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 to 100 (from 6,909) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 70  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*58:02-C*06:02  Kenya Luo 11.7000265
 2  A*30-B*13-C*06:02  Pakistan Karachi Parsi 11.000091
 3  B*58:02-C*06:02  Uganda Kampala pop 2 10.3000175
 4  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Tunisia 9.0000100
 5  B*58:02-C*06:02  Kenya Nandi 8.5000240
 6  B*13-C*06:02  Pakistan Kalash 7.200069
 7  A*30-B*13-C*06:02  Pakistan Kalash 6.500069
 8  B*45:01-C*06:02  Uganda Kampala pop 2 6.0000175
 9  A*02-B*37-C*06:02  Pakistan Kalash 5.700069
 10  A*66:01-B*58:02-C*06:02  Kenya Luo 5.1000265
 11  B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Ireland South 5.0000250
 12  A*31:08-B*13:02-C*06:02  India West Coast Parsi 4.700050
 13  A*02-B*51-C*06-DRB1*13-DQB1*06  Sudan Khartoum 4.590098
 14  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - China minority 4.51801,282
 15  B*13-C*06:02  Pakistan Mixed Pathan 4.4000100
 16  B*58:02-C*06:02  Uganda Kampala 4.4000161
 17  A*24-B*38-C*06-DRB1*11-DQB1*03  Spain Majorcans Jews 4.3000103
 18  A*01:01:01-B*37:01:01-C*06:02:01  South African Indian population 4.000050
 19  B*40:06-C*06:02  India Mumbai Maratha 4.000091
 20  B*57:01-C*06:02  USA Caucasian pop 2 4.0000265
 21  B*58:02-C*06:02  USA African American pop 4 3.96402,411
 22  A*01-B*57-C*06-DRB1*07  Myanmar Mon 3.906064
 23  A*30:01-B*13:02-C*06:02-DRB1*07:01  Taiwan pop 2 3.9000364
 24  A*30-B*13-C*06:02  Pakistan Mixed Pathan 3.9000100
 25  B*53:01-C*06:02  Mali Bandiagara 3.9000138
 26  B*45:01-C*06:02  Kenya Nandi 3.8000240
 27  B*44:07-C*06:02  India Mumbai Maratha 3.700091
 28  B*57:01-C*06:02  Ireland Northern 3.70001,000
 29  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  India Tamil Nadu 3.63482,492
 30  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 3.6238192
 31  A*02:01:01-B*50:01-C*06:02  Morocco Settat Chaouya 3.600098
 32  A*01:01-B*57:01-C*06:02  Ireland South 3.5000250
 33  B*58:02-C*06:02  USA African American 3.4000252
 34  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*03:03  Brazil Puyanawa 3.3333150
 35  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 3.3333120
 36  A*02:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 3.3333120
 37  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Malaysia Peninsular Indian 3.3210271
 38  A*29:02-B*45:01-C*06:02-DRB1*15:01-DQB1*06:02  Colombia North Chimila Amerindians 3.191547
 39  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  China Zhejiang Han 3.11091,734
 40  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 3.1035186
 41  A*23:01-B*53:01-C*06:02  Mali Bandiagara 3.1000138
 42  A*30:01-B*13:01-C*06:03  India Khandesh Region Pawra 3.100050
 43  A*30:01-B*13:02-C*06:02  South Korea pop 3 3.1000485
 44  A*01:01:01-B*57:01:01-C*06:02:01  South African Indian population 3.000050
 45  A*01:01:01-B*57:01:01-C*06:02:01  South African Mixed ancestry 3.000050
 46  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 47  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Ireland South 3.0000250
 48  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 49  A*02-B*50-C*06:02  Pakistan Mixed Sindhi 3.0000101
 50  A*30-B*13-C*06:02-DRB1*07:01-DQB1*02  Russia Transbaikal Territory Buryats 3.0000150
 51  B*45:01-C*06:02  Tunisia 3.0000100
 52  B*45:01-C*06:02  Kenya Luo 3.0000265
 53  B*13-C*06  Macedonia 2.9720286
 54  A*01:01-B*50:01-C*06:02  Morocco Settat Chaouya 2.900098
 55  A*02:01:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Morocco Atlantic Coast Chaouya 2.900098
 56  A*66:01-B*58:02-C*06:02  Kenya Nandi 2.9000240
 57  B*13:02-C*06:02-DRB1*07:01  South Korea pop 3 2.9000485
 58  A*02:01-B*13:02-C*06:02-DRB1*07:01  Russia Bering Island Aleuts 2.8846104
 59  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 2.880052
 60  A*30-B*13-C*06:02  South Korea pop 1 2.8000324
 61  A*02:02-B*58:02-C*06:02  Kenya Nandi 2.7000240
 62  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01/02:02  South Korea pop 3 2.7000485
 63  A*02-B*49-C*06-DRB1*03-DQB1*02  Sudan Khartoum 2.560098
 64  B*57:01-C*06:02  Tunisia 2.5000100
 65  A*01-B*57-C*06:02  England London Ashkenazi Jews 2.4000500
 66  A*03:01:01-B*07:02:01-C*06:02:01-DRB1*13:02:01-DQB1*03:01:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Barra Mansa Rio State Black 2.381073
 67  A*11:01:01-B*13:02:01-C*06:02:01-DRB1*01:02:01-DQB1*05:01:01-DPA1*03:01:01-DPB1*105:01:01  Brazil Barra Mansa Rio State Black 2.381073
 68  A*11:01:01-B*50:01:01-C*06:02:01-DRB1*04:04:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*13:01:01  Brazil Barra Mansa Rio State Black 2.381073
 69  A*23:01:01-B*41:01:01-C*06:02:01-DRB1*12:01:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Black 2.381073
 70  A*24:02:01-B*35:02:01-C*06:02:01-DRB1*11:04:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*105:01:01  Brazil Barra Mansa Rio State Black 2.381073
 71  A*66:01:01-B*58:02:01-C*06:02:01-DRB1*08:07-DQB1*03:03:02-DPA1*01:03:01-DPB1*04:02:01  Brazil Barra Mansa Rio State Black 2.381073
 72  A*01-B*37-C*06:02-DRB1*10:01-DQB1*05  Russia Transbaikal Territory Buryats 2.3340150
 73  A*01-C*06  Venezuela Colonia Tovar 2.300086
 74  A*01:01:01-B*57:01:01-C*06:02:01  England Blood Donors of Mixed Ethnicity 2.2987519
 75  B*13:02-C*06:02  USA Asian pop 2 2.27401,772
 76  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Korean 2.258577,584
 77  A*02:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Bosnia and Herzegovina minority 2.24501,028
 78  A*01:01:01-B*57:01:01-C*06:02-DRB1*07:01  South Africa Caucasians 2.2200102
 79  A*02-B*13-C*06-DRB1*07  Russia Tatars 2.2100355
 80  A*01:01-B*57:01-C*06:02  USA Caucasian pop 2 2.2000265
 81  B*13:02-C*06:02  Uganda Kampala 2.2000161
 82  B*45:01-C*06:02  USA African American 2.2000252
 83  B*57:01-C*06:02  Uganda Kampala 2.2000161
 84  A*01:01-B*57:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*03:03  USA NMDP South Asian Indian 2.1760185,391
 85  A*01:01:01-B*50:01-C*06:02-DRB1*03:01-DQA1*05:01-DQB1*02:01  Morocco Atlantic Coast Chaouya 2.100098
 86  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
 87  A*01:01-B*57:01-C*06:02  Ireland Northern 2.10001,000
 88  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Vietnam Hanoi Kinh pop 2 2.1000170
 89  A*80:01-B*45:01-C*06:02  Morocco Settat Chaouya 2.100098
 90  A*80:01-B*45:01-C*06:02-DRB1*13:03:02-DQA1*05:05-DQB1*03:01  Morocco Atlantic Coast Chaouya 2.100098
 91  B*37:01-C*06:02  USA Caucasian pop 2 2.1000265
 92  B*50:01-C*06:02  USA Hispanic 2.1000234
 93  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 2.0680356
 94  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Chinese 2.025499,672
 95  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 2.0110174
 96  A*24-B*13-C*06  Italy East Sicily 2.000050
 97  B*13:02-C*06:02  Tunisia 2.0000100
 98  B*57:01-C*06:02  USA Asian pop 2 1.99001,772
 99  A*23-B*50-C*06:02-DRB1*03-DQB1*02  Russia North Ossetian 1.9700127
 100  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 1.95162,492

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 to 100 (from 6,909) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 70  


   

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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