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 100 (from 199) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02:01-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uro 13.5000105
 2  A*02:01-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 13.4500105
 3  A*02-B*35-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 10.448087
 4  A*02-B*35-DRB1*08:02-DQB1*04:02  Bolivia Quechua 10.050069
 5  A*02-B*35-DRB1*08:02-DQB1*04:02  Guatemala Mayan 8.4000132
 6  A*24:02-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 6.8100105
 7  A*24:02-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uro 6.8000105
 8  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  USA Alaska Yupik 6.0000252
 9  A*24-B*35-DRB1*08:02-DQB1*04:02  Guatemala Mayan 4.2000132
 10  B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 3.4965143
 11  B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 3.4965143
 12  A*02:01:01/02:01:09-B*35:01/35:02/35:03-C*03:04-DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 3.400044
 13  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uro 3.3000105
 14  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 3.2700105
 15  A*24-B*35-DRB1*08:02-DQB1*04:02  Bolivia Quechua 3.230069
 16  A*02-B*35-DRB1*08:02-DQB1*04:02  Colombia Wayu from Guajira Peninsula 3.130048
 17  A*02:06-B*35:01-DRB1*08:02-DQB1*04:02  USA Alaska Yupik 3.1000252
 18  A*24-B*35-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 3.085087
 19  B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 2.9900234
 20  A*31:01:02-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 2.777872
 21  A*02-B*35-DRB1*08:02-DQB1*04:02  Mexico Sinaloa Capomos Mayo Yoremes 2.500060
 22  A*24-B*35-DRB1*08:02-DQB1*04:02  Peru Lamas City Lama 2.400083
 23  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 2.381084
 24  A*68-B*35-DRB1*08:02-DQB1*04:02  Bolivia Quechua 2.250069
 25  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 2.0979143
 26  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 1.9697330
 27  A*68:01:02-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 1.6800105
 28  A*02:01-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 1.5000234
 29  B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 1.5000234
 30  B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 1.3986143
 31  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 1.388972
 32  A*68:01:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 1.388972
 33  A*68-B*35-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 1.174087
 34  A*02:01-B*35:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 35  A*02:06-B*35:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 36  A*68:01-B*35:12-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 37  A*68:01-B*35:20-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 38  A*24:02-B*35:43-C*01:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 1.06111,463
 39  A*24:57-B*35:43-C*01:02-DRB1*08:02-DQB1*04:02  Colombia North Wiwa El Encanto 0.961552
 40  A*31:01-B*35:43-C*01:02-DRB1*08:02-DQB1*04:02  Colombia North Wiwa El Encanto 0.961552
 41  A*68:01-B*35:68-C*03:02-DRB1*08:02-DQB1*04:02  Colombia North Wiwa El Encanto 0.961552
 42  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.9050221
 43  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.8600234
 44  A*02:01-B*35:12-C*04:01-DRB1*08:02-DRBX*NNNN-DQB1*04:02  USA NMDP Mexican or Chicano 0.8120261,235
 45  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Tixcacaltuyub Maya 0.746367
 46  A*01-B*35-DRB1*08:02-DQB1*04:02  Bolivia Quechua 0.720069
 47  A*02:01-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 48  A*02:06-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 49  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 50  A*24:02-B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 51  A*24:02-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 52  A*31:01-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 53  A*02:01:01-B*35:01:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 54  A*02:01:01-B*35:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 55  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 56  A*68:03:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 57  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*04:02  Nicaragua Managua 0.6494339
 58  B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6400234
 59  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.6300105
 60  A*02:01-B*35:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.6061330
 61  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.6061330
 62  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  USA NMDP Alaska Native or Aleut 0.58981,376
 63  A*02:01-B*35:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 64  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 65  A*24:02-B*35:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 66  A*26:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 67  A*02:01-B*35:06-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 68  A*02:01-B*35:12-C*04:01-DRB1*08:02-DRBX*NNNN-DQB1*04:02  USA NMDP Hispanic South or Central American 0.4762146,714
 69  A*02:01-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.46301,999
 70  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.4587218
 71  A*68:01-B*35:43-C*01:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*04:02  Nicaragua Managua 0.4329339
 72  B*35:43-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4300234
 73  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 74  A*02:01-B*35:43-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 75  A*02:06-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 76  A*24:02-B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 77  A*31:01-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 78  A*68:01-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 79  A*68:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02-DPB1*04:02  Panama 0.3800462
 80  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.37401,999
 81  A*01:01-B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 82  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 83  A*02:01-B*35:16-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 84  A*02:01-B*35:43-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 85  A*02:06-B*35:12-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 86  A*31:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 87  A*68:05-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 88  B*35:16-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 89  B*35:43-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 90  A*02:03:01-B*35:03:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 91  A*03:01:01-B*35:03:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 92  A*24:02:01-B*35:03:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 93  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 94  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 95  A*24:02-B*35:12-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 96  A*24:02-B*35:17-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:12-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 97  A*31:01-B*35:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 98  A*31:01-B*35:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 99  A*68:01-B*35:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 100  A*68:01-B*35:12-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218

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 199) records   Pages: 1 2 of 2  


   

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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