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 1,501 to 1,600 (from 15,562) records   Pages: 11 12 13 14 15 16 17 18 19 20 of 156  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1,501  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 1,502  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.006023,595
 1,503  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.017723,595
 1,504  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.008223,595
 1,505  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00945,266
 1,506  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DPB1*09:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00955,266
 1,507  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.049223,595
 1,508  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 1,509  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01-DQB1*06:03  Costa Rica Central Valley Mestizo (G) 0.2262221
 1,510  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.013923,595
 1,511  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:02:01-DQB1*06:09:01  Poland BMR 0.004423,595
 1,512  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:03:01-DQB1*02:02:01  Poland BMR 0.000876023,595
 1,513  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.058523,595
 1,514  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:03:01-DQB1*03:04:01  Poland BMR 0.002123,595
 1,515  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:03:01-DQB1*04:02:01  Poland BMR 0.002123,595
 1,516  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:03:02-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 1,517  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:05:01-DQB1*02:01:01  Poland BMR 0.002123,595
 1,518  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:05:01-DQB1*03:01:01  Poland BMR 0.020223,595
 1,519  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*14:01:01-DQB1*05:03:01  Poland BMR 0.022423,595
 1,520  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*14:04:01-DQB1*05:03:01  Poland BMR 0.002123,595
 1,521  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*14:07:01-DQB1*05:03:01  Poland BMR 0.004223,595
 1,522  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.004423,595
 1,523  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*15:01:01-DPB1*135:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00905,266
 1,524  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*15:01:01-DQB1*06:01:01  India Kerala Malayalam speaking 0.1400356
 1,525  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.059323,595
 1,526  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*15:01:01-DQB1*06:03:01  Poland BMR 0.003523,595
 1,527  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*15:02:02-DQB1*06:01:01  India Karnataka Kannada Speaking 0.2870174
 1,528  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*16:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 1,529  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.013123,595
 1,530  A*01:01:01-B*57:01:01-C*06:02-DRB1*07:01  South Africa Caucasians 2.2200102
 1,531  A*01:01:01-B*57:01:01-C*06:07-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 1,532  A*01:01:01-B*57:01:01-C*06:18-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.006423,595
 1,533  A*01:01:01-B*57:01:01-C*07:01:01-DRB1*03:01:01-DQA1*02:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 1,534  A*01:01:01-B*57:01:01-C*07:01:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.006223,595
 1,535  A*01:01:01-B*57:01:01-C*07:01:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 1,536  A*01:01:01-B*57:01:01-C*07:01:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 1,537  A*01:01:01-B*57:01:01-C*07:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 0.1400356
 1,538  A*01:01:01-B*57:01:01-C*07:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 1,539  A*01:01:01-B*57:01:01-C*08:02:01-DRB1*07:01:01:01-DQB1*03:03:02:01  Russia Bashkortostan, Tatars 0.2604192
 1,540  A*01:01:01-B*57:01:01-C*12:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,541  A*01:01:01-B*57:01:01-C*12:03:01-DRB1*13:03:01-DQB1*03:04:01  Poland BMR 0.002123,595
 1,542  A*01:01:01-B*57:01:01-C*16:02:01-DRB1*13:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 1,543  A*01:01:01-B*57:01-C*06:02-DRB1*04:02-DQA1*03:01-DQB1*03:02  Morocco Atlantic Coast Chaouya 2.100098
 1,544  A*01:01:01-B*57:03:01-C*16:01:01-DRB1*01:02:01  Costa Rica Guanacaste Mestizo (G) 0.4545110
 1,545  A*01:01:01-B*57:40-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 1,546  A*01:01:01-B*58:01:01-C*03:02:01-DRB1*07:01:01-DQB1*02:01:02  India Karnataka Kannada Speaking 0.2870174
 1,547  A*01:01:01-B*58:01:01-C*03:02:01-DRB1*15:06:01-DQB1*05:02:01  India Karnataka Kannada Speaking 0.2870174
 1,548  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 0.3143186
 1,549  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.01345,266
 1,550  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02881,734
 1,551  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Poland BMR 0.010723,595
 1,552  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Vietnam Kinh 0.4950101
 1,553  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*15:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 1,554  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*15:02:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,555  A*01:01:01-B*58:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01-DPB1*105:01:01  South African Black 0.3520142
 1,556  A*01:01:01-B*58:01:01-C*07:18  England Blood Donors of Mixed Ethnicity 0.0963519
 1,557  A*01:01:01-B*58:01:01-C*07:18:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 1,558  A*01:01:01-B*58:01:01-C*07:18:01-DRB1*13:03:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*104:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 1,559  A*01:01:01-B*58:01:01-C*07:18:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 1,560  A*01:01:01-B*58:01:01-C*15:02:01-DRB1*07:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,561  A*01:01:01-B*58:01-DRB1*07:01:01  Portugal Center 1.000050
 1,562  A*01:01:01-B*58:01-DRB1*13:04  Guinea Bissau 1.500065
 1,563  A*01:01:01-B*58:02:01-C*06:02:01-DRB1*14:54:01-DQB1*03:19:01-DPB1*01:01:01  South African Black 0.3520142
 1,564  A*01:01:01-B*58:02:01-C*14:02:01-DRB1*12:02:02-DQB1*06:02:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 1,565  A*01:01:01-B*81:01:01-C*18:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 1,566  A*01:01:01-B*81:01-C*18:01-DRB1*11:01:02-DQB1*03:19:01-DPB1*105:01:01  South African Black 0.7040142
 1,567  A*01:01:01-C*06:02:01  China Jingpo Minority 0.9710105
 1,568  A*01:01:01-C*06:02:01-DRB1*10:01:01  China Jingpo Minority 1.0310105
 1,569  A*01:01:01-C*07:02:01-DRB1*04:05:01  China Jingpo Minority 0.5150105
 1,570  A*01:01:01-C*12:03:01  China Jingpo Minority 0.4850105
 1,571  A*01:01:03-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 1,572  A*01:01:33-B*08:01:01-C*07:01:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 1,573  A*01:01-B*07:02  China Hubei Han 0.00060003,732
 1,574  A*01:01-B*07:02  Ireland Northern 1.50001,000
 1,575  A*01:01-B*07:02  Mexico Mestizo 2.400041
 1,576  A*01:01-B*07:02  USA Caucasian pop 2 1.3000265
 1,577  A*01:01-B*07:02  USA Hispanic pop 2 0.28101,999
 1,578  A*01:01-B*07:02  USA African American pop 4 0.33402,411
 1,579  A*01:01-B*07:02  USA Asian pop 2 0.20701,772
 1,580  A*01:01-B*07:02-C*01:02-DRB1*15:01  Germany DKMS - United Kingdom minority 0.04801,043
 1,581  A*01:01-B*07:02-C*02:02-DRB1*04:07  Germany DKMS - Netherlands minority 0.03601,374
 1,582  A*01:01-B*07:02-C*02:02-DRB1*07:01  Germany DKMS - Croatia minority 0.02402,057
 1,583  A*01:01-B*07:02-C*03:04-DRB1*08:04  Poland DKMS 0.002020,653
 1,584  A*01:01-B*07:02-C*03:04-DRB1*11:01  Poland DKMS 0.002420,653
 1,585  A*01:01-B*07:02-C*03:04-DRB1*15:01-DQB1*06:02  India North UCBB 0.00855,849
 1,586  A*01:01-B*07:02-C*04:01-DRB1*13:01-DQB1*06:03  India Northeast UCBB 0.1689296
 1,587  A*01:01-B*07:02-C*04:01-DRB1*13:14-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 1,588  A*01:01-B*07:02-C*04:01-DRB1*14:54-DQB1*05:03  India East UCBB 0.02082,403
 1,589  A*01:01-B*07:02-C*04:01-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:01  Nicaragua Managua 0.2165339
 1,590  A*01:01-B*07:02-C*04:01-DRB1*15:01-DQB1*06:02  India South UCBB 0.009311,446
 1,591  A*01:01-B*07:02-C*04:01-DRB1*15:02-DQB1*06:02  India South UCBB 0.003811,446
 1,592  A*01:01-B*07:02-C*04:01-DRB1*15:03-DQB1*06:02-DPB1*01:01  Panama 0.1900462
 1,593  A*01:01-B*07:02-C*04:03-DRB1*16:02-DQB1*05:02  India Northeast UCBB 0.1689296
 1,594  A*01:01-B*07:02-C*05:01-DRB1*11:04  Italy pop 5 0.1000975
 1,595  A*01:01-B*07:02-C*05:01-DRB1*13:02-DQB1*06:41  India South UCBB 0.004411,446
 1,596  A*01:01-B*07:02-C*05:01-DRB1*14:54-DQB1*05:03  India West UCBB 0.00865,829
 1,597  A*01:01-B*07:02-C*06:02-DRB1*07:01  Germany DKMS - Netherlands minority 0.03601,374
 1,598  A*01:01-B*07:02-C*07:01-DRB1*04:01  Germany DKMS - Spain minority 0.05301,107
 1,599  A*01:01-B*07:02-C*07:01-DRB1*04:04  Poland DKMS 0.002420,653
 1,600  A*01:01-B*07:02-C*07:01-DRB1*13:01  Poland DKMS 0.007220,653

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 1,501 to 1,600 (from 15,562) records   Pages: 11 12 13 14 15 16 17 18 19 20 of 156  


   

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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