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 : 
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Displaying 101 to 200 (from 265) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Hispanic 0.3327115,374
 102  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Japanese 0.035924,582
 103  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Middle Eastern or North Coast of Africa 0.544670,890
 104  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP North American Amerindian 0.820635,791
 105  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Filipino 0.055650,614
 106  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Korean 0.050477,584
 107  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP African American pop 2 0.2441416,581
 108  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Mexican or Chicano 0.4183261,235
 109  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Southeast Asian 0.293627,978
 110  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP European Caucasian 1.12121,242,890
 111  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP African 0.107028,557
 112  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP South Asian Indian 0.3817185,391
 113  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Hispanic South or Central American 0.5057146,714
 114  A*03:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Chinese 0.044299,672
 115  A*11:01:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.67021,510
 116  A*11:01:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.7812192
 117  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQA1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*03:01  Russian Federation Vologda Region 0.4202119
 118  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQA1*01:01:01-DQB1*05:01-DPA1*01:03:01-DPB1*04:02  Russia Belgorod region 1.3072153
 119  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQA1*01:01:01-DQB1*05:01-DPA1*01:03:01-DPB1*09:01  Russia Belgorod region 0.3268153
 120  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 1.1790356
 121  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.486023,595
 122  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Spain, Canary Islands, Gran canaria island 0.4700215
 123  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.5837521
 124  A*11:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQA1*01:01:01-DQB1*05:01-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 125  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01  Mexico Tixcacaltuyub Maya 0.746367
 126  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  South Africa Worcester 0.6000159
 127  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  USA San Diego 0.2600496
 128  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:02  Nicaragua Managua 0.2165339
 129  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*17:01  Sri Lanka Colombo 0.0700714
 130  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.20511,463
 131  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.44501,159
 132  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.40404,856
 133  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.07872,492
 134  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India Central UCBB 0.30494,204
 135  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India Northeast UCBB 1.0135296
 136  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India East UCBB 0.48292,403
 137  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.200011,446
 138  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.34645,829
 139  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India North UCBB 0.39425,849
 140  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Italy pop 5 0.2900975
 141  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Malaysia Peninsular Indian 0.3690271
 142  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Mexico Mexico City Mestizo population 0.3497143
 143  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.51304,335
 144  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA NMDP Alaska Native or Aleut 0.23911,376
 145  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA NMDP Black South or Central American 0.21644,889
 146  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA NMDP American Indian South or Central America 0.41665,926
 147  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA NMDP Caribean Indian 0.224214,339
 148  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.18401,999
 149  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.22201,772
 150  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA African American pop 4 0.04402,411
 151  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*01:01  Germany DKMS - German donors 0.01163,456,066
 152  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.08113,456,066
 153  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*03:01  Germany DKMS - German donors 0.03133,456,066
 154  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*03:01  Russia Karelia 0.05701,075
 155  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.17513,456,066
 156  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.39421,075
 157  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:02  Germany DKMS - German donors 0.20753,456,066
 158  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:02  Russia Karelia 0.32101,075
 159  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*09:01  Germany DKMS - German donors 0.02013,456,066
 160  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*10:01  Germany DKMS - German donors 0.02353,456,066
 161  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*19:01  Russia Karelia 0.05611,075
 162  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP African 0.047128,557
 163  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Chinese 0.024599,672
 164  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Hispanic South or Central American 0.3500146,714
 165  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP South Asian Indian 0.3421185,391
 166  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Vietnamese 0.027043,540
 167  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Mexican or Chicano 0.3081261,235
 168  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP European Caucasian 0.56671,242,890
 169  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Southeast Asian 0.208827,978
 170  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP African American pop 2 0.1054416,581
 171  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Korean 0.014377,584
 172  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Filipino 0.058850,614
 173  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP North American Amerindian 0.434135,791
 174  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Middle Eastern or North Coast of Africa 0.364370,890
 175  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Black 0.083933,328
 176  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Japanese 0.024324,582
 177  A*11:01-B*35:01-C*04:01-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Hispanic 0.3627115,374
 178  A*11:01-B*35:01-C*04:01-E*01:01:01-F*01:01:02-G*01:04-DRB1*01:01-DQA1*01:01-DQB1*05:01  Portugal Azores Terceira Island 0.4386130
 179  A*23:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 180  A*24:02:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.05931,510
 181  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.046323,595
 182  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 183  A*24:02-B*35:01-C*04:01-DRB1*01:01:01-DQB1*05:01:01  England North West 0.2000298
 184  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03271,463
 185  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.02904,856
 186  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.02232,492
 187  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.054111,446
 188  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India North UCBB 0.06375,849
 189  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India Central UCBB 0.01324,204
 190  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.13845,829
 191  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 192  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.14301,999
 193  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.01143,456,066
 194  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.02683,456,066
 195  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.09281,075
 196  A*24:02-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:02  Germany DKMS - German donors 0.03173,456,066
 197  A*24:07-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.00435,829
 198  A*24:07-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  India North UCBB 0.01965,849
 199  A*25:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQA1*01:01:01-DQB1*05:01-DPA1*02:01:04-DPB1*13:01  Russia Belgorod region 0.3268153
 200  A*25:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.054923,595

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 265) 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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