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 1,189) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 12  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DPA1*02:01:01-DPB1*14:01  Ecuador Cayapa 42.2000183
 2  DPA1*02:01:01-DPB1*01:01:01  Ecuador African 33.600058
 3  DPA1*02:01:01-DPB1*17:01  Gambia 25.7000146
 4  DPA1*02:01:01-DPB1*01:01:01  Gambia 17.1000146
 5  DPA1*02:01:01-DPB1*09:01  Japan Fukuoka 11.000086
 6  DPA1*02:01:01-DPB1*01:01:01  Uganda Baganda 10.600047
 7  DPA1*02:01:01-DPB1*13:01  Gambia 9.9000146
 8  DPA1*02:01:01-DPB1*01:01:01  Cameroon Saa 7.6000172
 9  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPA1*02:01-DPB1*09:01  Japan pop 17 7.32003,078
 10  DPA1*02:01-DPB1*11:01  Spain Navarre Basques 6.8000116
 11  DRB1*07:01-DQA1*02:01-DPA1*02:01-DPB1*11:01  Spain Gipuzkoa Basque 6.7000100
 12  DPA1*02:01:01-DPB1*14:01  Ecuador African 6.000058
 13  DPA1*02:01:01-DPB1*13:01  Ecuador Cayapa 5.4000183
 14  DPA1*02:01:01-DPB1*17:01  Uganda Baganda 5.300047
 15  DPA1*02:01:01-DPB1*05:01  Japan Fukuoka 5.200086
 16  DPA1*02:01:01-DPB1*09:01  Russia Tuva pop 2 5.0000169
 17  DPA1*02:01:01-DPB1*13:01  Cameroon Saa 4.4000172
 18  DPA1*02:01:01-DPB1*09:01  India Bombay 4.200059
 19  DPA1*02:01:01-DPB1*13:01  India Bombay 4.200059
 20  DPA1*02:01:01-DPB1*26:01  India Bombay 4.200059
 21  DRB1*07:01-DQA1*02:01-DPA1*02:01-DPB1*11:01  Spain Catalonia Girona 4.200088
 22  DPA1*02:01:01-DPB1*01:01:02  Cameroon Saa 3.8000172
 23  DPA1*02:01:01-DPB1*17:01  Cameroon Saa 3.5000172
 24  DPA1*02:01:01-DPB1*17:01  India Bombay 3.400059
 25  DPA1*02:01:01-DPB1*19:01  Uganda Baganda 3.200047
 26  DPA1*02:01:02-DPB1*01:01:01  France Ceph 3.2000124
 27  DPA1*02:01:01-DPB1*17:01  Russia Tuva pop 2 2.7000169
 28  DPA1*02:01:01-DPB1*11:01:01  France Ceph 2.4000124
 29  DPA1*02:01:01-DPB1*17:01  France Ceph 2.4000124
 30  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*01:01:01  Brazil Barra Mansa Rio State Black 2.381073
 31  A*02:01:01-B*44:03:01-C*15:05:02-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*13:01:01  Brazil Barra Mansa Rio State Black 2.381073
 32  A*02:01:01-B*49:01:01-C*07:01:01-DRB1*13:02:01-DQB1*06:04:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Black 2.381073
 33  A*02:01:01-B*53:01:01-C*04:01:01-DRB1*01:02:01-DQB1*05:01:01-DPA1*02:01:08-DPB1*105:01:01  Brazil Barra Mansa Rio State Black 2.381073
 34  A*02:01:01-B*56:01:01-C*01:02:01-DRB1*11:03:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*10:01:01  Brazil Barra Mansa Rio State Black 2.381073
 35  A*02:05:01-B*44:03:01-C*04:01:01-DRB1*13:02:01-DQB1*03:02:01-DPA1*02:01:07-DPB1*04:01:01  Brazil Barra Mansa Rio State Black 2.381073
 36  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01-DPA1*02:01:01-DPB1*10:01:01  Brazil Barra Mansa Rio State Black 2.381073
 37  A*03:01:01-B*07:06:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*11:01:01  Brazil Barra Mansa Rio State Black 2.381073
 38  A*03:01:01-B*08:01:01-C*07:06:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*02:01:08-DPB1*01:01:01  Brazil Barra Mansa Rio State Black 2.381073
 39  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*13:02:01-DQB1*03:02:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Black 2.381073
 40  A*11:01:01-B*55:01:01-C*03:03:01-DRB1*04:03:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*10:01:01  Brazil Barra Mansa Rio State Black 2.381073
 41  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*04:05:01-DQB1*06:04:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Black 2.381073
 42  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*07:01:01-DQB1*02:01:01-DPA1*02:01:02-DPB1*17:01:01  Brazil Barra Mansa Rio State Black 2.381073
 43  A*24:02:01-B*51:01:01-C*07:02:01-DRB1*11:01:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*04:02:01  Brazil Barra Mansa Rio State Black 2.381073
 44  A*29:02:01-B*14:02:01-C*08:02:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*02:01:01-DPB1*13:01:01  Brazil Barra Mansa Rio State Black 2.381073
 45  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPA1*02:01-DPB1*17:01  China Zhejiang Han pop 2 2.3340833
 46  DPA1*02:01:01-DPB1*13:01  Uganda Baganda 2.100047
 47  DPA1*02:01-DPB1*76:01  Spain Navarre Basques 2.1000116
 48  DPA1*02:01:01-DPB1*01:01:01  India Bombay 1.700059
 49  DPA1*02:01:01-DPB1*01:01:02  Gambia 1.7000146
 50  DPA1*02:01:01-DPB1*14:01  India Bombay 1.700059
 51  DPA1*02:01:01-DPB1*17:01  Ecuador African 1.700058
 52  DPA1*02:01:01-DPB1*14:01  France Ceph 1.6000124
 53  DPA1*02:01-DPB1*70:01  Spain Navarre Basques 1.6000116
 54  DPA1*02:01:01-DPB1*14:01  Russia Tuva pop 2 1.5000169
 55  A*03:01:01-B*15:10:01-C*17:03:01-DRB1*13:03:01-DQB1*03:19:01-DPA1*02:01:01-DPB1*10:01:01  Brazil Rio de Janeiro Black 1.470668
 56  A*03:01:01-B*53:01:01-C*04:01:01-DRB1*11:03:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 57  A*11:01:01-B*07:02:01-C*04:01:01-DRB1*01:03:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*13:01:01  Brazil Rio de Janeiro Black 1.470668
 58  A*23:01:01-B*44:03:01-C*07:01:01-DRB1*07:01:01-DQB1*02:01:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Rio de Janeiro Black 1.470668
 59  A*23:17:01-B*15:03:01-C*07:01:01-DRB1*11:01:02-DQB1*03:19:01-DPA1*02:01:02-DPB1*01:01:01  Brazil Rio de Janeiro Black 1.470668
 60  A*24:02:01-B*14:02:01-C*08:02:01-DRB1*01:02:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Rio de Janeiro Black 1.470668
 61  A*30:02:01-B*14:02:01-C*08:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 62  A*30:02:01-B*37:01:01-C*07:01:01-DRB1*10:01:01-DQB1*06:04:01-DPA1*02:01:08-DPB1*01:01:01  Brazil Rio de Janeiro Black 1.470668
 63  A*30:02:01-B*41:02:01-C*03:04:02-DRB1*08:04:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*01:01:02  Brazil Rio de Janeiro Black 1.470668
 64  A*30:02:01-B*57:03:01-C*07:02:01-DRB1*08:02:01-DQB1*04:02:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 65  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*30:01:01  Brazil Rio de Janeiro Black 1.470668
 66  A*68:01:02-B*44:02:01-C*07:04:01-DRB1*04:02:01-DQB1*03:02:01-DPA1*02:01:01-DPB1*11:01:01  Brazil Rio de Janeiro Black 1.470668
 67  DQA1*02:01-DQB1*02:02-DPA1*02:01-DPB1*17:01  Hong Kong Chinese HKBMDR. DQ and DP 1.31121,064
 68  DQA1*01:01-DQB1*05:01-DPA1*02:01-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 1.30691,064
 69  DPA1*02:01:01-DPB1*01:01:01  Papua New Guinea Highland pop2 1.300028
 70  DPA1*02:01:01-DPB1*09:01  France Ceph 1.2000124
 71  DPA1*02:01:01-DPB1*13:01  Russia Tuva pop 2 1.2000169
 72  DPA1*02:01:01-DPB1*13:01  Japan Fukuoka 1.200086
 73  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*13:01:01  Brazil Rio de Janeiro Parda 1.1765170
 74  DPA1*02:01:01-DPB1*49:01  Uganda Baganda 1.100047
 75  DPA1*02:01-DPB1*01:01  Spain Navarre Basques 1.1000116
 76  DPA1*02:01-DPB1*05:01  Spain Navarre Basques 1.1000116
 77  DPA1*02:01-DPB1*10:01  Spain Navarre Basques 1.1000116
 78  DPA1*02:01-DPB1*14:01  Spain Navarre Basques 1.1000116
 79  DPA1*02:01-DPB1*17:01  Spain Navarre Basques 1.1000116
 80  DPA1*02:01:01-DPB1*10:01  Tokelau 1.000050
 81  DPA1*02:01:01-DPB1*14:01  Samoa pop2 1.000050
 82  DPA1*02:01:02-DPB1*01:01:01  Gambia 1.0000146
 83  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*02:01:02-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.9375405
 84  A*33:01:01-B*14:02:01-C*08:02:01-DRB1*01:02:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.9375405
 85  DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:01-DPB1*05:01  China Zhejiang Han pop 2 0.8436833
 86  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*02:01:02-DPB1*01:01  Russian Federation Vologda Region 0.8403119
 87  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*11:01:01  Brazil Rio de Janeiro Caucasian 0.7782521
 88  DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:01-DPB1*14:01  China Zhejiang Han pop 2 0.7353833
 89  A*11:01-B*40:06-C*15:02-DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*02:01-DPB1*14:01  United Arab Emirates Pop 1 0.6954570
 90  A*26:01:01-B*38:01:01-C*12:03:01-DRB1*13:01:01-DQA1*01:03:01-DQB1*06:03-DPA1*02:01:01-DPB1*02:01  Russia Belgorod region 0.6536153
 91  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*07:01:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 92  A*24:02:01-B*35:08:01-C*04:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*02:01:01-DPB1*10:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 93  DQA1*03:02-DQB1*03:03-DPA1*02:01-DPB1*14:01  Hong Kong Chinese HKBMDR. DQ and DP 0.62081,064
 94  DQA1*01:02-DQB1*06:09-DPA1*02:01-DPB1*09:01  Hong Kong Chinese HKBMDR. DQ and DP 0.59001,064
 95  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
 96  A*02:01:01-B*15:05:01-C*01:02:30-DRB1*16:02:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*04:02:01  Brazil Rio de Janeiro Parda 0.5882170
 97  A*02:01:01-B*35:02:01-C*04:01:01-DRB1*11:04:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*126:01:01  Brazil Rio de Janeiro Parda 0.5882170
 98  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*04:01:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 99  A*02:01:01-B*51:01:01-C*04:01:01-DRB1*01:02:01-DQB1*02:01:01-DPA1*02:01:02-DPB1*17:01:01  Brazil Rio de Janeiro Parda 0.5882170
 100  A*02:02:01-B*51:01:01-C*04:01:01-DRB1*07:01:01-DQB1*03:02:01-DPA1*02:01:01-DPB1*11:01:01  Brazil Rio de Janeiro Parda 0.5882170

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 1,189) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 12  


   

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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