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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Displaying 1 to 87 (from 87) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  India Andhra Pradesh Telugu Speaking 1.0753186
 2  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.9300215
 3  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*13:01:01  Saudi Arabia pop 6 (G) 0.629428,927
 4  A*68:01-B*51:01-C*15:02-E*01:01:01-F*01:01:02-G*01:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Portugal Azores Terceira Island 0.4386130
 5  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.4210356
 6  A*02:01:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Russia Bashkortostan, Bashkirs 0.4167120
 7  A*02:06:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03  Russia Bashkortostan, Bashkirs 0.4167120
 8  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.377128,927
 9  A*02:06:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Russia Bashkortostan, Tatars 0.2604192
 10  A*29:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA NMDP Caribean Indian 0.233714,339
 11  A*33:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 12  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*02:01:01-DPB1*11:01:01  Brazil Rio de Janeiro Caucasian 0.1945521
 13  A*03:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Northeast UCBB 0.1689296
 14  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA Hispanic pop 2 0.14001,999
 15  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.13704,335
 16  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.125028,927
 17  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.12362,492
 18  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.118428,927
 19  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.11365,849
 20  A*02:06-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*05:01  Russia Karelia 0.10751,075
 21  A*24:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Italy minority 0.08601,159
 22  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Italy minority 0.08601,159
 23  A*68:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.082023,595
 24  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.07312,492
 25  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Russia Karelia 0.07121,075
 26  A*33:03-B*51:01-C*15:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 27  A*29:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.06841,463
 28  A*68:01:02:02-B*51:01:01-C*15:02:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.06621,510
 29  A*01:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.04975,849
 30  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.04945,829
 31  A*11:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.049111,446
 32  A*25:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA Hispanic pop 2 0.04701,999
 33  A*29:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA Hispanic pop 2 0.04701,999
 34  A*11:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA Asian pop 2 0.04401,772
 35  A*31:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA African American pop 4 0.04402,411
 36  A*03:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.04245,849
 37  A*11:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.04195,829
 38  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.04184,204
 39  A*03:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India East UCBB 0.04162,403
 40  A*24:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India East UCBB 0.04162,403
 41  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.040711,446
 42  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.039511,446
 43  A*24:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.03815,829
 44  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03611,510
 45  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India East UCBB 0.03562,403
 46  A*02:11-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.03482,492
 47  A*31:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.03421,463
 48  A*01:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.03404,856
 49  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 50  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 51  A*68:01:02:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 52  A*31:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.03285,849
 53  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.032223,595
 54  A*01:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.024711,446
 55  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.02463,456,066
 56  A*31:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.02384,204
 57  A*11:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.02365,849
 58  A*24:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.02285,849
 59  A*24:02-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA Asian pop 2 0.02201,772
 60  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.02104,856
 61  A*03:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India East UCBB 0.02082,403
 62  A*01:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.02012,492
 63  A*32:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.019711,446
 64  A*68:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.01523,456,066
 65  A*03:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.014211,446
 66  A*26:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.01374,204
 67  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.01293,456,066
 68  A*32:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.01264,204
 69  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.01194,204
 70  A*11:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.01194,204
 71  A*02:03-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.010411,446
 72  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.01035,829
 73  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.010223,595
 74  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.01023,456,066
 75  A*26:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.00945,849
 76  A*02:06-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.00855,849
 77  A*23:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.00855,849
 78  A*68:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.008423,595
 79  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.007623,595
 80  A*11:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.007323,595
 81  A*33:03-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.006711,446
 82  A*26:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.004411,446
 83  A*03:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.003123,595
 84  A*02:06:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 85  A*02:17:02-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 86  A*68:02:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 87  A*02:06-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.002111,446

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).




   

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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