Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 100 (from 165) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*24:02-B*35:01-DRB1*11:01-DQB1*03:01  Iran Tabriz Azeris 3.092897
 2  A*01:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Kurd pop 2 2.500060
 3  A*03:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Saqqez-Baneh Kurds 2.500060
 4  A*24:02-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Iran Gorgan 2.340064
 5  A*02:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Kurd pop 2 1.700060
 6  A*01:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Saqqez-Baneh Kurds 1.666760
 7  A*02:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Saqqez-Baneh Kurds 1.666760
 8  A*24:02-B*35:01-DRB1*11:01-DQB1*03:01  USA South Dakota Lakota Sioux 1.4000302
 9  A*02:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Tabriz Azeris 1.030997
 10  A*32:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 0.9300215
 11  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Indian 0.9225271
 12  A*24:02-B*35:01-DRB1*11:01-DQB1*03:01  Iran Yazd 0.892956
 13  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.7020356
 14  A*68:01-B*35:01-DRB1*11:01-DQB1*03:01  Mexico Veracruz Xalapa 0.595284
 15  A*02:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Italy pop 5 0.5900975
 16  A*23:01-B*35:01-DRB1*11:01-DQB1*03:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 17  A*32:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.5620356
 18  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Andhra Pradesh Telugu Speaking 0.5376186
 19  A*11:01:01:01-B*35:01:01-C*04:01:01:05-DRB1*11:01:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.5208192
 20  A*11:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Tabriz Azeris 0.515597
 21  A*30:01-B*35:01-DRB1*11:01-DQB1*03:01  Iran Tabriz Azeris 0.515597
 22  A*66:01-B*35:01-C*03:02-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 23  A*32:01:01-B*35:01:10-C*04:01:01-DRB1*11:01:01-DQA1*05:05:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*02:01:02  Russian Federation Vologda Region 0.4202119
 24  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  India Tamil Nadu 0.41222,492
 25  A*24:02-B*35:01-C*04:01-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 0.4030124
 26  A*01:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.34501,159
 27  A*02:01-B*35:01-DRB1*11:01-DQB1*03:01  Mexico Mexico City Tlalpan 0.3030330
 28  A*24:02-B*35:01-DRB1*11:01-DQB1*03:01  Mexico Mexico City Tlalpan 0.3030330
 29  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.28804,856
 30  A*01:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Karnataka Kannada Speaking 0.2870174
 31  A*32:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 32  A*02:06:01-B*35:01:01-C*03:03:01-DRB1*11:01:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.2604192
 33  A*24:02-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.22404,856
 34  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.2101714
 35  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.15204,856
 36  A*01:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 37  A*03:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.134123,595
 38  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.13301,772
 39  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 40  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01-DPB1*04:01  Russia Karelia 0.11801,075
 41  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA NMDP Black South or Central American 0.11794,889
 42  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Malay 0.1052951
 43  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.104823,595
 44  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 45  A*01:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.09401,999
 46  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.09401,999
 47  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  India UCBB_Central Indian HLA 0.09394,204
 48  A*24:02-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  India UCBB_Central Indian HLA 0.08794,204
 49  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA African American pop 4 0.08702,411
 50  A*33:01-B*35:01-C*06:02-DRB1*11:01-DQB1*03:01  USA African American pop 4 0.08702,411
 51  A*68:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA African American pop 4 0.08702,411
 52  A*03:01-B*35:01-C*02:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.08601,159
 53  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.08601,159
 54  A*01:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  India Tamil Nadu 0.08342,492
 55  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  India Tamil Nadu 0.07692,492
 56  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01-DPB1*02:01  Russia Karelia 0.07681,075
 57  A*26:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.07504,856
 58  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  India UCBB_Central Indian HLA 0.07484,204
 59  A*24:02-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*13:01  Sri Lanka Colombo 0.0700714
 60  A*26:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 61  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 62  A*32:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*83:01  Sri Lanka Colombo 0.0700714
 63  A*33:03-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 64  A*33:03-B*35:01-C*04:01-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*13:01  Sri Lanka Colombo 0.0700714
 65  A*02:06-B*35:01-C*03:03-DRB1*11:01-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*02:02  Japan pop 17 0.07003,078
 66  A*31:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 67  A*11:01:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.06621,510
 68  A*01:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  India UCBB_Central Indian HLA 0.06134,204
 69  A*02:01:01-B*35:01:01-C*03:03:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.05771,734
 70  A*02:06:01-B*35:01:01-C*03:03:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.05771,734
 71  A*02:07:01-B*35:01:01-C*03:03:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.05771,734
 72  A*31:01-B*35:01-C*03:03-DRB1*11:01-DQB1*03:01-DPB1*02:01  Russia Karelia 0.05651,075
 73  A*24:02:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.05431,510
 74  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.05304,856
 75  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Malay 0.0526951
 76  A*24:07-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Malay 0.0526951
 77  A*30:01-B*35:01-C*06:02-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.04701,999
 78  A*31:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.04701,999
 79  A*01:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA African American pop 4 0.04402,411
 80  A*02:01-B*35:01-C*03:03-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 81  A*24:03-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 82  A*02:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 83  A*24:02-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 84  A*24:03-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 85  A*68:01-B*35:01-C*07:04-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 86  A*03:02-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.04204,856
 87  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Colombia Bogotá Cord Blood 0.04081,463
 88  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.040423,595
 89  A*68:01-B*35:01-C*07:01-DRB1*11:01-DQB1*03:01  India Tamil Nadu 0.04012,492
 90  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01-DPB1*04:01  Germany DKMS - German donors 0.03723,456,066
 91  A*02:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 92  A*29:02-B*35:01-C*02:02-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 93  A*29:02-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 94  A*11:01-B*35:01-C*04:01-DRB1*11:01-DQB1*03:01-DPB1*04:01  Germany DKMS - German donors 0.03323,456,066
 95  A*11:01:01:01-B*35:01:01-C*04:01:01:05-DRB1*11:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 96  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 97  A*26:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 98  A*31:01:02-B*35:01:01-C*04:01:01-DRB1*11:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 99  A*02:01-B*35:01-C*03:03-DRB1*11:01-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 100  A*02:07-B*35:01-C*03:03-DRB1*11:01-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078

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 165) 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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