Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 90 (from 90) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*01:01:01-B*08:01:01-C*07:02:01  England Blood Donors of Mixed Ethnicity 0.0963519
 2  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00685,266
 3  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*02:01:02  Russian Federation Vologda Region 0.4202119
 4  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.02881,734
 5  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 6  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*04:02:01-DQB1*03:02:01  Poland BMR 0.002123,595
 7  A*01:01:01-B*08:01:01-C*07:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 8  A*02:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 9  A*02:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.024823,595
 10  A*02:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.130428,927
 11  A*02:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.192528,927
 12  A*02:03:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00655,266
 13  A*02:06:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04015,266
 14  A*02:06:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.002123,595
 15  A*02:11:01-B*08:01:01-C*07:02:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 16  A*03:01:01:01-B*08:01:01-C*07:02:01-DRB1*10:01-DQB1*05:01:01  Russia Bashkortostan, Bashkirs 0.4167120
 17  A*03:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01905,266
 18  A*03:01:01-B*08:01:01-C*07:02:01-DRB1*03:02:01-DQB1*03:02:01-DPB1*13:01:01  South African Black 0.3520142
 19  A*03:01:01-B*08:01:01-C*07:02:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.002123,595
 20  A*03:01:01-B*08:01:01-C*07:02:01-DRB1*11:01:01-DQA1*02:01:01-DQB1*03:01-DPA1*01:03:01-DPB1*03:01  Russia Belgorod region 0.3268153
 21  A*03:01:01-B*08:01:01-C*07:02:01-DRB1*12:02:01-DPB1*04:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00925,266
 22  A*03:01:01-B*08:01:01-C*07:02:01-DRB1*12:02:01-DQB1*03:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 23  A*03:02:01-B*08:01:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 24  A*03:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.030823,595
 25  A*03:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*04:01:01  China Zhejiang Han 0.02881,734
 26  A*03:02:01-B*08:01:01-C*07:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 27  A*03:02:01-B*08:01:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.008623,595
 28  A*03:02:01-B*08:01:01-C*07:02:01-DRB1*16:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 29  A*03:02:01-B*08:01:01-C*07:02:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.002223,595
 30  A*11:01:01:01-B*08:01:01-C*07:02:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 31  A*11:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00515,266
 32  A*11:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.05771,734
 33  A*11:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 34  A*11:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*05:02:01  China Zhejiang Han 0.02881,734
 35  A*11:01:01-B*08:01:01-C*07:02:01-DRB1*07:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 36  A*24:02:01:01-B*08:01:01-C*07:02:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 37  A*24:02:01:01-B*08:01:01-C*07:02:01:01-DRB1*08:01:01-DQB1*02:01  Russia Bashkortostan, Bashkirs 0.4167120
 38  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.003323,595
 39  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01455,266
 40  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.05731,734
 41  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.5750174
 42  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.033123,595
 43  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.667228,927
 44  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01-DQB1*02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 45  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*07:01:01-DPB1*02:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00835,266
 46  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002423,595
 47  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*07:01:01-DQB1*05:01:01  Poland BMR 0.001123,595
 48  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*07:01-DQB1*02:01  Costa Rica Central Valley Mestizo (G) 0.0509221
 49  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*07:01-DQB1*03:01  Costa Rica Central Valley Mestizo (G) 0.1584221
 50  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*07:01-DQB1*03:03  Costa Rica Central Valley Mestizo (G) 0.0170221
 51  A*24:07:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 52  A*25:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.003923,595
 53  A*26:01:01-B*08:01:01-C*07:02:01  England Blood Donors of Mixed Ethnicity 0.0963519
 54  A*26:01:01-B*08:01:01-C*07:02:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.16561,510
 55  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.01415,266
 56  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00895,266
 57  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03585,266
 58  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DPB1*17:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04715,266
 59  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.08651,734
 60  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.2870174
 61  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.7020356
 62  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 0.5376186
 63  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.015523,595
 64  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.330928,927
 65  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.233228,927
 66  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.593328,927
 67  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*17:01:01  Saudi Arabia pop 6 (G) 0.090828,927
 68  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*04:05:01-DPB1*02:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00915,266
 69  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*09:01:02-DPB1*03:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01905,266
 70  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*12:02:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00855,266
 71  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*12:10-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01905,266
 72  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.002123,595
 73  A*29:02:01:01-B*08:01:01-C*07:02:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 74  A*30:01:01-B*08:01:01-C*07:02:01-DRB1*13:01:01-DQB1*06:04:01-DPB1*51:01  South African Black 0.3520142
 75  A*32:01:01-B*08:01:01-C*07:02:01:01-DRB1*04:01:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 76  A*32:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.016223,595
 77  A*32:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.090528,927
 78  A*32:01:01-B*08:01:01-C*07:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 79  A*33:03:01-B*08:01:01-C*07:02:01  South African Indian population 1.000050
 80  A*33:03:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.02921,734
 81  A*33:03:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 0.8065186
 82  A*33:03:01-B*08:01:01-C*07:02:01-DRB1*13:02:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00615,266
 83  A*68:01:01:02-B*08:01:01-C*07:02:01:03-DRB1*03:01:02-DQB1*05:01  Russia Bashkortostan, Tatars 0.2604192
 84  A*68:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.094528,927
 85  A*68:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.614928,927
 86  A*68:01:01-B*08:01:01-C*07:02:01-DRB1*04:05-DQB1*03:02:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.120028,927
 87  A*68:01:01-B*08:01:01-C*07:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.106928,927
 88  A*68:01:01-B*08:01:01-C*07:02:01-DRB1*16:02:01-DQB1*05:02:01-DPB1*14:01:01  Saudi Arabia pop 6 (G) 0.147028,927
 89  A*68:01:02:02-B*08:01:01-C*07:02:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 90  A*68:01:02-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  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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