Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

Population:  Country:  Source of dataset : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 101 to 200 (from 212) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01-DQB1*02:01  Costa Rica Central Valley Mestizo (G) 0.9050221
 102  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Jalisco, Zapopan 0.8929168
 103  A*01-B*08-DRB1*03:01-DQB1*02  Ecuador Andes Mixed Ancestry 0.7888824
 104  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Nayarit Rural 0.781264
 105  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Puebla Rural 0.7794833
 106  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Sonora Rural 0.7614197
 107  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP Caribean Black 0.748133,328
 108  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Yucatan Rural 0.7463132
 109  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Mexico City North 0.7304751
 110  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Tabasco Rural 0.7042142
 111  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01  Spain, Canary Islands, Gran canaria island 0.7000215
 112  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Guerrero state 0.6944144
 113  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Oaxaca, Oaxaca city 0.6623151
 114  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Mexico City Metropolitan Area Rural 0.6579150
 115  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.6536153
 116  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:02  Russia Belgorod region 0.6536153
 117  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP African 0.644828,557
 118  A*01-B*08-DRB1*03:01-DQB1*02  Ecuador Mixed Ancestry 0.63941,173
 119  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Tabasco, Villahermosa 0.609882
 120  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*02:01:01-DPB1*10:01:01  Brazil Rio de Janeiro Parda 0.5882170
 121  A*01-B*08-DRB1*03:01-DQB1*02:01  Bolivia La Paz Aymaras 0.575087
 122  A*01-B*08-DRB1*03:01-DQB1*02  Mexico San Luis Potosi Rural 0.574787
 123  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Sinaloa Rural 0.5464183
 124  A*01:01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 0.5208192
 125  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Nayarit, Tepic 0.515597
 126  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:02  Germany DKMS - German donors 0.48783,456,066
 127  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Veracruz Rural 0.4621539
 128  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*03:01  Germany DKMS - German donors 0.45243,456,066
 129  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.43835,829
 130  A*01:01:01-B*08:01:01-C*07:01:01-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
 131  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*23:01:01  Russian Federation Vologda Region 0.4202119
 132  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*02:01:01-DPB1*01:01:01  Russian Federation Vologda Region 0.4202119
 133  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*01:01  Russian Federation Vologda Region 0.4202119
 134  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*02:01:02  Russian Federation Vologda Region 0.4202119
 135  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Chihuahua Chihuahua City 0.4202119
 136  A*01-B*08-DRB1*03:01-DQB1*02  Ecuador Coast Mixed Ancestry 0.4202238
 137  A*01:01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01:01-DQB1*02:01  Russia Bashkortostan, Bashkirs 0.4167120
 138  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.41153,456,066
 139  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Oaxaca Rural 0.4107485
 140  A*01:01-B*08:04-C*07:01-DRB1*03:01-DQA1*05:01-DQB1*02:01  Kosovo 0.4030124
 141  A*01:01-B*08:01-C*04:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Panama 0.3800462
 142  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.35055,849
 143  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQA1*05:01-DQB1*02:01  Brazil Puyanawa 0.3333150
 144  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Puebla, Puebla city 0.32571,994
 145  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.32274,204
 146  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Caucasian 0.3125405
 147  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 148  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Veracruz, Veracruz city 0.2907171
 149  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*02:01  Russia Karelia 0.28861,075
 150  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP Filipino 0.260750,614
 151  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:02  USA San Diego 0.2600496
 152  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP Japanese 0.245224,582
 153  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Tlaxcala Rural 0.2410830
 154  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.238711,446
 155  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Nuevo Leon Rural 0.2273439
 156  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*16:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 157  A*01:01-B*08:01-C*01:02-DRB1*03:01-DQB1*02:01-DPB1*01:01  Panama 0.1900462
 158  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Indian 0.1845271
 159  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.17801,772
 160  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.15262,492
 161  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*09:01  Germany DKMS - German donors 0.14093,456,066
 162  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 163  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.13752,403
 164  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.13604,856
 165  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*03:01  Russia Karelia 0.13151,075
 166  A*01:01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.09941,510
 167  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.08901,772
 168  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:02  Russia Karelia 0.08141,075
 169  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.07821,510
 170  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP Korean 0.069477,584
 171  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 172  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*20:01  Russia Karelia 0.05651,075
 173  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*09:01  Russia Karelia 0.05651,075
 174  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:85-DPB1*01:01  Russia Karelia 0.05631,075
 175  A*01:01-B*08:01-C*05:01-DRB1*03:01-DQB1*02:01-DPB1*01:01  Russia Karelia 0.05621,075
 176  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP Vietnamese 0.049343,540
 177  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*16:01  Germany DKMS - German donors 0.04693,456,066
 178  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*05:01  Germany DKMS - German donors 0.04463,456,066
 179  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*10:01  Germany DKMS - German donors 0.04023,456,066
 180  A*01:01-B*08:01-C*06:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.034911,446
 181  A*01:01-B*08:01-C*15:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.030611,446
 182  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.02881,734
 183  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*20:01  Germany DKMS - German donors 0.02693,456,066
 184  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*13:01  Germany DKMS - German donors 0.02603,456,066
 185  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*06:01  Germany DKMS - German donors 0.02343,456,066
 186  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*17:01  Germany DKMS - German donors 0.02163,456,066
 187  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*14:01  Germany DKMS - German donors 0.02023,456,066
 188  A*01:01-B*08:01-C*06:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.02012,492
 189  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.02012,492
 190  A*01:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:07  India Tamil Nadu 0.02012,492
 191  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*19:01  Germany DKMS - German donors 0.01903,456,066
 192  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  India North UCBB 0.01715,849
 193  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*15:01  Germany DKMS - German donors 0.01713,456,066
 194  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP Chinese 0.015499,672
 195  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*11:01  Germany DKMS - German donors 0.01373,456,066
 196  A*01:01-B*08:01-C*02:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01214,204
 197  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*23:01  Germany DKMS - German donors 0.01073,456,066
 198  A*01:01-B*08:01-C*05:01-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 199  A*01:01-B*08:01-C*02:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.00885,849
 200  A*01:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  India West UCBB 0.00865,829

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 212) records   Pages: 1 2 3 of 3  


   

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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