Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 100 (from 1,285) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 13  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*34:01-B*40:02-DRB1*14:54  New Zealand Polynesians with Full Ancestry 4.762021
 2  A*34:01-B*40:02-DRB1*14:54  New Zealand Polynesians with Admixed History 3.704027
 3  A*24:02-B*40:01-DRB1*14:54  Taiwan Tzu Chi Morrow Donor Registry Aborigine 3.6970233
 4  A*24:02-B*48:01-DRB1*14:54  Taiwan Tzu Chi Morrow Donor Registry Aborigine 2.5620233
 5  A*02:06-B*39:01-DRB1*14:54  New Zealand Polynesians with Full Ancestry 2.381021
 6  A*11:01-B*40:01-DRB1*14:54  New Zealand Polynesians with Full Ancestry 2.381021
 7  A*02:01-B*51:01-C*02:02-DRB1*14:54-DQA1*01:04-DQB1*05:03  United Arab Emirates Abu Dhabi 1.920052
 8  A*24:02-B*39:01-DRB1*14:54  New Zealand Maori with Admixed History 1.9048105
 9  DRB1*14:54-DQB1*05:02  Taiwan pop 2 1.9000364
 10  A*02:06-B*39:01-DRB1*14:54  New Zealand Polynesians with Admixed History 1.852027
 11  A*11:01-B*40:01-DRB1*14:54  New Zealand Polynesians with Admixed History 1.852027
 12  DRB1*14:54-DQB1*05:03  Taiwan pop 2 1.6000364
 13  A*02:06-B*48:01-DRB1*14:54  Taiwan Tzu Chi Morrow Donor Registry Aborigine 1.3360233
 14  A*29:02-B*45:01-DRB1*14:54  Gaza 1.282042
 15  A*68:02-B*41:01-DRB1*14:54  Gaza 1.282042
 16  A*01:01-B*39:01-DRB1*14:54  New Zealand Maori with Full Ancestry 1.100046
 17  A*24:02-B*39:01-DRB1*14:54  New Zealand Maori with Full Ancestry 1.100046
 18  A*02:07-B*46:01-C*01:02-DRB1*14:54  Taiwan pop 2 1.0000364
 19  A*11:01:01-B*39:01:01-C*07:02:01-DRB1*14:54:01-DQB1*03:01:01  Vietnam Kinh 0.9900101
 20  DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.8403833
 21  A*01:01-B*35:01-C*12:03-DRB1*14:54-DQA1*01:01-DQB1*05:03  Kosovo 0.8060124
 22  A*32:01-B*58:02-C*06:02-DRB1*14:54-DQB1*05:01-DPB1*55:01  Tanzania Maasai 0.7987336
 23  DRB1*14:54-DQB1*05:03  Italy pop 5 0.7300975
 24  A*02:01-B*46:01-DRB1*14:54  Hong Kong Chinese cord blood registry 0.72753,892
 25  A*30:10-B*53:01-C*06:02-DRB1*14:54-DQB1*03:02-DPB1*17:01  Tanzania Maasai 0.6390336
 26  A*02:01:01-B*15:04:01-C*02:10:01-DRB1*14:54:01-DQB1*06:04:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 27  A*26:01:01-B*51:01:01-C*07:06:01-DRB1*14:54:01-DQB1*03:02:01-DPA1*02:02:02-DPB1*04:02:01  Brazil Rio de Janeiro Parda 0.5882170
 28  A*34:02:01-B*53:01:01-C*16:01:01-DRB1*14:54:01-DQB1*06:02:01-DPA1*02:01:01-DPB1*131:01:01  Brazil Rio de Janeiro Parda 0.5882170
 29  A*68:01:02-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 Parda 0.5882170
 30  A*24:02:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.5837521
 31  A*11:01-B*35:01-C*04:01-DRB1*14:54-DQB1*05:03  Italy pop 5 0.5800975
 32  A*02:01-B*46:01-C*01:02-DRB1*14:54  Hong Kong Chinese BMDR 0.56447,595
 33  A*02:07:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Tatars 0.5208192
 34  A*11:01:01:01-B*35:03:01-C*04:01:01-DRB1*14:54:01-DQB1*05:03:01  Russia Bashkortostan, Tatars 0.5208192
 35  B*35:01-DRB1*14:54  Italy pop 5 0.5000975
 36  A*02:07:01-B*07:02:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01  Vietnam Kinh 0.4950101
 37  A*01:01-B*39:01-DRB1*14:54  New Zealand Maori with Admixed History 0.4762105
 38  A*25:01-B*44:02-DRB1*14:54  New Zealand Maori with Admixed History 0.4762105
 39  A*34:01-B*40:02-DRB1*14:54  New Zealand Maori with Admixed History 0.4762105
 40  A*02:07:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.45635,266
 41  A*02:01-B*35:01-C*04:01-DRB1*14:54-DQB1*05:03  Italy pop 5 0.4400975
 42  A*25:01:01-B*44:27:01-C*07:04:01-DRB1*14:54:01-DQA1*01:02:02-DQB1*05:02-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 43  A*02:01:01:01-B*40:01:01-C*03:04:01-DRB1*14:54:01-DQB1*05:03  Russia Bashkortostan, Bashkirs 0.4167120
 44  A*24:02:01:01-B*58:01:01-C*15:02:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Bashkirs 0.4167120
 45  A*24:02:01-B*35:01:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03  Russia Bashkortostan, Bashkirs 0.4167120
 46  A*24:02:01-B*48:01:01-C*04:01:01-DRB1*14:54:01-DQB1*05:03  Russia Bashkortostan, Bashkirs 0.4167120
 47  A*33:01:01-B*14:02:01-C*15:02:01:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Bashkirs 0.4167120
 48  A*02:01-B*40:01-C*03:04-DRB1*14:54-DQA1*01:01-DQB1*05:03  Kosovo 0.4030124
 49  A*03:01-B*18:01-C*07:01-DRB1*14:54-DQA1*01:01-DQB1*05:03  Kosovo 0.4030124
 50  A*32:01-B*51:08-C*16:02-DRB1*14:54-DQA1*01:01-DQB1*06:09  Kosovo 0.4030124
 51  A*02:01-B*35:01-C*04:01-DRB1*14:54  Italy pop 5 0.4000975
 52  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.3891521
 53  A*23:01:01-B*50:02-C*04:01:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Caucasian 0.3891521
 54  A*11:01-B*35:01-C*04:01-DRB1*14:54-DQB1*05:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.37604,335
 55  A*02:07:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DQB1*05:02:01  China Zhejiang Han 0.36511,734
 56  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
 57  A*03:01:01-B*81:01-C*04:01:01-DRB1*14:54:01-DQB1*06:02:01-DPB1*04:01:01  South African Black 0.3520142
 58  A*43:01-B*42:01:01-C*06:02:01-DRB1*14:54:01-DQB1*06:02:01-DPB1*02:01:02  South African Black 0.3520142
 59  A*68:03-B*35:16-C*04:01-DRB1*14:54-DQB1*05:03  Mexico Mexico City Mestizo population 0.3497143
 60  B*35:16-C*04:01-DRB1*14:54-DQB1*05:03  Mexico Mexico City Mestizo population 0.3497143
 61  DRB1*14:54-DQB1*05:03  Mexico Mexico City Mestizo population 0.3497143
 62  A*33:03-B*35:03-C*12:03-DRB1*14:54  Hong Kong Chinese BMDR 0.33727,595
 63  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*14:54:01-DQA1*01:04:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*03:01  Russia Belgorod region 0.3268153
 64  A*02:01:01-B*15:03-C*04:01:01-DRB1*14:54:01-DQA1*02:01:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:02  Russia Belgorod region 0.3268153
 65  A*24:02:01-B*50:01:01-C*03:04:01-DRB1*14:54:01-DQA1*01:04:01-DQB1*02:02-DPA1*01:03:01-DPB1*02:01:02  Russia Belgorod region 0.3268153
 66  A*02:01:01-B*39:01:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*02:02:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 67  A*02:01:01-B*45:01:01-C*16:01:01-DRB1*14:54:01-DQB1*02:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 68  A*03:02:01-B*35:03:01-C*15:02:01-DRB1*14:54:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 69  A*03:02:01-B*51:01:01-C*15:02:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 70  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*14:54:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 71  A*24:02:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Caucasian 0.3125405
 72  A*24:02:01-B*39:06:02-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*10:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 73  A*26:08:01-B*15:01:01-C*03:03:01-DRB1*14:54:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*57:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 74  A*29:02:01-B*35:01:01-C*16:01:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*02:01:08-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.3105405
 75  A*33:03-B*35:03-DRB1*14:54  Hong Kong Chinese cord blood registry 0.30383,892
 76  A*02:01-B*07:02-C*07:02-DRB1*14:54-DQB1*05:03  Italy pop 5 0.2900975
 77  B*51:01-DRB1*14:54  Italy pop 5 0.2900975
 78  A*02:01:01-B*51:06:01-C*14:02:01-DRB1*14:54:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.2870174
 79  DRB1*14:54-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.2705833
 80  A*02:11:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 81  A*24:02:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 82  A*32:01:01-B*51:01:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 83  A*01:01:01:01-B*52:01:01:02-C*12:02:02-DRB1*14:54:01-DQB1*05:03:01  Russia Bashkortostan, Tatars 0.2604192
 84  A*02:06:01-B*51:01:01-C*15:02:01:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Tatars 0.2604192
 85  A*23:01:01-B*51:01:01-C*04:01:01-DRB1*14:54:01-DQB1*06:09:01  Russia Bashkortostan, Tatars 0.2604192
 86  A*24:02:01:01-B*57:01:01-C*03:04:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Tatars 0.2604192
 87  A*33:03:01-B*18:01:01-C*12:03:01:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Tatars 0.2604192
 88  A*11:01-B*35:01-C*04:01-DRB1*14:54  Italy pop 5 0.2600975
 89  A*11:01-B*40:01-C*07:02-DRB1*14:54  Hong Kong Chinese BMDR 0.21677,595
 90  B*35:03-DRB1*14:54  Italy pop 5 0.2100975
 91  A*02:01-B*51:01-C*15:02-DRB1*14:54  Italy pop 5 0.2000975
 92  A*03:01-B*35:01-C*04:01-DRB1*14:54  Italy pop 5 0.2000975
 93  A*01:01:01-B*15:16:01-C*04:01:01-DRB1*14:54:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 94  A*01:01:01-B*50:02-C*04:01:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 95  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
 96  A*02:07:01-B*51:02:01-C*15:02:01-DRB1*14:54:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 97  A*03:01:01-B*18:01:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Caucasian 0.1946521
 98  A*24:02:01-B*49:01:01-C*04:01:01-DRB1*14:54:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 99  A*30:04:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Caucasian 0.1946521
 100  A*36:01-B*55:01:01-C*03:03:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*02:01:04-DPB1*13:01:01  Brazil Rio de Janeiro Caucasian 0.1946521

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 1,285) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 13  


   

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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