Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 100 (from 531) records   Pages: 1 2 3 4 5 6 of 6  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*11:01:01-B*39:01:01-C*07:02:01-DRB1*14:54:01-DQB1*03:01:01  Vietnam Kinh 0.9900101
 2  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
 3  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
 4  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
 5  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
 6  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
 7  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
 8  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
 9  A*02:07:01-B*07:02:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01  Vietnam Kinh 0.4950101
 10  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
 11  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
 12  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
 13  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
 14  A*24:02:01-B*35:01:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03  Russia Bashkortostan, Bashkirs 0.4167120
 15  A*24:02:01-B*48:01:01-C*04:01:01-DRB1*14:54:01-DQB1*05:03  Russia Bashkortostan, Bashkirs 0.4167120
 16  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
 17  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
 18  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
 19  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
 20  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
 21  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
 22  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
 23  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
 24  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
 25  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
 26  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
 27  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
 28  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
 29  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
 30  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
 31  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
 32  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
 33  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
 34  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
 35  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
 36  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
 37  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
 38  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
 39  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
 40  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
 41  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
 42  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
 43  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
 44  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
 45  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
 46  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
 47  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
 48  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
 49  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
 50  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
 51  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
 52  A*68:02:01-B*55:01:01-C*18:01:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 53  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*02:01:01-DPB1*09:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 54  A*33:03:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DPB1*03:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.14185,266
 55  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.141523,595
 56  A*30:01:01-B*07:02:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01  India Kerala Malayalam speaking 0.1400356
 57  A*02:03:01-B*40:01:02-C*03:04:01-DRB1*14:54:01-DQB1*05:03:01  China Zhejiang Han 0.11531,734
 58  A*24:02:01-B*40:01:02-C*07:02:01-DRB1*14:54:01-DQB1*05:02:01  China Zhejiang Han 0.08521,734
 59  A*02:03:01-B*38:02:01-C*07:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.08435,266
 60  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.084123,595
 61  A*24:02:01-B*15:02:01-C*08:01:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.08195,266
 62  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.079923,595
 63  A*11:01:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.07295,266
 64  A*11:01:01-B*39:05:01-C*07:02:01-DRB1*14:54:01-DPB1*13:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.06635,266
 65  A*02:01:01-B*18:01:01-C*07:01:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.059323,595
 66  A*02:07:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.05845,266
 67  A*11:01:01-B*40:01:02-C*07:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.05835,266
 68  A*02:01:01-B*40:02:01-C*03:03:01-DRB1*14:54:01-DQB1*05:03:01  China Zhejiang Han 0.05771,734
 69  A*11:01:01-B*40:01:02-C*03:04:01-DRB1*14:54:01-DQB1*03:01:01  China Zhejiang Han 0.05771,734
 70  A*24:02:01-B*40:02:01-C*03:04:01-DRB1*14:54:01-DQB1*05:03:01  China Zhejiang Han 0.05771,734
 71  A*02:06:01-B*51:01:01-C*14:02:01-DRB1*14:54:01-DQB1*05:02:01  China Zhejiang Han 0.05601,734
 72  A*11:01:01-B*13:01:01-C*03:04:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.05545,266
 73  A*02:01:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.055023,595
 74  A*11:01:01-B*15:02:01-C*08:01:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.05445,266
 75  A*11:01:01-B*51:01:01-C*14:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.05075,266
 76  A*24:02:01-B*39:05:01-C*07:02:01-DRB1*14:54:01-DPB1*13:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04805,266
 77  A*11:01:01-B*55:01:01-C*03:03:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.047623,595
 78  A*24:02:01-B*40:01:02-C*07:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04765,266
 79  A*24:02:01-B*15:02:01-C*08:01:01-DRB1*14:54:01-DPB1*31:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04745,266
 80  A*24:02:01-B*18:01:01-C*07:01:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.047323,595
 81  A*11:01:01-B*18:01:01-C*07:04:01-DRB1*14:54:01-DPB1*03:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04675,266
 82  A*11:01:01-B*48:01:01-C*08:01:01-DRB1*14:54:01-DPB1*02:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04405,266
 83  A*02:07:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DPB1*02:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04375,266
 84  A*02:03:01-B*40:01:02-C*04:03:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04345,266
 85  A*11:01:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DQB1*05:02:01  China Zhejiang Han 0.04051,734
 86  A*33:03:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04015,266
 87  A*11:02:01-B*27:04:01-C*12:02:02-DRB1*14:54:01-DPB1*135:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03775,266
 88  A*24:02:01-B*38:02:01-C*07:02:01-DRB1*14:54:01-DPB1*04:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03775,266
 89  A*26:01:01-B*13:01:01-C*03:04:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03775,266
 90  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.037423,595
 91  A*02:06:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.03745,266
 92  A*02:01:01-B*55:01:01-C*03:03:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.036623,595
 93  A*33:03:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DPB1*02:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03655,266
 94  A*25:01:01-B*18:01:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.036323,595
 95  A*33:03:01-B*13:01:01-C*03:04:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03625,266
 96  A*11:01:01-B*40:01:02-C*07:02:01-DRB1*14:54:01-DPB1*03:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03345,266
 97  A*03:01:01-B*35:03:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.032823,595
 98  A*01:01:01-B*35:01:01-C*04:01:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.031823,595
 99  A*02:01:01-B*46:01:01-C*01:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03135,266
 100  A*02:07:01-B*27:04:01-C*12:02:02-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03105,266

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).


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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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