Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 100 (from 416) records   Pages: 1 2 3 4 5 of 5  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DQA1*01:03-DQB1*06:01  Japan Fukuoka 22.100086
 2  DQA1*01:03-DQB1*06:01  India Bombay 22.000059
 3  DRB1*08:03:02-DQA1*01:03-DQB1*06:01  Australia New South Wales Aborigine 9.4000177
 4  DQA1*01:03-DQB1*06:01  Israel Iranian Jews 8.8000101
 5  DQA1*01:03-DQB1*06:01  China, Xinjiang Uyghur Autonomous Region Hui 8.750040
 6  DRB1*15:02-DQA1*01:03-DQB1*06:01  Japan pop 2 8.2000916
 7  DRB1*15:02-DQA1*01:03-DQB1*06:01  Iran Kurd 8.0000100
 8  DQA1*01:03-DQB1*06:01  China, Xinjiang Uyghur Autonomous Region Han 7.860070
 9  DRB1*08:03-DQA1*01:03-DQB1*06:01  Japan pop 2 7.4000916
 10  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPA1*02:01-DPB1*09:01  Japan pop 17 7.32003,078
 11  DRB1*08:03:02-DQA1*01:03-DQB1*06:01  South Korea pop 5 7.1000467
 12  DRB1*08:03-DQA1*01:03-DQB1*06:01  South Korea pop 1 6.7000324
 13  DRB1*15:02-DQA1*01:03-DQB1*06:01  Mongolia Tarialan Khoton 6.500085
 14  DQA1*01:03-DQB1*06:01  Israel Moroccan Jews 6.3000113
 15  DQA1*01:03-DQB1*06:01  Tunisia 6.1000100
 16  DQA1*01:03-DQB1*06:01  Israel Arab 5.7000109
 17  DRB1*08:03-DQA1*01:03-DQB1*06:01  China Urumqi Han 5.100059
 18  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*05:01  South Korea pop 11 5.1000149
 19  DRB1*15:02-DQA1*01:03-DQB1*06:01  Iran Azeri 5.0000100
 20  DQA1*01:03-DQB1*06:01  China, Xinjiang Uyghur Autonomous Region Uyghur 4.930071
 21  DRB1*15:02-DQA1*01:03-DQB1*06:01  Mongolia Ulaanbaatar Khalkha 4.900041
 22  DQA1*01:03-DQB1*06:01  Russia Tuva pop 2 4.7000169
 23  DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*05:01  Hong Kong Chinese HKBMDR. DQ and DP 3.88121,064
 24  DQA1*01:03-DQB1*06:01  China, Xinjiang Uyghur Autonomous Region Kazakh 3.850052
 25  DRB1*15:02-DQA1*01:03-DQB1*06:01  Turkey pop 1 3.8000250
 26  DRB1*15:02-DQA1*01:03-DQB1*06:01  Iran Yazd Zoroastrian 3.800065
 27  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Uttar Pradesh 3.8000202
 28  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 3.7695833
 29  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*05:01  China Canton Han 3.7000264
 30  DRB1*15-DQA1*01:03-DQB1*06:01:01  Iran 3.500058
 31  DRB1*15:02-DQA1*01:03-DQB1*06:01  Italy Sardinia Tempio 3.300091
 32  DRB1*15:02-DQA1*01:03-DQB1*06:01  Tunisia 3.0000100
 33  DRB1*15:01:01-DQA1*01:03-DQB1*06:01  Russia Siberia Lower Yenisey Ket 2.900017
 34  DRB1*15:02-DQA1*01:03-DQB1*06:01  South Korea pop 1 2.9000324
 35  A*11:01-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01  United Arab Emirates Abu Dhabi 2.880052
 36  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Vaish 2.8000198
 37  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Kayastha 2.8000190
 38  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Kayastha 2.8000190
 39  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Vaish 2.8000198
 40  DRB1*15:02-DQA1*01:03-DQB1*06:01  Algeria pop 2 2.8000106
 41  DRB1*15-DQA1*01:03-DQB1*06:01  Italy pop 2 2.800053
 42  DQA1*01:03-DQB1*06:01  Israel Yemenite Jews 2.700076
 43  DRB1*15:02-DQA1*01:03-DQB1*06:01  Iran Fars Parsi 2.700073
 44  DQA1*01:03-DQB1*06:01  Israel Ashkenazi Jews pop 2 2.6000132
 45  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*05:01  South Korea pop 1 2.6000324
 46  DRB1*15:02-DQA1*01:03-DQB1*06:01  South Korea pop 5 2.6000467
 47  DRB1*15:02-DQA1*01:03-DQB1*06:01  China Urumqi Kazak 2.400042
 48  DRB1*15:01-DQA1*01:03-DQB1*06:01  Russia Tuva pop3 2.300044
 49  DRB1*15:01-DQA1*01:03-DQB1*06:01  Russia Siberia Sulamai Ket 2.300022
 50  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*05:01  South Korea pop 2 2.2000207
 51  DRB1*15:02-DQA1*01:03-DQB1*06:01  Greece pop3 2.2000246
 52  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Mathur 2.1000155
 53  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Rastogi 2.0000196
 54  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Rajbanshi 2.000098
 55  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Rastogi 2.0000196
 56  DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*09:01  South Korea pop 1 2.0000324
 57  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01  United Arab Emirates Abu Dhabi 1.920052
 58  DRB1*15-DQA1*01:03-DQB1*06:01  Russia Smolensk 1.9000156
 59  DRB1*15-DQA1*01:03-DQB1*06:01  Belarus Brest Region 1.9000105
 60  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Uttar Pradesh 1.8000202
 61  DRB1*15:02-DQA1*01:03-DQB1*06:01  USA San Francisco Caucasian 1.8000220
 62  DQA1*01:03-DQB1*06:01  Israel Libyan Jews 1.7000119
 63  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:01  South Korea pop 2 1.7000207
 64  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Lachung 1.700058
 65  DRB1*15:02-DQA1*01:03-DQB1*06:01  Italy Sardinia Lanusei 1.700087
 66  DRB1*15:02-DQA1*01:03-DQB1*06:01  Italy Sardinia Oristano 1.600091
 67  A*11-B*52-DRB1*15:02-DQA1*01:03-DQB1*06:01  Morocco 1.500096
 68  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:01  South Korea pop 1 1.5000324
 69  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:02  South Korea pop 2 1.5000207
 70  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Mech 1.500063
 71  DRB1*15-DQA1*01:03-DQB1*06:01  Belarus Vitebsk Region 1.500070
 72  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Sunni 1.4000188
 73  DRB1*15:02-DQA1*01:03-DQB1*06:01  Russia Siberia Khanty Mansi 1.400068
 74  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*09:01  USA San Diego 1.3020496
 75  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Sunni 1.3000188
 76  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*02:02  China Zhejiang Han pop 2 1.2849833
 77  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:02  South Korea pop 1 1.2000324
 78  DRB1*15:02-DQA1*01:03-DQB1*06:01  Russia Siberia Irkutsk Tofalar 1.200043
 79  DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*09:01  South Korea pop 2 1.2000207
 80  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 1.1633833
 81  DRB1*15:02-DQA1*01:03-DQB1*06:01  Russia Tuva pop3 1.100044
 82  DRB1*15:02:01-DQA1*01:03-DQB1*06:01  Russia Northwest Slavic 1.0000200
 83  A*33:03-B*15:17-C*07:01-DRB1*13:02-DQA1*01:03-DQB1*06:01  United Arab Emirates Abu Dhabi 0.960052
 84  A*33:03-B*58:01-C*07:02-DRB1*16:02-DQA1*01:03-DQB1*06:01  United Arab Emirates Abu Dhabi 0.960052
 85  A*02:07-B*46:01-C*01:02-DRB1*08:03-DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*02:02  Japan pop 17 0.91003,078
 86  A*02-B*57-DRB1*15-DQA1*01:03-DQB1*06:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.9100112
 87  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.78003,078
 88  A*02:07-B*46:01-C*01:02-DRB1*08:03-DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.68003,078
 89  DRB1*15:02-DQA1*01:03-DQB1*06:01  USA European American 0.66001,899
 90  A*01:01:01-B*52:01:01-C*12:02:02-DRB1*15:02-DQA1*01:03:01-DQB1*06:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.6536153
 91  A*02:01:01-B*52:01:01-C*12:02:02-DRB1*15:02-DQA1*01:03:01-DQB1*06:01-DPA1*01:03:01-DPB1*04:01  Russia Belgorod region 0.6536153
 92  A*02:11-B*14:02-C*08:02-DRB1*01:02-DQA1*01:03-DQB1*06:01-DPB1*13:01  South Africa Worcester 0.6000159
 93  A*02:11-B*40:06-C*15:02-DRB1*15:01-DQA1*01:03-DQB1*06:01-DPB1*02:01  Sri Lanka Colombo 0.5602714
 94  A*11:01-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*04:01  Sri Lanka Colombo 0.4902714
 95  A*01-B*40-DRB1*15-DQA1*01:03-DQB1*06:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112
 96  A*02-B*46-DRB1*08-DQA1*01:03-DQB1*06:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112
 97  A*11-B*52-DRB1*15-DQA1*01:03-DQB1*06:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112
 98  A*11-B*57-DRB1*15-DQA1*01:03-DQB1*06:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112
 99  A*24-B*57-DRB1*15-DQA1*01:03-DQB1*06:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112
 100  A*31-B*52-DRB1*15-DQA1*01:03-DQB1*06:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112

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 416) 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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