Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
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Displaying 1 to 100 (from 412) records   Pages: 1 2 3 4 5 of 5  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*68:01-B*51:01-DRB1*11:01-DQB1*03:01  USA Alaska Yupik 5.0000252
 2  A*02:01-B*51:01-DRB1*11:01-DQB1*03:01  Iran Yazd 2.678656
 3  A*24:02-B*51:01-DRB1*11:01-DQB1*03:01  USA Alaska Yupik 2.5000252
 4  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
 5  A*24:19-B*51:01-DRB1*11:01-DQB1*03:01  Iran Yazd 1.785756
 6  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 1.6130124
 7  A*23:01-B*51:01-DRB1*11:01-DQB1*03:01  Tunisia Gabes 1.570095
 8  A*02:01:01-B*51:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 1.4000215
 9  A*02:01:01-B*51:01:01-C*02:02:02-DRB1*11:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 1.1765170
 10  A*24:02-B*51:01-C*01:02-DRB1*11:01-DQB1*03:01  Colombia North Wiwa El Encanto 0.961552
 11  A*02:01-B*51:01-C*16:02-DRB1*11:01-DQA1*01:02-DQB1*03:01  United Arab Emirates Abu Dhabi 0.960052
 12  A*26:08-B*51:01-DRB1*11:01-DQB1*03:01  Iran Yazd 0.892956
 13  A*11:01-B*51:01-DRB1*11:01-DQB1*03:01  Iran Saqqez-Baneh Kurds 0.833360
 14  A*24:02-B*51:01-DRB1*11:01-DQB1*03:01  Iran Saqqez-Baneh Kurds 0.833360
 15  A*68:01-B*51:01-DRB1*11:01-DQB1*03:01  Chile Mapuche 0.770066
 16  A*68:01-B*51:01-C*03:04-DRB1*11:01-DQB1*03:01  USA NMDP Alaska Native or Aleut 0.71001,376
 17  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 18  A*24:02:01-B*51:01:01-C*01:02:01-DRB1*11:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*34:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 19  A*01:02-B*51:01-DRB1*11:01-DQB1*03:01  Iran Tabriz Azeris 0.515597
 20  A*02:01-B*51:01-C*01:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.4400975
 21  A*03:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.4400975
 22  A*23:01-B*51:01-C*02:02-E*01:01:01-F*01:01:01-G*01:04-DRB1*11:01-DQA1*05:05-DQB1*03:01  Portugal Azores Terceira Island 0.4386130
 23  A*24:02-B*51:01-C*03:04-DRB1*11:01-DQB1*03:01  USA NMDP Alaska Native or Aleut 0.42271,376
 24  A*02:01:01-B*51:01:01-C*01:02:01-DRB1*11:01:01-DQA1*05:05:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*02:01:02  Russian Federation Vologda Region 0.4202119
 25  A*03:01:01-B*51:01:01-C*07:02:01-DRB1*11:01:01-DQA1*05:05:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*03:01  Russian Federation Vologda Region 0.4202119
 26  A*03:01-B*51:01:01-C*04:01:01-DRB1*11:01:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*03:01  Russian Federation Vologda Region 0.4202119
 27  A*02:01:01:01-B*51:01:01-C*16:02:01-DRB1*11:01-DQB1*03:01  Russia Bashkortostan, Bashkirs 0.4167120
 28  A*11:01-B*51:01-C*15:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 0.4030124
 29  A*03:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India Northeast UCBB 0.3378296
 30  A*32:01-B*51:01-C*03:03-DRB1*11:01-DQB1*03:01  England North West 0.3000298
 31  A*02:01-B*51:01-C*14:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.2900975
 32  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.2900975
 33  A*24:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.2900975
 34  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.2810356
 35  A*24:02:13-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 36  A*02:01-B*51:01-C*14:02-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:01  USA San Diego 0.2600496
 37  A*11:01:01-B*51:01:01-C*14:02:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.24521,734
 38  A*68:01:01-B*51:01:01-C*15:04:01-DRB1*11:01:01-DQB1*03:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.233528,927
 39  A*29:02:01-B*51:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 40  A*31:01:02-B*51:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 41  A*31:01:02-B*51:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 42  A*02:01-B*51:01-C*16:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.21601,159
 43  A*24:02-B*51:01-C*01:02-DRB1*11:01-DQB1*03:01  England North West 0.2000298
 44  A*24:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  England North West 0.2000298
 45  A*01:01:01-B*51:01:01-C*02:02:02-DRB1*11:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Caucasian 0.1946521
 46  A*02:01:01-B*51:01:01-C*02:02:02-DRB1*11:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Caucasian 0.1946521
 47  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 48  A*03:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01-DPB1*04:01  Panama 0.1900462
 49  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.18701,999
 50  A*02:11-B*51:01-C*16:02-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 51  A*24:02-B*51:01-C*16:02-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 52  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.17104,335
 53  A*68:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India North UCBB 0.16755,849
 54  A*31:12-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India North UCBB 0.16245,849
 55  A*03:01-B*51:01-C*01:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.16101,159
 56  A*02:05-B*51:01-C*06:76-DRB1*11:01-DQB1*03:01-DPB1*17:01  Tanzania Maasai 0.1597336
 57  A*03:01-B*51:01-DRB1*11:01-DQB1*03:01  Mexico Mexico City Tlalpan 0.1515330
 58  A*11:01-B*51:01-DRB1*11:01-DQB1*03:01  Mexico Mexico City Tlalpan 0.1515330
 59  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.14504,856
 60  A*32:01-B*51:01-C*14:02-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 61  A*01:01-B*51:01-C*05:01-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 62  A*01:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 63  A*02:05-B*51:01-C*12:03-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 64  A*26:01:01-B*51:01:01-C*16:02:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.1400356
 65  A*29:01-B*51:01-C*01:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 66  A*31:01:02-B*51:01:01-C*14:02:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.1400356
 67  A*32:01-B*51:01-C*02:02-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.14001,999
 68  A*68:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 69  A*24:02-B*51:01-C*15:04-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.13604,856
 70  A*02:01-B*51:01-C*02:02-DRB1*11:01-DQB1*03:01  USA African American pop 4 0.13102,411
 71  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  USA NMDP American Indian South or Central America 0.12945,926
 72  A*02:01-B*51:01-C*14:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 73  A*02:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 74  A*11:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 75  A*03:02:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.126128,927
 76  A*31:12-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India East UCBB 0.12482,403
 77  A*02:01-B*51:01-C*16:02-DRB1*11:01-DQB1*03:01  India East UCBB 0.12372,403
 78  A*02:01-B*51:01-C*14:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.12204,856
 79  A*03:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India West UCBB 0.11965,829
 80  A*31:12-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.11894,204
 81  A*02:01:01:01-B*51:01:01-C*01:02:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.11381,510
 82  A*03:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.11204,856
 83  A*02:01-B*51:01-C*16:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.10904,856
 84  A*03:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India North UCBB 0.10715,849
 85  A*02:01-B*51:01-C*02:02-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 86  A*02:01-B*51:01-C*02:02-DRB1*11:01-DQB1*03:01-DPB1*04:01  Germany DKMS - German donors 0.10093,456,066
 87  A*24:02-B*51:01-C*14:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.09804,856
 88  A*11:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India North UCBB 0.09755,849
 89  A*02:11-B*51:01-C*16:02-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.08901,772
 90  A*11:01-B*51:01-C*14:02-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.08901,772
 91  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.088923,595
 92  A*03:02-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.08804,204
 93  A*68:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.08714,204
 94  A*24:02-B*51:01-C*01:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.08601,159
 95  A*68:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India East UCBB 0.08322,403
 96  A*03:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India North UCBB 0.08175,849
 97  A*68:01-B*51:01-C*07:01-DRB1*11:01-DQB1*03:01  India Tamil Nadu 0.08032,492
 98  A*03:01-B*51:01-C*15:02-DRB1*11:01-DQB1*03:01  India West UCBB 0.07895,829
 99  A*02:01:01-B*51:01:01-C*02:02:02-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.076623,595
 100  A*11:01-B*51:01-C*07:02-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*02:01  Sri Lanka Colombo 0.0700714

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 412) records   Pages: 1 2 3 4 5 of 5  


   

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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