Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 100 (from 669) records   Pages: 1 2 3 4 5 6 7 of 7  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DQA1*05:05-DQB1*03:01  Tunisia 24.7000100
 2  DRB1*11-DQA1*05:05-DQB1*03:01  Czech Republic pop 3 15.3000180
 3  DRB1*11-DQA1*05:05-DQB1*03:01  Iran 9.600058
 4  A*31:01-B*39:01-C*08:03-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 5.9180150
 5  DRB1*11:02-DQA1*05:05-DQB1*03:01  Congo Kinshasa Bantu 5.600090
 6  DRB1*13:03:02-DQA1*05:05-DQB1*03:01  Morocco Settat Chaouya 5.500098
 7  A*02:01-B*18:01-C*07:01-DRB1*11:04-DQA1*05:05-DQB1*03:01  Kosovo 5.2420124
 8  A*68:01-B*35:01-C*04:01-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 5.0000150
 9  DRB1*11:01-DQA1*05:05-DQB1*03:01  Tunisia 5.0000100
 10  A*68:03-B*35:01-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 4.1284218
 11  DQA1*05:05-DQB1*03:03  Tunisia 4.1000100
 12  DRB1*11:01-DQA1*05:05-DQB1*03:01  South Korea pop 5 4.0000467
 13  DRB1*11:01-DQA1*05:05-DQB1*03:01  South Korea pop 1 3.4000324
 14  DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  Hong Kong Chinese HKBMDR. DQ and DP 3.06091,064
 15  DRB1*11:04-DQA1*05:05-DQB1*03:01  Tunisia 3.0000100
 16  DRB1*11:01-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 2.9991833
 17  DRB1*12:01-DQA1*05:05-DQB1*03:01-DPB1*05:01  South Korea pop 2 2.7000207
 18  A*31:01-B*52:01-C*15:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 2.6667150
 19  DRB1*13:03-DQA1*05:05-DQB1*03:01:01  Iran 2.600058
 20  DRB1*12:01-DQA1*05:05-DQB1*03:01  Tunisia 2.5000100
 21  DRB1*12-DQA1*05:05-DQB1*03:01  Czech Republic pop 3 2.5000180
 22  DRB1*13-DQA1*05:05-DQB1*03:01  Czech Republic pop 3 2.5000180
 23  A*24:02-B*39:02-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Chichen Itza Maya (prehispanic) 2.127747
 24  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
 25  DRB1*11:01-DQA1*05:05-DQB1*03:01-DPB1*05:01  South Korea pop 11 2.1000149
 26  DRB1*11:01-DQA1*05:05-DQB1*03:01-DPB1*05:01  South Korea pop 2 2.0000207
 27  DRB1*12:01-DQA1*05:05-DQB1*03:01  South Korea pop 1 1.9000324
 28  A*31:01-B*39:01-C*08:01-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 1.7486150
 29  A*31:01-B*39:05-C*08:03-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 1.7486150
 30  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 1.6130124
 31  A*68:01-B*18:01-C*02:02-DRB1*11:04-DQA1*05:05-DQB1*03:01  Kosovo 1.6130124
 32  A*02:01-B*18:01-C*07:01-DRB1*11:04-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 1.6055218
 33  DRB1*11:01-DQA1*05:05-DQB1*03:01-DPB1*05:01  South Korea pop 1 1.6000324
 34  DRB1*12:01-DQA1*05:05-DQB1*03:01  South Korea pop 5 1.6000467
 35  A*31:01-B*39:05-C*08:01-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 1.5847150
 36  DRB1*12:01-DQA1*05:05-DQB1*03:01-DPB1*02:01  South Korea pop 1 1.4000324
 37  A*02:01-B*15:04-C*03:03-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 1.3333150
 38  DRB1*11:01-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 1.3275833
 39  DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 1.28341,064
 40  A*03:01-B*35:01-C*04:01-DRB1*11:04-DQA1*05:05-DQB1*03:01  Kosovo 1.2100124
 41  DRB1*11:01-DQA1*05:05-DQB1*03:01-DPB1*02:01  South Korea pop 11 1.2000149
 42  A*24:02-B*15:01-C*01:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Chichen Itza Maya (prehispanic) 1.063847
 43  A*24:02-B*40:02-C*03:04-DRB1*16:02-DQA1*05:05-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 44  A*31:01-B*35:20-C*15:09-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Chichen Itza Maya (prehispanic) 1.063847
 45  A*31:01-B*48:01-C*08:03-DRB1*16:02-DQA1*05:05-DQB1*03:03  Mexico Chichen Itza Maya (prehispanic) 1.063847
 46  A*68:01-B*40:08-C*03:04-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Chichen Itza Maya (prehispanic) 1.063847
 47  A*68:05-B*35:23-C*04:01-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Chichen Itza Maya (prehispanic) 1.063847
 48  A*02:01-B*07:02-C*07:02-DRB1*11:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 1.0000150
 49  A*02:01-B*51:01-C*15:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 1.0000150
 50  DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*02:02  Hong Kong Chinese HKBMDR. DQ and DP 0.98881,064
 51  A*02:01:01-B*18:01:01-C*07:01:01-DRB1*11:04:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.9804153
 52  A*68:01:02-B*44:02:01-C*07:04:01-DRB1*11:01:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*02:01:02  Russia Belgorod region 0.9804153
 53  A*01:01-B*81:01-C*18:01-DRB1*11:01-DQA1*05:05-DQB1*03:19  United Arab Emirates Abu Dhabi 0.960052
 54  A*02:01-B*50:01-C*07:01-DRB1*11:01-DQA1*05:05-DQB1*03:19  United Arab Emirates Abu Dhabi 0.960052
 55  A*03:02-B*08:01-C*07:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 56  A*23:01-B*50:01-C*07:01-DRB1*04:02-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 57  A*24:02-B*35:02-C*12:03-DRB1*11:04-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 58  A*24:02-B*50:01-C*06:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 59  A*24:03-B*58:02-C*12:03-DRB1*11:02-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 60  A*29:02-B*15:03-C*04:01-DRB1*11:01-DQA1*05:05-DQB1*05:01  United Arab Emirates Abu Dhabi 0.960052
 61  A*31:01-B*15:17-C*17:03-DRB1*03:01-DQA1*05:05-DQB1*02:01  United Arab Emirates Abu Dhabi 0.960052
 62  A*32:01-B*15:220-C*12:03-DRB1*11:01-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 63  A*32:01-B*39:10-C*04:01-DRB1*08:04-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 64  A*32:01-B*44:02-C*08:01-DRB1*12:02-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 65  A*32:01-B*51:01-C*07:02-DRB1*15:01-DQA1*05:05-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 66  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:05-DQB1*02:01  United Arab Emirates Abu Dhabi 0.960052
 67  A*33:03-B*58:01-C*03:02-DRB1*15:01-DQA1*05:05-DQB1*06:02  United Arab Emirates Abu Dhabi 0.960052
 68  A*68:01-B*51:01-C*16:01-DRB1*11:01-DQA1*05:05-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 69  A*74:01-B*38:01-C*06:02-DRB1*08:04-DQA1*05:05-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 70  A*02-B*51-DRB1*11:01-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.9446641
 71  A*24:02-B*35:03-C*12:03-E*01:03:02-F*01:01:02-G*01:01-DRB1*11:01-DQA1*05:05-DQB1*03:01  Portugal Azores Terceira Island 0.8772130
 72  DRB1*12:01-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*02:02  China Zhejiang Han pop 2 0.8724833
 73  A*02:01:01-B*18:01:01-C*07:01:01-DRB1*11:04:01-DQA1*05:05:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.8403119
 74  A*02:01-B*18:01-C*07:01-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 0.8060124
 75  A*02:01-B*35:03-C*04:01-DRB1*11:04-DQA1*05:05-DQB1*03:01  Kosovo 0.8060124
 76  A*02:01-B*35:03-C*04:01-DRB1*12:01-DQA1*05:05-DQB1*03:01  Kosovo 0.8060124
 77  A*02:01-B*41:02-C*17:03-DRB1*13:03-DQA1*05:05-DQB1*03:01  Kosovo 0.8060124
 78  A*24:02-B*35:03-C*12:03-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 0.8060124
 79  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:05-DQB1*03:19  Mexico Tixcacaltuyub Maya 0.746367
 80  A*29:02-B*44:03-C*16:01-DRB1*11:03-DQA1*05:05-DQB1*03:01  Mexico Tixcacaltuyub Maya 0.746367
 81  A*31:01-B*35:01-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Tixcacaltuyub Maya 0.746367
 82  A*68:03-B*39:05-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Tixcacaltuyub Maya 0.746367
 83  A*02-B*18-DRB1*11:04-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.6967641
 84  A*68:01-B*39:05-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.6881218
 85  A*11:01-B*07:02-C*07:01-DRB1*15:01-DQA1*05:05-DQB1*06:01  Brazil Puyanawa 0.6667150
 86  A*02:01:01-B*18:01:01-C*07:01:01-DRB1*11:04:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:02  Russia Belgorod region 0.6536153
 87  A*02:01:01-B*35:02:01-C*06:02:01-DRB1*11:04:01-DQA1*05:05:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*03:01  Russia Belgorod region 0.6536153
 88  A*02:01:01-B*51:01:01-C*04:01:01-DRB1*04:02:01-DQA1*05:05:01-DQB1*03:02-DPA1*01:03:01-DPB1*03:01  Russia Belgorod region 0.6536153
 89  A*03:01:01-B*18:01:01-C*07:01:01-DRB1*11:04:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.6536153
 90  A*25:01:01-B*18:01:01-C*12:03:01-DRB1*11:01:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:02  Russia Belgorod region 0.6536153
 91  A*02-B*35-DRB1*11:04-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.6106641
 92  A*02-B*35-DRB1*11:01-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.5921641
 93  DRB1*12:01-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.5016833
 94  A*24-B*35-DRB1*11:01-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.4680641
 95  A*02:01-B*18:01-C*07:01-DRB1*11:04-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  Mexico Chiapas Lacandon Mayans 0.4587218
 96  A*68:03-B*35:01-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*02:01  Mexico Chiapas Lacandon Mayans 0.4587218
 97  A*68:03-B*39:05-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.4587218
 98  A*01:01-B*15:39-C*03:03-E*01:01:01-F*01:01:01-G*01:06-DRB1*11:02-DQA1*05:05-DQB1*02:01  Portugal Azores Terceira Island 0.4386130
 99  A*01:01-B*41:01-C*06:02-E*01:03:01-F*01:01:01-G*01:06-DRB1*12:01-DQA1*05:05-DQB1*03:01  Portugal Azores Terceira Island 0.4386130
 100  A*02:01-B*07:02-C*07:01-E*01:03:02-F*01:01:01-G*01:01-DRB1*12:01-DQA1*05:05-DQB1*03:01  Portugal Azores Terceira Island 0.4386130

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 669) records   Pages: 1 2 3 4 5 6 7 of 7  


   

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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