Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
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Displaying 101 to 200 (from 963) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 10  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*68:01:02-B*18:01:01-C*07:04:01-DRB1*13:02:01-DQA1*01:02:01-DQB1*06:09:01-DPA1*02:02:02-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 102  DRB1*13:34-DQB1*06:09  Georgia Caucasus Tbilisi 0.4202119
 103  DRB1*13:01-DQB1*06:09  USA African American pop 4 0.41202,411
 104  DRB1*13:02:01-DQB1*06:09-DPB1*05:01:01  China Inner Mongolia Autonomous Region Northeast 0.4120496
 105  DRB1*13:02-DQB1*06:09  Italy pop 5 0.4100975
 106  DQB1*06:09-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 0.4040496
 107  DRB1*13:02-DQB1*06:09  Cretan Islanders 0.4032124
 108  A*24:02-B*53:01-C*04:01-DRB1*13:02-DQA1*01:02-DQB1*06:09  Kosovo 0.4030124
 109  A*26:01-B*58:01-C*07:02-DRB1*03:01-DQA1*05:01-DQB1*06:09  Kosovo 0.4030124
 110  A*32:01-B*51:08-C*16:02-DRB1*14:54-DQA1*01:01-DQB1*06:09  Kosovo 0.4030124
 111  A*74:01-B*15:03-C*02:02-DRB1*13:02-DQB1*06:09  USA African American pop 4 0.37602,411
 112  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.3680951
 113  DRB1*13:02-DQB1*06:09-DPB1*131:01  Gambia pop 3 0.3628939
 114  DRB1*13:02-DQB1*06:09-DPB1*30:01  Gambia pop 3 0.3628939
 115  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.36155,849
 116  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.35904,204
 117  A*02:01:01-B*44:03:02-C*07:06:01-DRB1*04:01:01-DQB1*06:09:01-DPB1*01:01:01  South African Black 0.3520142
 118  A*30:01:01-B*15:10:01-C*03:04:02-DRB1*13:02:01-DQB1*06:09:01-DPB1*105:01:01  South African Black 0.3520142
 119  A*30:02:01-B*15:220-C*03:02:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*584:01  South African Black 0.3520142
 120  A*30:02:01-B*42:02:01-C*17:01:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*13:01:01  South African Black 0.3520142
 121  A*30:02:02-B*45:07-C*16:01:01-DRB1*13:01:01-DQB1*06:09:01-DPB1*18:01  South African Black 0.3520142
 122  A*30:04:01-B*15:10:01-C*04:01:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*02:01:19  South African Black 0.3520142
 123  A*36:01-B*44:03:02-C*07:06:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*01:01:01  South African Black 0.3520142
 124  A*68:02:01-B*07:02:01-C*04:01:01-DRB1*15:03:01-DQB1*06:09:01-DPB1*11:01:01  South African Black 0.3520142
 125  A*68:02:01-B*15:03:01-C*02:10:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*105:01:01  South African Black 0.3520142
 126  A*74:01:01-B*15:03:01-C*02:10:01-DRB1*13:01:01-DQB1*06:09:01-DPB1*02:01:19  South African Black 0.3520142
 127  A*74:01-B*15:03-C*02:10-DRB1*13:02-DQB1*06:09  Mexico Mexico City Mestizo population 0.3497143
 128  B*15:03-C*02:10-DRB1*13:02-DQB1*06:09  Mexico Mexico City Mestizo population 0.3497143
 129  DRB1*13:02-DQB1*06:09  Mexico Mexico City Mestizo population 0.3497143
 130  DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.34231,064
 131  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.33182,492
 132  DRB1*13:02:01-DQB1*06:09-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.3230496
 133  A*03:01-B*51:01-C*14:02-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.3195336
 134  A*34:02-B*44:03-C*07:01-DRB1*13:02-DQB1*06:09-DPB1*105:01  Tanzania Maasai 0.3195336
 135  A*01:01:01-B*07:05:01-C*07:01:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 136  A*02:01:01-B*51:32-C*16:01:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*104:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 137  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*02:01-DPB1*13:01  China Zhejiang Han pop 2 0.3001833
 138  A*02:01-B*15:10-C*03:04-DRB1*13:01-DQA1*01:03-DQB1*06:09-DPB1*05:01  South Africa Worcester 0.3000159
 139  A*23:01-B*35:01-C*04:01-DRB1*13:02-DQA1*01:01-DQB1*06:09-DPB1*26:01  South Africa Worcester 0.3000159
 140  A*29:01-B*18:01-C*07:04-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 141  A*30:01-B*15:03-C*02:10-DRB1*11:01-DQA1*05:05-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 142  A*68:02-B*15:10-C*03:04-DRB1*13:02-DQA1*02:01-DQB1*06:09-DPB1*04:01  South Africa Worcester 0.3000159
 143  A*68:02-B*18:01-C*06:02-DRB1*01:01-DQA1*05:05-DQB1*06:09-DPB1*105:01  South Africa Worcester 0.3000159
 144  A*68:02-B*42:01-C*17:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 145  A*68:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*03:01  South Africa Worcester 0.3000159
 146  A*68:02-B*58:02-C*06:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 147  A*74:01-B*42:01-C*17:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*105:01  South Africa Worcester 0.3000159
 148  DRB1*13:02-DQB1*06:09-DPB1*105:01  Gambia pop 3 0.2903939
 149  A*01:01:01-B*13:01:01-C*07:02:01-DRB1*13:02:01-DQB1*06:09:01  India Karnataka Kannada Speaking 0.2870174
 150  A*02:01:01-B*55:01:01-C*03:03:01-DRB1*13:02:01-DQB1*06:09:01  India Karnataka Kannada Speaking 0.2870174
 151  A*03:01:01-B*35:01:01-C*03:02:01-DRB1*15:02:01-DQB1*06:09:01  India Karnataka Kannada Speaking 0.2870174
 152  A*24:02:01-B*07:05:01-C*12:03:01-DRB1*13:02:01-DQB1*06:09:01  India Karnataka Kannada Speaking 0.2870174
 153  A*24:02:01-B*35:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  India Karnataka Kannada Speaking 0.2870174
 154  A*68:01:02-B*18:01:01-C*07:06-DRB1*13:02:01-DQB1*06:09:01  India Karnataka Kannada Speaking 0.2870174
 155  A*68:01:02-B*40:06:01-C*12:02:01-DRB1*11:01:01-DQB1*06:09:01  India Karnataka Kannada Speaking 0.2870174
 156  A*30:02:01-B*53:01:01-C*04:01:01-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.2810356
 157  A*32:01-B*35:03-C*04:01-DRB1*13:02-DQB1*06:09  USA NMDP Caribean Indian 0.271314,339
 158  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*04:01  China Zhejiang Han pop 2 0.2711833
 159  DQB1*06:09-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.2690496
 160  A*02:11:01-B*58:01:01-C*04:01:01-DRB1*08:02:01-DQB1*06:09:01  India Andhra Pradesh Telugu Speaking 0.2688186
 161  A*68:01:02-B*51:01:01-C*07:02:01-DRB1*15:01:01-DQB1*06:09:01  India Andhra Pradesh Telugu Speaking 0.2688186
 162  A*23:01:01-B*51:01:01-C*04:01:01-DRB1*14:54:01-DQB1*06:09:01  Russia Bashkortostan, Tatars 0.2604192
 163  A*33:03:01-B*44:02:01:01-C*05:01:01:02-DRB1*13:02:01-DQB1*06:09:01  Russia Bashkortostan, Tatars 0.2604192
 164  A*33:03:01-B*58:01:01-C*08:22-DRB1*13:02:01-DQB1*06:09:01  Russia Bashkortostan, Tatars 0.2604192
 165  A*02:01-B*54:01-C*03:02-DRB1*11:01-DQA1*05:01-DQB1*06:09-DPB1*03:01  USA San Diego 0.2600496
 166  A*33:03-B*35:01-C*04:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  USA San Diego 0.2600496
 167  A*11:01-B*58:01-C*07:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Chinese 0.2577194
 168  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.24182,403
 169  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*104:01  China Zhejiang Han pop 2 0.2401833
 170  DQA1*01:02-DQB1*06:09-DPA1*02:01-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 0.22041,064
 171  DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*04:01  Hong Kong Chinese HKBMDR. DQ and DP 0.21661,064
 172  DRB1*13:02-DQB1*06:09-DPB1*04:02  Gambia pop 3 0.2165939
 173  A*23:01-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Nicaragua Managua 0.2165339
 174  A*29:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Nicaragua Managua 0.2165339
 175  DQB1*06:09-DPB1*05:01:01  China Inner Mongolia Autonomous Region Northeast 0.2130496
 176  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*04:01  Sri Lanka Colombo 0.2101714
 177  A*02:05-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.20504,335
 178  DQB1*06:09-DPB1*09:01:01  China Inner Mongolia Autonomous Region Northeast 0.2020496
 179  DQB1*06:09-DPB1*14:01  China Inner Mongolia Autonomous Region Northeast 0.2020496
 180  DRB1*13:02:01-DQB1*06:09-DPB1*14:01  China Inner Mongolia Autonomous Region Northeast 0.2020496
 181  A*01:01-B*40:01-C*03:04-DRB1*13:02:01-DQB1*06:09  England North West 0.2000298
 182  A*02:01-B*07:02-C*07:02-DRB1*04:01:01-DQB1*06:09  England North West 0.2000298
 183  A*33:03-B*58:01-C*03:02-DRB1*13:02:01-DQB1*06:09  England North West 0.2000298
 184  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*08:03:02-DQB1*06:09:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 185  A*02:05:01-B*49:01:01-C*07:01:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*02:01:07-DPB1*104:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 186  A*24:02:01-B*08:01:01-C*07:01:01-DRB1*15:01:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 187  A*24:02:01-B*57:01:01-C*07:02:01-DRB1*07:01:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*105:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 188  A*26:01:01-B*38:01:01-C*12:03:01-DRB1*15:03:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 189  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 190  A*68:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 191  A*74:01:01-B*15:03:01-C*04:01:01-DRB1*13:01:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 192  A*68:02-B*53:01-C*04:01-DRB1*13:02-DQB1*06:09  USA NMDP Black South or Central American 0.19344,889
 193  A*02:01-B*40:01-C*03:04-DRB1*07:01-DQB1*06:09-DPB1*13:01  Panama 0.1900462
 194  A*02:01-B*51:01-C*06:02-DRB1*04:01-DQB1*06:09-DPB1*04:02  Panama 0.1900462
 195  A*33:01-B*39:11-C*16:01-DRB1*14:02-DQB1*06:09-DPB1*02:01  Panama 0.1900462
 196  A*33:01-B*52:01-C*15:05-DRB1*04:11-DQB1*06:09-DPB1*02:01  Panama 0.1900462
 197  A*01:01-B*13:01-C*04:03-DRB1*15:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 198  A*01:01-B*15:13-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 199  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 200  A*24:02-B*35:04-C*04:01-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271

Notes:

* Haplotype Frequencies: Total number of copies of the haplotype in the population sample (Haplotypes / 2n) shown in percentages (%).
   Important: This field has been expanded to two decimals to better represent frequencies of large datasets (e.g. where sample size > 1000 individuals)
¹ Distribution - Shows the geographic distribution in overlaid maps of the complete haplotype (left icon) or the input alleles if low level resolution was entered (right icon).


Displaying 101 to 200 (from 963) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 10  


   

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.

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