Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 101 to 200 (from 1,849) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 19  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*26:13-B*40:02-C*03:02-DRB1*12:09-DQB1*03:01  Iran Gorgan 0.780064
 102  A*30:01-B*07:03-C*03:02-DRB1*08:20-DQB1*04:01  Iran Gorgan 0.780064
 103  A*30:01-B*35:01-C*03:02-DRB1*10:01-DQB1*05:01  Iran Gorgan 0.780064
 104  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*06:01  Iran Gorgan 0.780064
 105  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*03:01  Sri Lanka Colombo 0.7703714
 106  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA NMDP Hawaiian or other Pacific Islander 0.732811,499
 107  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.72025,266
 108  B*58:01-C*03:02  Mexico Mexico City Mestizo population 0.6993143
 109  A*01:01:01-B*18:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 110  A*02:01:01-B*35:01:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 111  A*02:01:01-B*40:02:01-C*03:02:01-DRB1*01:03:01-DQB1*05:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 112  A*02:01:01-B*40:02:01-C*03:02:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 113  A*02:01:01-B*40:02:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 114  A*02:01:01-B*51:01:01-C*03:02:01-DRB1*14:02:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 115  A*02:01:01-B*51:01:01-C*03:02:01-DRB1*14:06:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 116  A*31:01:02-B*40:02:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 117  A*31:01:02-B*40:02:01-C*03:02:01-DRB1*14:02:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 118  A*31:01:02-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 119  A*33:03-B*58:01-C*03:02-DRB1*04:01  Brazil Vale do Ribeira Quilombos 0.6944144
 120  A*68:01:01-B*40:02:01-C*03:02:01-DRB1*04:03:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 121  A*68:01:01-B*40:02:01-C*03:02:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 122  A*68:01:01-B*40:02:01-C*03:02:01-DRB1*14:06:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 123  A*33-B*58-C*03:02-DRB1*13:02-DQB1*06  Russia Transbaikal Territory Buryats 0.6670150
 124  A*02:01-B*15:01-C*03:02-DRB1*04:01-DQA1*05:01-DQB1*02:01  Brazil Puyanawa 0.6667150
 125  A*68:01-B*40:02-C*03:02-DRB1*14:02-DQA1*05:03-DQB1*03:02  Brazil Puyanawa 0.6667150
 126  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Southeast Asian 0.658827,978
 127  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP South Asian Indian 0.6448185,391
 128  A*33:03-B*58:01-C*03:02  Italy pop 5 0.6300975
 129  A*02:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 130  A*02:04-B*58:01:01-C*03:02:02-DRB1*04:11:01-DQB1*04:02:01-DPA1*02:01:01-DPB1*14:01:01  Brazil Rio de Janeiro Parda 0.5882170
 131  A*03:01:01-B*35:01:01-C*03:02:02-DRB1*11:01:02-DQB1*03:19:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Parda 0.5882170
 132  A*03:01:01-B*58:01:01-C*03:02:02-DRB1*15:01:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 133  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.57935,829
 134  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.5783951
 135  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.5750174
 136  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*07:01:01-DQB1*06:05:02  India Karnataka Kannada Speaking 0.5750174
 137  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.5620356
 138  B*58:01-C*03:02  USA Hispanic pop 2 0.52701,999
 139  A*02:03:01-B*58:01:01-C*03:02:01-DRB1*15:02:01  China Jingpo Minority 0.5210105
 140  A*11:01:01-B*58:01:01-C*03:02:01-DRB1*03:01:01  China Jingpo Minority 0.5210105
 141  A*24:07-B*58:01:01-C*03:02:01-DRB1*13:02:01  China Jingpo Minority 0.5210105
 142  B*58:01:01-C*03:02:01-DRB1*13:02:01  China Jingpo Minority 0.5210105
 143  A*24:02:01:01-B*40:06:01-C*03:02:02-DRB1*11:01:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.5208192
 144  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 0.5155194
 145  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Chinese 0.5155194
 146  A*33:01-B*58:01-C*03:02-DRB1*16:02-DQB1*05:02  Malaysia Peninsular Chinese 0.5155194
 147  A*11:01:01-C*03:02:01-DRB1*03:01:01  China Jingpo Minority 0.5150105
 148  A*33:03:01-C*03:02:01-DRB1*03:01:01  China Jingpo Minority 0.5150105
 149  A*33:03-B*58:01-C*03:02-DRB1*11:01-DQB1*03:01  India Northeast UCBB 0.5068296
 150  A*01:01-B*58:01-C*03:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*02:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 151  A*02:01-B*58:01-C*03:02-DRB1*03:01-DQA1*01:01-DQB1*02:01-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 152  A*02:14-B*58:01-C*03:02-DRB1*01:02-DQA1*01:01-DQB1*05:01-DPB1*39:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 153  A*29:02-B*58:01-C*03:02-DRB1*11:01-DQA1*01:02-DQB1*03:01-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 154  A*30:01-B*58:01-C*03:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 155  A*66:01-B*35:01-C*03:02-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 156  A*74:01-B*58:01-C*03:02-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*02:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 157  A*74:03-B*82:02-C*03:02-DRB1*01:02-DQA1*01:01-DQB1*05:01-DPB1*17:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 158  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Vietnam Kinh 0.4950101
 159  A*24:02:01-B*58:01:01-C*03:02:02-DRB1*12:02:01-DQB1*02:01:01  Vietnam Kinh 0.4950101
 160  A*32:01:01-B*58:01:01-C*03:02:01  China Jingpo Minority 0.4950105
 161  A*33:03:01-B*15:13:01-C*03:02:02-DRB1*10:01:01-DQB1*03:03:02  Vietnam Kinh 0.4950101
 162  A*33:03:01-B*15:27:01-C*03:02:02-DRB1*11:06:01-DQB1*03:01:01  Vietnam Kinh 0.4950101
 163  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*05:01:01  Vietnam Kinh 0.4950101
 164  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*10:01:01-DQB1*05:01:01  Vietnam Kinh 0.4950101
 165  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*12:02:01-DQB1*03:01:01  Vietnam Kinh 0.4950101
 166  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.490211,446
 167  A*01:02-B*58:01:01-C*03:02:01-DRB1*03:01  Costa Rica African -Caribbean (G) 0.4902102
 168  A*23:01:01-B*15:10:01-C*03:02:01-DRB1*03:01  Costa Rica African -Caribbean (G) 0.4902102
 169  A*29:02:01-B*82:01-C*03:02:01-DRB1*04:05:01  Costa Rica African -Caribbean (G) 0.4902102
 170  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Sri Lanka Colombo 0.4902714
 171  A*34:02:01-B*58:01:01-C*03:02:01-DRB1*13:02:01  Costa Rica African -Caribbean (G) 0.4902102
 172  A*66:02-B*15:03:01-C*03:02:01-DRB1*15:03  Costa Rica African -Caribbean (G) 0.4902102
 173  A*74:01-B*82:01-C*03:02:01-DRB1*16:02:01  Costa Rica African -Caribbean (G) 0.4902102
 174  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Filipino 0.486850,614
 175  A*32:01:01-C*03:02:01  China Jingpo Minority 0.4850105
 176  A*33:01-B*58:01-C*03:02-DRB1*03:01  Russia Bering Island Aleuts 0.4808104
 177  A*68:01-B*40:02-C*03:02-DRB1*04:03  Russia Bering Island Aleuts 0.4808104
 178  A*02:01:01-B*57:02:01-C*03:02:01-DRB1*15:03  Costa Rica Guanacaste Mestizo (G) 0.4545110
 179  A*02:02-B*58:01:01-C*03:02:01-DRB1*11:01:02  Costa Rica Guanacaste Mestizo (G) 0.4545110
 180  A*02:22:01-B*58:01:01-C*03:02:01-DRB1*04:07  Costa Rica Guanacaste Mestizo (G) 0.4545110
 181  A*11:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.44481,734
 182  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  Nicaragua Managua 0.4329339
 183  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*15:01:01-DQB1*06:01:01  India Kerala Malayalam speaking 0.4210356
 184  A*03:01:01-B*40:02:01-C*03:02:02-DRB1*03:01-DQA1*05:05:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 185  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01  Russian Federation Vologda Region 0.4202119
 186  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*11:04:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*05:01:01  Russian Federation Vologda Region 0.4202119
 187  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQA1*01:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01  Russian Federation Vologda Region 0.4202119
 188  B*58:01-C*03:02  Italy pop 5 0.4200975
 189  A*11:01:01:01-B*58:01:01-C*03:02:02-DRB1*04:01:01-DQB1*03:01  Russia Bashkortostan, Bashkirs 0.4167120
 190  A*33:03:01-B*07:02:01-C*03:02:02-DRB1*07:01-DQB1*02:01  Russia Bashkortostan, Bashkirs 0.4167120
 191  A*33:03:01-B*51:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Russia Bashkortostan, Bashkirs 0.4167120
 192  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01  Russia Bashkortostan, Bashkirs 0.4167120
 193  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.40485,266
 194  A*02:01-B*07:02-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*02:01  Kosovo 0.4030124
 195  A*33:01-B*58:01-C*03:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 0.4030124
 196  A*02-B*40-C*03:02-DRB1*04-DQB1*03  Russia North Ossetian 0.3900127
 197  A*02-B*40-C*03:02-DRB1*11-DQB1*03  Russia North Ossetian 0.3900127
 198  A*03-B*40-C*03:02-DRB1*07-DQB1*02  Russia North Ossetian 0.3900127
 199  A*26-B*40-C*03:02-DRB1*13-DQB1*06  Russia North Ossetian 0.3900127
 200  A*30-B*40-C*03:02-DRB1*04-DQB1*03  Russia North Ossetian 0.3900127

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 1,849) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 19  


   

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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