Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Displaying 1 to 86 (from 86) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*68-B*51-DRB1*13:02-DQB1*06:03  Colombia San Basilio de Palenque 2.381042
 2  A*68-B*51-C*06-DRB1*13-DQB1*06  Albanian Kosovo 1.2500120
 3  A*68:01-B*51:06-DRB1*13:01-DQB1*06:02  Iran Yazd 0.892956
 4  A*68:01:02-B*51:01:01-C*12:03:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Parda 0.5882170
 5  A*68:01-B*51:01-DRB1*13:01-DQB1*06:02  Iran Tabriz Azeris 0.515597
 6  A*68:01-B*51:01-C*15:02-E*01:01:01-F*01:01:02-G*01:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Portugal Azores Terceira Island 0.4386130
 7  A*68:01-B*51:01-C*05:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Kosovo 0.4030124
 8  A*68:01-B*51:01-C*12:03-DRB1*13:02-DQA1*01:02-DQB1*06:04  Kosovo 0.4030124
 9  A*68-B*51-DRB1*13-DQB1*06  Mexico Michoacan, Morelia 0.3311150
 10  A*68:01:02-B*51:01:01-C*16:02:01-DRB1*13:01:01-DQB1*06:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 11  A*68:01-B*51:01-C*15:02-DRB1*13:02:01-DQB1*06:04  England North West 0.2000298
 12  A*68:01:01-B*51:75-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*02:02:02-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 13  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.14215,849
 14  A*68-B*51-DRB1*13-DQB1*06  Mexico Coahuila, Torreon 0.1250396
 15  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.11365,849
 16  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  India East UCBB 0.10402,403
 17  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.09385,829
 18  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPA1*01:03-DPB1*02:01  United Arab Emirates Pop 1 0.0935570
 19  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Italy minority 0.08601,159
 20  A*68-B*51-DRB1*13-DQB1*06  Mexico Jalisco Rural 0.0853585
 21  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:110  India North UCBB 0.08505,849
 22  A*68:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.082023,595
 23  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.08164,204
 24  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.073611,446
 25  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.07312,492
 26  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Russia Karelia 0.07121,075
 27  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*09:01  Sri Lanka Colombo 0.0700714
 28  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*26:01  Sri Lanka Colombo 0.0700714
 29  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQA1*01:03-DQB1*06:110-DPB1*04:01  Sri Lanka Colombo 0.0700714
 30  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.06841,463
 31  A*68:01:02:02-B*51:01:01-C*15:02:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.06621,510
 32  A*68-B*51-C*16-DRB1*13-DQA1*01-DQB1*06  Spain, Castilla y Leon, Northwest, 0.06571,743
 33  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:110  India West UCBB 0.06505,829
 34  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.05982,492
 35  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:110  India Central UCBB 0.05954,204
 36  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.05895,849
 37  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.04945,829
 38  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.047611,446
 39  A*68:01-B*51:01-C*05:01-DRB1*13:01-DQB1*06:03  USA African American pop 4 0.04402,411
 40  A*68:01-B*51:06-C*15:02-DRB1*13:01-DQB1*06:03  USA Asian pop 2 0.04401,772
 41  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.04235,829
 42  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.04184,204
 43  A*68-B*51-C*07-DRB1*13-DQA1*01-DQB1*06  Spain, Castilla y Leon, Northwest, 0.04001,743
 44  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.039511,446
 45  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:110  India East UCBB 0.03832,403
 46  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India East UCBB 0.03562,403
 47  A*68:01-B*51:01-C*07:01-DRB1*13:02-DQB1*06:09  India South UCBB 0.034911,446
 48  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.03443,456,066
 49  A*68:01-B*51:01-C*02:02-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 50  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 51  A*68:01:01:02-B*51:01:01-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 52  A*68:01:02:01-B*51:01:01-C*14:02:01-DRB1*13:02:01-DQB1*06:04:01  Russia Nizhny Novgorod, Russians 0.03311,510
 53  A*68:01:02:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 54  A*68-B*51-C*02-DRB1*13-DQA1*01-DQB1*06  Spain, Castilla y Leon, Northwest, 0.03281,743
 55  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.03102,492
 56  A*68-B*51-C*05-DRB1*13-DQB1*06-DPB1*20  Norway ethnic Norwegians 0.03004,510
 57  A*68:01-B*51:01-C*14:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.02992,492
 58  A*68:01:02-B*51:01:01-C*16:02:01-DRB1*13:01:01-DQB1*06:03:01  China Zhejiang Han 0.02881,734
 59  A*68:01:02-B*51:01:01-C*14:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.025723,595
 60  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.02463,456,066
 61  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:110  India South UCBB 0.021811,446
 62  A*68:01-B*51:01-C*04:01-DRB1*13:01-DQB1*06:03  India East UCBB 0.02082,403
 63  A*68:01-B*51:01-C*07:01-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.02012,492
 64  A*68-B*51-C*14-DRB1*13-DQB1*06-DPB1*02  Norway ethnic Norwegians 0.02004,510
 65  A*68-B*51-C*15-DRB1*13-DQB1*06-DPB1*06  Norway ethnic Norwegians 0.02004,510
 66  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.01523,456,066
 67  A*68:01-B*51:01-C*01:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.01304,856
 68  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.01194,204
 69  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.01103,456,066
 70  A*68:01-B*51:09-C*18:01-DRB1*13:02-DQB1*06:04  USA African American pop 4 0.01102,411
 71  A*68-B*51-C*14-DRB1*13-DQB1*06-DPB1*03  Norway ethnic Norwegians 0.01004,510
 72  A*68-B*51-C*14-DRB1*13-DQB1*06-DPB1*04  Norway ethnic Norwegians 0.01004,510
 73  A*68:01-B*51:01-C*07:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.008711,446
 74  A*68:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:110  India West UCBB 0.00865,829
 75  A*68:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.008423,595
 76  A*68:01-B*51:01-C*15:04-DRB1*13:01-DQB1*06:03  India South UCBB 0.008411,446
 77  A*68:01-B*51:01-C*15:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.00705,849
 78  A*68:01-B*51:01-C*14:02-DRB1*13:02-DQB1*06:04  India South UCBB 0.004411,446
 79  A*68:01-B*51:01-C*15:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.004411,446
 80  A*68:01-B*51:01-C*15:07-DRB1*13:01-DQB1*06:03  India South UCBB 0.004411,446
 81  A*68:01-B*51:01-C*15:07-DRB1*13:02-DQB1*06:09  India South UCBB 0.004411,446
 82  A*68:01-B*51:06-C*14:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.004411,446
 83  A*68:01:01-B*51:01:01-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.003423,595
 84  A*68:01:02-B*51:01:01-C*15:02:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.002323,595
 85  A*68:01:02-B*51:01:01-C*14:02:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.002123,595
 86  A*68:02:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595

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).




   

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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