minority | 0.0510 | 1,374 | 48_31_N_9_3_E | |
| 73 | A*11:01 | Germany DKMS - Portugal minority | 0.0689 | 1,176 | 48_31_N_9_3_E | |
| 74 | A*11:01 | Germany DKMS - Romania minority | 0.0584 | 1,234 | 48_31_N_9_3_E | |
| 75 | A*11:01 | Germany DKMS - Spain minority | 0.0628 | 1,107 | 48_31_N_9_3_E | |
| 76 | A*11:01 | Germany DKMS - Turkey minority | 0.0748 | 4,856 | 48_31_N_9_3_E | |
| 77 | A*11:01 | Germany DKMS - United Kingdom minority | 0.0647 | 1,043 | 48_31_N_9_3_E | |
| 78 | A*11:01 | Germany pop 6 | 0.0507 | 8,862 | 51_6_N_10_23_E | |
| 79 | A*11:01 | Germany pop 8 | 0.0563 | 39,689 | 48_24_N_9_58_E | |
| 80 | A*11:01 | Greece pop 6 | 0.0682 | 242 | 37_58_N_23_43_E | |
| 81 | A*11:01 | Greece pop 8 | 12.1 | 0.0723 | 83 | 37_58_N_23_43_E |
| 82 | A*11:01 | Hong Kong Chinese | 48.8 | 0.2870 | 569 | 22_16_N_114_9_E |
| 83 | A*11:01 | Hong Kong Chinese BMDR | 0.2968 | 7,595 | 22_15_N_114_10_E | |
| 84 | A*11:01 | Hong Kong Chinese cord blood registry | 0.2978 | 3,892 | 22_15_N_114_10_E | |
| 85 | A*11:01 | India Andhra Pradesh Golla | 0.1190 | 111 | 17_5_N_78_5_E | |
| 86 | A*11:01 | India Central UCBB | 30.2 | 0.1509 | 4,204 | 27_1_N_81_19_E |
| 87 | A*11:01 | India Delhi pop 2 | 18.9 | 0.0940 | 90 | 28_36_N_77_13_E |
| 88 | A*11:01 | India East UCBB | 33.0 | 0.1825 | 2,403 | 22_25_N_88_18_E |
| 89 | A*11:01 | India Mumbai Maratha | 0.1230 | 91 | 18_58_N_72_49_E | |
| 90 | A*11:01 | India New Delhi | 0.2350 | 71 | 28_37_N_77_13_E | |
| 91 | A*11:01 | India North pop 2 | 0.1250 | 72 | 25_0_N_74_0_E | |
| 92 | A*11:01 | India North UCBB | 29.0 | 0.1588 | 5,849 | 28_36_N_77_11_E |
| 93 | A*11:01 | India Northeast UCBB | 54.7 | 0.3226 | 296 | 26_16_N_91_48_E |
| 94 | A*11:01 | India South UCBB | 26.8 | 0.1453 | 11,446 | 13_6_N_80_8_E |
| 95 | A*11:01 | India Tamil Nadu | 0.1359 | 2,492 | 11_32_N_78_52_E | |
| 96 | A*11:01 | India West UCBB | 27.4 | 0.1481 | 5,829 | 19_11_N_73_3_E |
| 97 | A*11:01 | Indonesia Java Western | 30.1 | 236 | 7_30_S_111_15_E | |
| 98 | A*11:01 | Iran Gorgan | 0.0550 | 64 | 36_50_N_54_43_E | |
| 99 | A*11:01 | Iran Kurd pop 2 | 0.0830 | 60 | 36_17_N_46_17_E | |
| 100 | A*11:01 | Iran Saqqez-Baneh Kurds | 0.0833 | 60 | 36_14_N_46_16_E | |
| 101 | A*11:01 | Iran Tabriz Azeris | 0.0619 | 97 | 38_4_N_46_17_E | |
| 102 | A*11:01 | Iran Yazd | 0.1161 | 56 | 31_53_N_54_21_E | |
| 103 | A*11:01 | Ireland Northern | 15.0 | 0.0800 | 1,000 | 54_40_N_6_45_W |
| 104 | A*11:01 | Ireland South | 11.2 | 0.0620 | 250 | 53_20_N_6_15_W |
| 105 | A*11:01 | Israel Arab Druze | 0.1100 | 101 | 31_8_N_35_2_E | |
| 106 | A*11:01 | Israel Arab pop 2 | 0.0513 | 12,301 | 32_8_N_34_52_E | |
| 107 | A*11:01 | Israel Argentina Jews | 0.0571 | 4,307 | 32_8_N_34_52_E | |
| 108 | A*11:01 | Israel Ashkenazi and Non Ashkenazi Jews | 0.0640 | 146 | 31_8_N_35_2_E | |
| 109 | A*11:01 | Israel Ashkenazi Jews pop 3 | 0.0523 | 4,625 | 32_8_N_34_52_E | |
| 110 | A*11:01 | Israel Bukhara Jews | 0.0276 | 2,317 | 32_8_N_34_52_E | |
| 111 | A*11:01 | Israel Druze | 0.0690 | 5,914 | 32_41_N_35_17_E | |
| 112 | A*11:01 | Israel Ethiopia Jews | 0.0012 | 5,928 | 32_8_N_34_52_E | |
| 113 | A*11:01 | Israel Georgia Jews | 0.0357 | 4,471 | 32_10_N_34_53_E | |
| 114 | A*11:01 | Israel Iran Jews | 0.0724 | 8,153 | 32_8_N_34_52_E | |
| 115 | A*11:01 | Israel Iraq Jews | 0.0936 | 13,270 | 32_10_N_34_52_E | |
| 116 | A*11:01 | Israel Kavkazi Jews | 0.0296 | 2,840 | 32_10_N_34_52_E | |
| 117 | A*11:01 | Israel Libya Jews | 0.0999 | 3,739 | 32_10_N_34_52_E | |
| 118 | A*11:01 | Israel Morocco Jews | 0.0365 | 36,718 | 32_10_N_34_52_E | |
| 119 | A*11:01 | Israel Poland Jews | 0.0518 | 13,871 | 32_10_N_34_52_E | |
| 120 | A*11:01 | Israel Tunisia Jews | 0.0748 | 9,070 | 32_10_N_34_52_E | |
| 121 | A*11:01 | Israel USA Jews | 0.0541 | 6,058 | 32_10_N_34_52_E | |
| 122 | A*11:01 | Israel USSR Jews | 0.0557 | 45,681 | 32_9_N_34_50_E | |
| 123 | A*11:01 | Israel YemenJews | 0.0247 | 15,542 | 32_9_N_34_50_E | |
| 124 | A*11:01 | Italy North pop 3 | 15.4 | 0.0770 | 97 | 43_0_N_12_0_E |
| 125 | A*11:01 | Italy pop 5 | 0.0460 | 975 | 45_28_N_9_11_E | |
| 126 | A*11:01 | Japan Central | 0.0820 | 371 | 35_41_N_139_46_E | |
| 127 | A*11:01 | Japan Hokkaido Ainu | 0.0100 | 50 | 43_0_N_142_0_E | |
| 128 | A*11:01 | Japan pop 16 | 0.0912 | 18,604 | 35_41_N_139_46_E | |
| 129 | A*11:01 | Japan pop 3 | 0.1020 | 1,018 | 35_41_N_139_46_E | |
| 130 | A*11:01 | Japan pop 5 | 0.1110 | 117 | 35_41_N_139_46_E | |
| 131 | A*11:01 | Jordan Amman | 0.0790 | 146 | 31_35_N_36_20_E | |
| 132 | A*11:01 | Kenya Luo | 0.0000 | 265 | 0_0_S_34_6_E | |
| 133 | A*11:01 | Kenya Nandi | 0.0000 | 240 | 0_0_S_35_0_E | |
| 134 | A*11:01 | Kosovo | 8.1 | 0.0403 | 124 | 42_34_N_21_0_E |
| 135 | A*11:01 | Macedonia pop 4 | 0.0490 | 216 | 42_0_N_21_0_E | |
| 136 | A*11:01 | Malaysia Champa | 27.6 | 0.1720 | 29 | 2_30_N_112_30_E |
| 137 | A*11:01 | Malaysia Jelebu Temuan | 0.2710 | 25 | 2_56_N_102_5_E | |
| 138 | A*11:01 | Malaysia Kedah Baling Kensiu | 0.3400 | 25 | 5_40_N_100_55_E | |
| 139 | A*11:01 | Malaysia Kedah Kensiu | 28.6 | 0.1430 | 21 | 5_40_N_100_55_E |
| 140 | A*11:01 | Malaysia Kelantan | 21.4 | 0.1610 | 28 | 2_30_N_112_30_E |
| 141 | A*11:01 | Malaysia Mandailing | 22.2 | 0.1300 | 27 | 2_30_N_112_30_E |
| 142 | A*11:01 | Malaysia Pahang Semai | 7.9 | 0.0390 | 38 | 4_11_N_102_3_E |
| 143 | A*11:01 | Malaysia Patani | 20.0 | 0.1200 | 25 | 2_30_N_112_30_E |
| 144 | A*11:01 | Malaysia Peninsular Chinese | 50.0 | 0.2964 | 194 | 3_9_N_101_57_E |
| 145 | A*11:01 | Malaysia Peninsular Indian | 24.4 | 0.1310 | 271 | 3_9_N_101_57_E |
| 146 | A*11:01 | Malaysia Peninsular Malay | 30.7 | 0.1714 | 951 | 3_9_N_101_57_E |
| 147 | A*11:01 | Malaysia Perak Grik Jehai | 0.0400 | 25 | 5_25_N_101_8_E | |
| 148 | A*11:01 | Malaysia Sarawak Bau Bidayuh | 0.1000 | 25 | 1_25_N_110_9_E | |
| 149 | A*11:01 | Mali Bandiagara | 0.0000 | 138 | 14_4_N_3_6_W | |
| 150 | A*11:01 | Mexico Chihuahua Chihuahua City Pop 2 | 6.8 | 0.0341 | 88 | 28_48_N_106_26_W |
| 151 | A*11:01 | Mexico Mestizo | 7.3 | 0.0370 | 41 | 19_24_N_99_9_W |
| 152 | A*11:01 | Mexico Mexico City Mestizo pop 2 | 0.0214 | 234 | 19_26_N_99_8_W | |
| 153 | A*11:01 | Mexico Mexico City Mestizo population | 0.0524 | 143 | 19_25_N_99_7_W | |
| 154 | A*11:01 | Mexico Mexico City Tlalpan | 5.5 | 0.0273 | 330 | 19_25_N_99_8_W |
| 155 | A*11:01 | Mexico Mixtec | 0.0050 | 97 | 23_57_N_103_29_W | |
| 156 | A*11:01 | Mexico Oaxaca Jamiltepec Mixtec | 0.0050 | 96 | 16_25_N_97_58_W | |
| 157 | A*11:01 | Mexico Oaxaca Mixtec | 0.0290 | 103 | 17_5_N_96_45_W | |
| 158 | A*11:01 | Mexico Oaxaca Zapotec | 0.0000 | 90 | 17_5_N_96_45_W | |
| 159 | A*11:01 | Mexico Tixcacaltuyub Maya | 0.0299 | 67 | 20_29_N_88_54_W | |
| 160 | A*11:01 | Mexico Veracruz Xalapa | 3.6 | 0.0179 | 84 | 19_32_N_96_55_W |
| 161 | A*11:01 | Netherlands Leiden | 0.0520 | 1,305 | 52_9_N_4_31_E | |
| 162 | A*11:01 | Netherlands UMCU | 9.4 | 0.0469 | 64 | 52_5_N_5_10_E |
| 163 | A*11:01 | New Caledonia | 0.1310 | 65 | 21_0_S_165_0_E | |
| 164 | A*11:01 | New Zealand Maori with Admixed History | 29.5 | 0.1670 | 105 | 42_0_S_174_0_E |
| 165 | A*11:01 | New Zealand Maori with Full Ancestry | 30.4 | 0.1630 | 46 | 42_0_S_174_0_E |
| 166 | A*11:01 | New Zealand Polynesians with Admixed History | 29.6 | 0.1480 | 27 | 42_0_S_174_0_E |
| 167 | A*11:01 | New Zealand Polynesians with Full Ancestry | 38.1 | 0.1910 | 21 | 42_0_S_174_0_E |
| 168 | A*11:01 | Nicaragua Managua | 5.1 | 0.0254 | 339 | 12_7_N_86_10_W |
| 169 | A*11:01 | Oman | 21.2 | 0.1140 | 118 | 22_0_N_56_0_E |
| 170 | A*11:01 | Pakistan Baloch | 0.2220 | 66 | 30_0_N_67_0_E | |
| 171 | A*11:01 | Pakistan Brahui | 0.2520 | 104 | 30_0_N_67_0_E | |
| 172 | A*11:01 | Pakistan Burusho | 0.1250 | 92 | 36_0_N_73_0_E | |
| 173 | A*11:01 | Pakistan Kalash | 0.0080 | 69 | 32_0_N_70_0_E | |
| 174 | A*11:01 | Pakistan Karachi Parsi | 0.1280 | 91 | 24_49_N_66_59_E | |
| 175 | A*11:01 | Pakistan Mixed Pathan | 0.1630 | 100 | 32_0_N_70_0_E | |
| 176 | A*11:01 | Pakistan Mixed Sindhi | 0.1960 | 101 | 24_0_N_68_0_E | |
| 177 | A*11:01 | Panama | 0.0305 | 462 | 8_59_N_79_37_W | |
| 178 | A*11:01 | Papua New Guinea East New Britain Rabaul | 0.2600 | 60 | 4_12_S_152_11_E | |
| 179 | A*11:01 | Papua New Guinea Eastern Highlands Goroka Asaro | 0.0260 | 57 | 6_5_S_145_23_E | |
| 180 | A*11:01 | Papua New Guinea Karimui Plateau Pawaia | 0.1790 | 80 | 7_14_S_145_20_E | |
| 181 | A*11:01 | Papua New Guinea Madang | 0.6360 | 65 | 5_13_S_145_48_E | |
| 182 | A*11:01 | Papua New Guinea West Schrader Ranges Haruai | 0.5500 | 55 | 5_5_S_144_10_E | |
| 183 | A*11:01 | Papua New Guinea Wosera Abelam | 0.3850 | 131 | 3_48_S_143_2_E | |
| 184 | A*11:01 | Philippines Ivatan | 14.0 | 0.0700 | 50 | 20_22_N_121_56_E |
| 185 | A*11:01 | Poland | 0.0680 | 200 | 51_7_N_17_2_E | |
| 186 | A*11:01 | Poland DKMS | 0.0623 | 20,653 | 52_8_N_19_23_E | |
| 187 | A*11:01 | Portugal Azores Terceira Island | 13.2 | 0.0702 | 130 | 38_43_N_27_13_W |
| 188 | A*11:01 | Portugal Center | 0.0500 | 50 | 39_0_N_8_0_W | |
| 189 | A*11:01 | Portugal North | 0.0540 | 46 | 41_0_N_8_0_W | |
| 190 | A*11:01 | Portugal South | 0.1330 | 49 | 37_0_N_8_0_W | |
| 191 | A*11:01 | Romania | 15.8 | 0.0820 | 348 | 46_0_N_25_0_E |
| 192 | A*11:01 | Russia Belgorod region | 0.7 | 0.0033 | 153 | 50_46_N_37_27_E |
| 193 | A*11:01 | Russia Bering Island Aleuts | 0.0433 | 104 | 55_0_N_166_15_E | |
| 194 | A*11:01 | Russia Karelia | 0.0628 | 1,075 | 63_9_N_32_59_E | |
| 195 | A*11:01 | Russia Nizhny Novgorod, Russians | 0.5 | 0.0023 | 1,510 | 56_19_N_43_59_E |
| 196 | A*11:01 | Russia Tuva pop 2 | 0.0870 | 169 | 51_30_N_95_5_E | |
| 197 | A*11:01 | Russian Federation Vologda Region | 3.4 | 0.0168 | 119 | 59_13_N_39_54_E |
| 198 | A*11:01 | Sao Tome Island Angolar | 0.0310 | 32 | 0_20_N_6_44_E | |
| 199 | A*11:01 | Sao Tome Island Forro | 0.0000 | 66 | 0_20_N_6_44_E | |
| 200 | A*11:01 | Saudi Arabia Guraiat and Hail | 5.6 | 0.0280 | 213 | 27_31_N_41_41_E |
| 201 | A*11:01 | Singapore Chinese | 47.7 | 0.2650 | 149 | 1_24_N_103_45_E |
| 202 | A*11:01 | Singapore Chinese Han | 0.2150 | 94 | 1_17_N_103_51_E | |
| 203 | A*11:01 | Singapore Javaneses | 0.1400 | 51 | 1_24_N_103_45_E | |
| 204 | A*11:01 | Singapore Riau Malay | 0.1770 | 132 | 1_24_N_103_45_E | |
| 205 | A*11:01 | Singapore SGVP Chinese CHS | 0.2930 | 96 | 1_21_N_103_50_E | |
| 206 | A*11:01 | Singapore SGVP Malay MAS | 0.2140 | 89 | 1_21_N_103_50_E | |
| 207 | A*11:01 | Singapore SGVP. Indian INS | 0.1740 | 86 | 1_21_N_103_50_E | |
| 208 | A*11:01 | Singapore Thai | 0.2600 | 100 | 1_24_N_103_45_E | |
| 209 | A*11:01 | South Africa Natal Tamil | 0.1800 | 51 | 30_0_S_31_0_E | |
| 210 | A*11:01 | South Africa Natal Zulu | 0.0 | 0.0000 | 100 | 29_0_S_31_0_E |
| 211 | A*11:01 | South Africa Worcester | 5.0 | 0.0250 | 159 | 33_39_S_19_27_E |
| 212 | A*11:01 | South Korea pop 10 | 0.1025 | 4,128 | 37_33_N_126_58_E | |
| 213 | A*11:01 | South Korea pop 3 | 0.1080 | 485 | 37_33_N_126_59_E | |
| 214 | A*11:01 | Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, | 13.5 | 0.0704 | 4,335 | 41_22_N_2_11_E |
| 215 | A*11:01 | Sri Lanka Colombo | 26.5 | 0.1400 | 714 | 6_56_N_79_50_E |
| 216 | A*11:01 | Sri Lanka Colombo Sinhalese | 0.1040 | 101 | 6_56_N_79_50_E | |
| 217 | A*11:01 | Sudan Central Shaigiya Mixed | 2.7 | 36 | 18_0_N_33_0_E | |
| 218 | A*11:01 | Sudan Mixed | 3.5 | 0.0180 | 200 | 5_0_N_35_0_E |
| 219 | A*11:01 | Sweden Northern Sami | 0.0100 | 154 | 67_0_N_18_30_E | |
| 220 | A*11:01 | Sweden Southern Sami | 0.0580 | 130 | 60_52_N_14_44_E | |
| 221 | A*11:01 | Taiwan Ami | 5.1 | 0.0260 | 98 | 23_0_N_121_0_E |
| 222 | A*11:01 | Taiwan Atayal | 15.1 | 0.0800 | 106 | 24_0_N_121_0_E |
| 223 | A*11:01 | Taiwan Bunun | 18.8 | 0.0990 | 101 | 23_46_N_121_0_E |
| 224 | A*11:01 | Taiwan Hakka | 60.0 | 0.4000 | 55 | 24_0_N_121_0_E |
| 225 | A*11:01 | Taiwan Han Chinese | 0.3260 | 504 | 23_46_N_121_0_E | |
| 226 | A*11:01 | Taiwan Minnan pop 1 | 54.9 | 0.3090 | 102 | 24_0_N_121_0_E |
| 227 | A*11:01 | Taiwan Paiwan | 3.9 | 0.0200 | 51 | 23_0_N_121_0_E |
| 228 | A*11:01 | Taiwan Pazeh | 50.9 | 0.2820 | 55 | 25_0_N_121_30_E |
| 229 | A*11:01 | Taiwan pop 2 | 0.2730 | 364 | 23_46_N_121_0_E | |
| 230 | A*11:01 | Taiwan pop 3 | 0.2930 | 212 | 23_46_N_121_0_E | |
| 231 | A*11:01 | Taiwan Puyuma | 4.0 | 0.0200 | 50 | 23_0_N_121_0_E |
| 232 | A*11:01 | Taiwan Rukai | 8.0 | 0.0400 | 50 | 23_0_N_121_0_E |
| 233 | A*11:01 | Taiwan Saisiat | 21.6 | 0.1180 | 51 | 24_0_N_121_0_E |
| 234 | A*11:01 | Taiwan Siraya | 33.3 | 0.1760 | 51 | 24_0_N_121_0_E |
| 235 | A*11:01 | Taiwan Tao | 62.0 | 0.3600 | 50 | 24_0_N_121_0_E |
| 236 | A*11:01 | Taiwan Taroko | 14.5 | 0.0730 | 55 | 24_0_N_121_0_E |
| 237 | A*11:01 | Taiwan Thao | 43.3 | 0.2170 | 30 | 24_0_N_121_0_E |
| 238 | A*11:01 | Taiwan Tsou | 21.6 | 0.1080 | 51 | 24_0_N_121_0_E |
| 239 | A*11:01 | Taiwan Tzu Chi Morrow Donor Registry | 0.2375 | 46,682 | 25_2_N_121_38_E | |
| 240 | A*11:01 | Taiwan Tzu Chi Morrow Donor Registry Aborigine | 0.1588 | 233 | 25_2_N_121_38_E | |
| 241 | A*11:01 | Taiwan Tzu Chi Cord Blood Bank | 0.2750 | 710 | 23_46_N_121_0_E | |
| 242 | A*11:01 | Thailand | 0.2990 | 142 | 16_7_N_102_0_E | |
| 243 | A*11:01 | Tunisia | 9.0 | 0.0450 | 100 | 35_0_N_9_0_E |
| 244 | A*11:01 | Tunisia Gabes | 0.0421 | 95 | 33_53_N_10_6_E | |
| 245 | A*11:01 | Uganda Kampala | 0.0430 | 161 | 0_3_N_32_6_E | |
| 246 | A*11:01 | United Arab Emirates Abu Dhabi | 0.0577 | 52 | 24_28_N_54_22_E | |
| 247 | A*11:01 | USA African American | 0.0240 | 252 | 30_0_N_95_0_W | |
| 248 | A*11:01 | USA African American Bethesda | 0.0 | 0.0000 | 187 | 38_0_N_78_0_W |
| 249 | A*11:01 | USA African American pop 2 | 0.0030 | 149 | 32_46_N_96_46_W | |
| 250 | A*11:01 | USA African American pop 4 | 0.0158 | 2,411 | 44_58_N_93_15_W | |
| 251 | A*11:01 | USA Alaska Yupik | 0.0080 | 252 | 60_48_N_161_26_W | |
| 252 | A*11:01 | USA Asian | 0.2300 | 358 | 30_0_N_95_0_W | |
| 253 | A*11:01 | USA Asian pop 2 | 0.1790 | 1,772 | 44_58_N_93_15_W | |
| 254 | A*11:01 | USA Caucasian Bethesda | 14.0 | 0.0700 | 307 | 38_0_N_78_0_W |
| 255 | A*11:01 | USA Caucasian pop 2 | 0.0700 | 265 | 30_0_N_95_0_W | |
| 256 | A*11:01 | USA Caucasian pop 3 | 0.0740 | 88 | 32_46_N_96_48_W | |
| 257 | A*11:01 | USA Caucasian pop 4 | 0.0561 | 1,070 | 38_53_N_77_2_W | |
| 258 | A*11:01 | USA Eastern European | 0.0630 | 558 | 38_53_N_77_2_W | |
| 259 | A*11:01 | USA Hawaii Okinawa | 0.0670 | 106 | 21_0_N_157_0_W | |
| 260 | A*11:01 | USA Hispanic | 0.0580 | 234 | 30_0_N_95_0_W | |
| 261 | A*11:01 | USA Hispanic pop 2 | 0.0462 | 1,999 | 44_58_N_93_15_W | |
| 262 | A*11:01 | USA NMDP African | 0.0112 | 28,557 | 38_45_N_76_6_W | |
| 263 | A*11:01 | USA NMDP African American pop 2 | 0.0142 | 416,581 | 38_45_N_76_6_W | |
| 264 | A*11:01 | USA NMDP Alaska Native or Aleut | 0.0360 | 1,376 | 38_45_N_76_6_W | |
| 265 | A*11:01 | USA NMDP American Indian South or Central America | 0.0510 | 5,926 | 38_45_N_76_6_W | |
| 266 | A*11:01 | USA NMDP Caribean Black | 0.0156 | 33,328 | 38_45_N_76_6_W | |
| 267 | A*11:01 | USA NMDP Caribean Hispanic | 0.0412 | 115,374 | 38_45_N_76_6_W | |
| 268 | A*11:01 | USA NMDP Caribean Indian | 0.0440 | 14,339 | 38_45_N_76_6_W | |
| 269 | A*11:01 | USA NMDP Chinese | 0.2752 | 99,672 | 38_45_N_76_6_W | |
| 270 | A*11:01 | USA NMDP European Caucasian | 0.0609 | 1,242,890 | 38_45_N_76_6_W | |
| 271 | A*11:01 | USA NMDP Filipino | 0.1792 | 50,614 | 38_45_N_76_6_W | |
| 272 | A*11:01 | USA NMDP Hawaiian or other Pacific Islander | 0.1357 | 11,499 | 38_45_N_76_6_W | |
| 273 | A*11:01 | USA NMDP Hispanic South or Central American | 0.0456 | 146,714 | 38_45_N_76_6_W | |
| 274 | A*11:01 | USA NMDP Japanese | 0.0874 | 24,582 | 38_45_N_76_6_W | |
| 275 | A*11:01 | USA NMDP Korean | 0.1021 | 77,584 | 38_45_N_76_6_W | |
| 276 | A*11:01 | USA NMDP Mexican or Chicano | 0.0484 | 261,235 | 38_45_N_76_6_W | |
| 277 | A*11:01 | USA NMDP Middle Eastern or North Coast of Africa | 0.0641 | 70,890 | 38_45_N_76_6_W | |
| 278 | A*11:01 | USA NMDP North American Amerindian | 0.0488 | 35,791 | 38_45_N_76_6_W | |
| 279 | A*11:01 | USA NMDP South Asian Indian | 0.1396 | 185,391 | 38_45_N_76_6_W | |
| 280 | A*11:01 | USA NMDP Southeast Asian | 0.1753 | 27,978 | 38_45_N_76_6_W | |
| 281 | A*11:01 | USA NMDP Vietnamese | 0.2466 | 43,540 | 38_45_N_76_6_W | |
| 282 | A*11:01 | USA North American Native | 0.0270 | 187 | 30_0_N_95_0_W | |
| 283 | A*11:01 | USA Philadelphia Caucasian | 12.6 | 0.0700 | 141 | 39_56_N_75_10_W |
| 284 | A*11:01 | USA San Antonio Caucasian | 0.0723 | 222 | 29_23_N_98_33_W | |
| 285 | A*11:01 | USA San Diego | 15.5 | 0.0810 | 496 | 32_50_N_117_15_W |
| 286 | A*11:01 | USA San Francisco Caucasian | 0.0550 | 220 | 37_46_N_122_25_W | |
| 287 | A*11:01 | USA South Texas Hispanic | 0.0730 | 194 | 29_0_N_98_0_W | |
| 288 | A*11:01 | Vietnam Hanoi Kinh pop 2 | 0.2290 | 170 | 21_2_N_105_51_E | |
| 289 | A*11:01 | Zambia Lusaka | 0.0000 | 44 | 15_25_S_28_17_E | |
| 290 | A*11:01:01 | Brazil Barra Mansa Rio State Black | 0.0548 | 73 | 22_32_S_44_10_W | |
| 291 | A*11:01:01 | Brazil Barra Mansa Rio State Caucasian | 0.0605 | 405 | 22_32_S_44_10_W | |
| 292 | A*11:01:01 | Brazil Rio de Janeiro Black | 0.0515 | 68 | 22_54_S_43_12_W | |
| 293 | A*11:01:01 | Brazil Rio de Janeiro Caucasian | 0.0480 | 521 | 22_54_S_43_12_W | |
| 294 | A*11:01:01 | Brazil Rio de Janeiro Parda | 0.0265 | 170 | 22_54_S_43_12_W | |
| 295 | A*11:01:01 | Bulgaria | 0.0730 | 55 | 42_0_N_23_0_E | |
| 296 | A*11:01:01 | Cape Verde Northwestern Islands | 0.0240 | 62 | 16_0_N_24_0_W | |
| 297 | A*11:01:01 | Cape Verde Southeastern Islands | 0.0240 | 62 | 16_0_N_24_0_W | |
| 298 | A*11:01:01 | Chile Huilliche NA-DHS_14 (G) | 5.0 | 0.0250 | 20 | 41_0_S_73_0_W |
| 299 | A*11:01:01 | China Guangdong Province Meizhou Han | 0.3030 | 100 | 24_27_N_116_7_E | |
| 300 | A*11:01:01 | China Jingpo Minority | 70.9 | 0.4850 | 105 | 25_0_N_102_0_E |
| 301 | A*11:01:01 | China North Han | 0.1620 | 105 | 39_54_N_116_24_E | |
| 302 | A*11:01:01 | China Tibet Region Tibetan | 0.1300 | 158 | 29_39_N_91_7_E | |
| 303 | A*11:01:01 | China Yunnan Province Jinuo | 0.3670 | 109 | 24_30_N_101_30_E | |
| 304 | A*11:01:01 | China Yunnan Province Lisu | 0.4550 | 111 | 24_30_N_101_30_E | |
| 305 | A*11:01:01 | China Yunnan Province Nu | 0.4810 | 107 | 24_30_N_101_30_E | |
| 306 | A*11:01:01 | China Yunnan Province Wa | 0.5840 | 119 | 24_30_N_101_30_E | |
| 307 | A*11:01:01 | China Zhejiang Han | 0.2581 | 1,734 | 27_2_N_118_1_E | |
| 308 | A*11:01:01 | Colombia Embera NA-DHS_19 (G) | 7.1 | 0.0357 | 14 | 7_0_N_76_0_W |
| 309 | A*11:01:01 | Colombia Inga NA-DHS_11 (G) | 13.3 | 0.0667 | 16 | 1_0_N_77_0_W |
| 310 | A*11:01:01 | Costa Rica African -Caribbean (G) | 1.0 | 0.0050 | 102 | 9_59_N_83_1_W |
| 311 | A*11:01:01 | Costa Rica Amerindians (G) | 0.8 | 0.0040 | 125 | 9_34_N_83_25_W |
| 312 | A*11:01:01 | Costa Rica Central Valley Mestizo (G) | 4.6 | 0.0230 | 221 | 9_55_N_84_5_W |
| 313 | A*11:01:01 | Costa Rica Guanacaste Mestizo (G) | 6.4 | 0.0320 | 110 | 10_16_N_85_37_W |
| 314 | A*11:01:01 | England Blood Donors of Mixed Ethnicity | 11.4 | 0.0578 | 519 | 52_21_N_1_10_W |
| 315 | A*11:01:01 | Guatemala Kaqchikel NA-DHS_8 (G) | 5.3 | 0.0263 | 19 | 15_0_N_91_0_W |
| 316 | A*11:01:01 | Guinea Bissau | 0.0000 | 65 | 12_0_N_15_0_W | |
| 317 | A*11:01:01 | Hong Kong Chinese HKBMDR HLA 11 loci | 50.6 | 0.2984 | 5,266 | 22_25_N_114_17_E |
| 318 | A*11:01:01 | India Andhra Pradesh Telugu Speaking | 29.0 | 0.1586 | 186 | 13_4_N_80_14_E |
| 319 | A*11:01:01 | India Karnataka Kannada Speaking | 17.8 | 0.1000 | 174 | 12_57_N_77_36_E |
| 320 | A*11:01:01 | India Kerala Malayalam speaking | 31.2 | 0.1670 | 356 | 13_1_N_80_15_E |
| 321 | A*11:01:01 | India Khandesh Region Pawra | 0.2100 | 50 | 20_54_N_74_46_E | |
| 322 | A*11:01:01 | India Tamil Nadu Nadar | 0.0980 | 61 | 8_0_N_77_0_E | |
| 323 | A*11:01:01 | India West Bhil | 0.0000 | 50 | 20_54_N_74_46_E | |
| 324 | A*11:01:01 | India West Coast Parsi | 0.0900 | 50 | 18_0_N_74_0_E | |
| 325 | A*11:01:01 | Indonesia Java pop 2 | 0.1390 | 36 | 6_8_S_106_10_E | |
| 326 | A*11:01:01 | Indonesia Sundanese and Javanese | 0.1640 | 201 | 6_8_S_106_10_E | |
| 327 | A*11:01:01 | Iran Baloch | 0.1460 | 100 | 29_29_N_60_52_E | |
| 328 | A*11:01:01 | Japan Okinawa Ryukyuan | 0.0560 | 143 | 26_4_N_127_8_E | |
| 329 | A*11:01:01 | Libya Cyrenaica | 0.0250 | 118 | 32_7_N_20_4_E | |
| 330 | A*11:01:01 | Madeira | 0.0590 | 185 | 32_44_N_16_58_W | |
| 331 | A*11:01:01 | Mexico Guadalajara Mestizo pop 2 | 0.0340 | 103 | 20_40_N_103_21_W | |
| 332 | A*11:01:01 | Mexico Hidalgo Mezquital Valley/ Otomi | 2.8 | 0.0139 | 72 | 20_28_N_99_13_W |
| 333 | A*11:01:01 | Mongolia Buryat | 0.0750 | 141 | 47_6_N_118_6_E | |
| 334 | A*11:01:01 | Morocco Atlantic Coast Chaouya | 0.0340 | 98 | 30_22_N_7_22_W | |
| 335 | A*11:01:01 | Morocco Nador Metalsa pop 2 | 0.0480 | 73 | 35_10_N_2_56_W | |
| 336 | A*11:01:01 | Morocco Settat Chaouya | 6.8 | 0.0340 | 98 | 33_0_N_7_36_W |
| 337 | A*11:01:01 | Nicaragua Mestizo (G) | 9.6 | 0.0480 | 155 | 12_40_N_85_13_W |
| 338 | A*11:01:01 | Poland BMR | 11.8 | 0.0608 | 23,595 | 52_0_N_19_22_E |
| 339 | A*11:01:01 | Russia Belgorod region | 12.4 | 0.0654 | 153 | 50_46_N_37_27_E |
| 340 | A*11:01:01 | Russia Bashkortostan, Bashkirs | 5.0 | 0.0250 | 120 | 54_0_N_55_0_E |
| 341 | A*11:01:01 | Russia Bashkortostan, Tatars | 0.5 | 0.0026 | 192 | 54_13_N_56_9_E |
| 342 | A*11:01:01 | Russia Nizhny Novgorod, Russians | 0.1 | 0.0007 | 1,510 | 56_19_N_43_59_E |
| 343 | A*11:01:01 | Russian Federation Vologda Region | 4.2 | 0.0210 | 119 | 59_13_N_39_54_E |
| 344 | A*11:01:01 | Saudi Arabia pop 5 | 3.2 | 0.0158 | 158 | 24_38_N_46_43_E |
| 345 | A*11:01:01 | Saudi Arabia pop 6 (G) | 0.0350 | 28,927 | 23_52_N_45_4_E | |
| 346 | A*11:01:01 | South Africa Caucasians | 0.0600 | 102 | 30_0_S_25_0_E | |
| 347 | A*11:01:01 | South African Black | 2.8 | 0.0141 | 142 | 29_9_S_24_39_E |
| 348 | A*11:01:01 | South African Indian population | 28.0 | 0.1700 | 50 | 29_22_S_24_31_E |
| 349 | A*11:01:01 | South African Mixed ancestry | 10.0 | 0.0600 | 50 | 29_22_S_24_31_E |
| 350 | A*11:01:01 | South Korea pop 3 | 0.0000 | 485 | 37_33_N_126_59_E | |
| 351 | A*11:01:01 | Spain, Canary Islands, Gran canaria island | 10.7 | 0.0581 | 215 | 27_57_N_15_36_W |
| 352 | A*11:01:01 | USA African American pop 3 | 0.0130 | 564 | 38_53_N_77_2_W | |
| 353 | A*11:01:01 | USA Arizona Gila River Pima | 0.0009 | 3,000 | 33_4_N_111_43_W | |
| 354 | A*11:01:01 | USA Arizona Pima | 0.0120 | 100 | 33_0_N_113_0_W | |
| 355 | A*11:01:01 | USA Italy Ancestry | 0.0600 | 273 | 38_0_N_77_0_W | |
| 356 | A*11:01:01 | USA Mexican American Mestizo | 0.0420 | 553 | 38_53_N_77_2_W | |
| 357 | A*11:01:01 | USA San Francisco Caucasian | 0.0550 | 220 | 37_46_N_122_25_W | |
| 358 | A*11:01:01 | USA South Dakota Lakota Sioux | 0.0120 | 302 | 44_30_N_100_0_W | |
| 359 | A*11:01:01 | USA Spain Ancestry | 0.0220 | 279 | 38_0_N_77_0_W | |
| 360 | A*11:01:01 | Vietnam Kinh | 41.0 | 0.2277 | 101 | 14_5_N_108_27_E |
| 361 | A*11:01:01:01 | Russia Bashkortostan, Bashkirs | 4.2 | 0.0208 | 120 | 54_0_N_55_0_E |
| 362 | A*11:01:01:01 | Russia Bashkortostan, Tatars | 15.1 | 0.0807 | 192 | 54_13_N_56_9_E |
| 363 | A*11:01:01:01 | Russia Nizhny Novgorod, Russians | 11.6 | 0.0589 | 1,510 | 56_19_N_43_59_E |
| 364 | A*11:01:02 | Bulgaria | 0.0000 | 55 | 42_0_N_23_0_E | |
| 365 | A*11:01:02 | China North Han | 0.0000 | 105 | 39_54_N_116_24_E | |
| 366 | A*11:01:02 | Morocco Nador Metalsa pop 2 | 0.0000 | 73 | 35_10_N_2_56_W | |
| 367 | A*11:01:02 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 368 | A*11:01:02 | South Korea pop 3 | 0.0000 | 485 | 37_33_N_126_59_E | |
| 369 | A*11:01:03 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 370 | A*11:01:04 | China Zhejiang Han | 0.0003 | 1,734 | 27_2_N_118_1_E | |
| 371 | A*11:01:04 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 372 | A*11:01:05 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 373 | A*11:01:06 | Hong Kong Chinese HKBMDR HLA 11 loci | 0.0 | 0.0001 | 5,266 | 22_25_N_114_17_E |
| 374 | A*11:01:06 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 375 | A*11:01:07 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 376 | A*11:01:07 | Saudi Arabia pop 5 | 0.6 | 0.0032 | 158 | 24_38_N_46_43_E |
| 377 | A*11:01:08 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 378 | A*11:01:09 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 379 | A*11:01:10 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 380 | A*11:01:11 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 381 | A*11:01:12 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 382 | A*11:01:13 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 383 | A*11:01:14 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 384 | A*11:01:15 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 385 | A*11:01:16 | Morocco Settat Chaouya | 0.0 | 0.0000 | 98 | 33_0_N_7_36_W |
| 386 | A*11:01:58 | USA Arizona Gila River Pima | 0.0002 | 3,000 | 33_4_N_111_43_W | |
| 387 | A*11:01:79 | Poland BMR | 0.2 | 0.0011 | 23,595 | 52_0_N_19_22_E |
| 388 | A*11:01:79 | Russia Belgorod region | 0.7 | 0.0033 | 153 | 50_46_N_37_27_E |
| 389 | A*11:01:79 | Russian Federation Vologda Region | 0.8 | 0.0042 | 119 | 59_13_N_39_54_E |
Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools
Gonzalez-Galarza FF, McCabe A, Santos EJ, Jones J, Takeshita LY, Ortega-Rivera ND, Del Cid-Pavon GM, Ramsbottom K, Ghattaoraya GS, Alfirevic A, Middleton D and Jones AR Nucleic Acid Research 2020, 48:D783-8.
Liverpool, U.K.
support@allelefrequencies.net