Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

Population:  Country:  Source of dataset : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 100 (from 260) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*10:01-DQA1*01:04-DQB1*05:01  India Northeast Mathur 8.1000155
 2  DRB1*10:01-DQA1*01:04-DQB1*05:01  India Uttar Pradesh 7.7000202
 3  DRB1*10:01-DQA1*01:04-DQB1*05:01  India Northeast Rastogi 6.8000196
 4  DRB1*10:01-DQA1*01:04-DQB1*05:01  India Northeast Sunni 4.2000188
 5  DRB1*14-DQA1*01:04-DQB1*05:03  Italy pop 2 3.800053
 6  DRB1*12:01-DQA1*01:04-DQB1*05:01  Cameroon Yaounde 3.600092
 7  DRB1*10:01-DQA1*01:04-DQB1*05:01  India Northeast Vaish 3.5000198
 8  DRB1*10:01-DQA1*01:04-DQB1*05:01  India Northeast Kayastha 3.4000190
 9  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Northeast Lachung 3.100058
 10  DRB1*14:05-DQA1*01:04:01-DQB1*05:03:01  South Korea pop 5 3.1000467
 11  DRB1*14:05-DQA1*01:04-DQB1*05:03:01-DPB1*05:01  South Korea pop 2 3.0000207
 12  DRB1*14:01-DQA1*01:04-DQB1*05:02  South Korea pop 1 2.9000324
 13  DRB1*01-DQA1*01:04-DQB1*05:01  Mexico Guadalajara Mestizo 2.800054
 14  DRB1*14-DQA1*01:04-DQB1*05:03  Czech Republic pop 3 2.8000180
 15  DRB1*10:01-DQA1*01:04-DQB1*05:01  India Northeast Shia 2.6000190
 16  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Northeast Mathur 2.5000155
 17  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Northeast Mech 2.500063
 18  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Northeast Rajbanshi 2.400098
 19  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Northeast Kayastha 2.2000190
 20  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Uttar Pradesh 2.2000202
 21  DRB1*14:05-DQA1*01:04-DQB1*05:03  South Korea pop 1 2.2000324
 22  DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*05:01  Hong Kong Chinese HKBMDR. DQ and DP 2.02391,064
 23  DRB1*14:01-DQA1*01:04-DQB1*05:03  USA European American 2.00001,899
 24  DRB1*14:01-DQA1*01:04-DQB1*05:03  Greece pop3 2.0000246
 25  A*02:01-B*51:01-C*02:02-DRB1*14:54-DQA1*01:04-DQB1*05:03  United Arab Emirates Abu Dhabi 1.920052
 26  DRB1*10-DQA1*01:04-DQB1*05:01  Italy pop 2 1.900053
 27  DRB1*14:01-DQA1*01:04-DQB1*05:02-DPB1*05:01  South Korea pop 1 1.8000324
 28  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Northeast Vaish 1.7000198
 29  DRB1*14:05-DQA1*01:04-DQB1*05:03-DPB1*05:01  South Korea pop 1 1.7000324
 30  DRB1*14:01-DQA1*01:04:01-DQB1*05:02  South Korea pop 5 1.5000467
 31  DRB1*14:01-DQA1*01:04-DQB1*05:03:01  Russia Northwest Slavic 1.5000200
 32  DRB1*14:01-DQA1*01:04:01-DQB1*05:03:01  South Korea pop 5 1.4000467
 33  DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  Hong Kong Chinese HKBMDR. DQ and DP 1.34091,064
 34  A*02-B*40-DRB1*14-DQA1*01:04-DQB1*05:01  Georgia Svaneti Region Svan 1.300080
 35  DRB1*01:01-DQA1*01:04-DQB1*05:01  India Uttar Pradesh 1.2000202
 36  DRB1*10:01-DQA1*01:04-DQB1*05:01  Cameroon Yaounde 1.200092
 37  DRB1*14:01-DQA1*01:04-DQB1*05:03:01  Cameroon Yaounde 1.200092
 38  DRB1*14:05-DQA1*01:04-DQB1*05:03-DPB1*05:01  South Korea pop 11 1.2000149
 39  DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 1.0952833
 40  DRB1*10:01-DQA1*01:04-DQB1*05:01  Greece pop3 1.0000246
 41  DRB1*14:01-DQA1*01:04-DQB1*05:03  India Northeast Rastogi 1.0000196
 42  A*68:01-B*35:01-C*16:02-DRB1*14:04-DQA1*01:04-DQB1*05:03  United Arab Emirates Abu Dhabi 0.960052
 43  DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.8403833
 44  A*80:01-B*57:02-C*18:02-DRB1*10:01-DQA1*01:04-DQB1*05:01  Mexico Tixcacaltuyub Maya 0.746367
 45  DRB1*10:01-DQA1*01:04-DQB1*05:01  USA European American 0.71001,899
 46  DRB1*13:01-DQA1*01:04-DQB1*06:04  Spain Las Alpujarras 0.590085
 47  DQA1*01:04-DQB1*05:03-DPA1*02:01-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 0.46271,064
 48  DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*02:02  Hong Kong Chinese HKBMDR. DQ and DP 0.44691,064
 49  A*02:01-B*18:01-C*05:01-E*01:03:02-F*01:01:01-G*01:01-DRB1*14:01-DQA1*01:04-DQB1*03:01  Portugal Azores Terceira Island 0.4386130
 50  A*02:01-B*35:03-C*04:01-E*01:03:02-F*01:01:01-G*01:03-DRB1*14:01-DQA1*01:04-DQB1*02:02  Portugal Azores Terceira Island 0.4386130
 51  A*02:06-B*57:01-C*06:02-E*01:01:01-F*01:01:01-G*01:06-DRB1*14:01-DQA1*01:04-DQB1*03:03:02  Portugal Azores Terceira Island 0.4386130
 52  A*03:01-B*44:02-C*04:01-E*01:01:01-F*01:03:01-G*01:01-DRB1*14:06-DQA1*01:04-DQB1*05:03  Portugal Azores Terceira Island 0.4386130
 53  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQA1*01:04:02-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:02:01  Russian Federation Vologda Region 0.4202119
 54  A*02:01:01-B*18:01:01-C*12:03:01-DRB1*16:01:01-DQA1*01:04:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:01  Russian Federation Vologda Region 0.4202119
 55  A*31:01:02-B*54:01:01-C*01:02:01-DRB1*14:05:01-DQA1*01:04:01-DQB1*05:03:01-DPA1*02:01:02-DPB1*47:01:01  Russian Federation Vologda Region 0.4202119
 56  A*02:01-B*51:01-C*01:02-DRB1*14:01-DQA1*01:04-DQB1*05:03  Kosovo 0.4030124
 57  DQA1*01:04-DQB1*05:03-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.38541,064
 58  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
 59  A*23:01:01-B*44:03:01-C*12:03:01-DRB1*07:01:01-DQA1*01:04:01-DQB1*02:02-DPA1*01:03:01-DPB1*04:01  Russia Belgorod region 0.3268153
 60  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
 61  DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*02:02  Hong Kong Chinese HKBMDR. DQ and DP 0.30991,064
 62  DQA1*01:04-DQB1*05:02-DPA1*02:01-DPB1*14:01  Hong Kong Chinese HKBMDR. DQ and DP 0.30651,064
 63  A*23:01-B*15:05-C*03:03-DRB1*04:01-DQA1*01:04-DQB1*03:02-DPB1*04:01  South Africa Worcester 0.3000159
 64  DQA1*01:04-DQB1*05:03-DPA1*02:01-DPB1*14:01  Hong Kong Chinese HKBMDR. DQ and DP 0.29251,064
 65  DRB1*14:54-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.2705833
 66  DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.23891,064
 67  A*26:01-B*54:01-C*01:02-DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.23003,078
 68  DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*135:01  Hong Kong Chinese HKBMDR. DQ and DP 0.22401,064
 69  DQA1*01:04-DQB1*05:03-DPA1*01:03-DPB1*03:01  Hong Kong Chinese HKBMDR. DQ and DP 0.18241,064
 70  DRB1*14:04-DQA1*01:04-DQB1*05:03-DPA1*01:03-DPB1*04:02  China Zhejiang Han pop 2 0.1801833
 71  A*24:02-B*40:02-C*03:04-DRB1*14:54-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.16003,078
 72  A*02-B*18-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.1560641
 73  A*24-B*35-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.1405641
 74  A*11-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.1317641
 75  A*11:01-B*48:01-C*08:01-DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.13003,078
 76  DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*02:01-DPB1*14:01  China Zhejiang Han pop 2 0.1208833
 77  DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.1200833
 78  DQA1*01:04-DQB1*05:03-DPA1*04:01-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 0.11041,064
 79  DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.10381,064
 80  A*31:01-B*51:01-C*14:02-DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*01:03-DPB1*02:01  Japan pop 17 0.10003,078
 81  DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*02:01  China Zhejiang Han pop 2 0.0939833
 82  DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*31:01  Hong Kong Chinese HKBMDR. DQ and DP 0.09351,064
 83  DRB1*14:54-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*02:02  China Zhejiang Han pop 2 0.0896833
 84  DQA1*01:04-DQB1*05:02-DPA1*04:01-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 0.07971,064
 85  A*01-B*13-DRB1*14:02-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 86  A*02-B*13-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 87  A*02-B*44-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 88  A*02-B*45-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 89  A*02-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 90  A*02-B*53-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 91  A*03-B*18-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 92  A*03-B*41-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 93  A*03-B*45-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 94  A*03-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 95  A*29-B*15-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 96  A*29-B*38-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 97  DRB1*14:07-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.0720833
 98  A*02:01-B*40:02-C*15:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.07003,078
 99  A*02:01-B*44:03-C*14:03-DRB1*14:54-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*04:01  Japan pop 17 0.07003,078
 100  A*02:01-B*48:01-C*03:03-DRB1*14:54-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078

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 260) records   Pages: 1 2 3 of 3  


   

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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