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 80 (from 80) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*66:01-B*41:01-C*17:01-DRB1*07:01  Brazil Vale do Ribeira Quilombos 1.3889144
 2  A*30:04:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02:01-DPB1*665:01  South African Black 0.7040142
 3  A*01:01:01-B*41:01-C*17:01:01-DRB1*07:01:01-DQB1*03:03:02-DPB1*04:02:01  Saudi Arabia pop 6 (G) 0.643328,927
 4  A*02:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQA1*02:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 5  A*23:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 0.3497143
 6  B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 0.3497143
 7  A*68:02-B*41:01-C*17:01-DRB1*07:01-DQA1*03:01-DQB1*02:02-DPB1*03:01  South Africa Worcester 0.3000159
 8  A*68:27-B*41:01-C*17:01-DRB1*07:01-DQA1*04:01-DQB1*02:02-DPB1*04:01  South Africa Worcester 0.3000159
 9  A*01:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Caucasian 0.1946521
 10  A*31:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02-DPB1*02:01  Panama 0.1900462
 11  A*23:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  India UCBB_Central Indian HLA 0.17844,204
 12  A*01:01-B*41:01-C*17:01-DRB1*07:01-DQB1*03:03  Germany DKMS - Turkey minority 0.15404,856
 13  A*24:02:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02:01  India Kerala Malayalam speaking 0.1400356
 14  A*32:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  Italy pop 5 0.1400975
 15  A*02:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 0.12901,159
 16  A*02:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Greece minority 0.11601,894
 17  A*01:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Netherlands minority 0.10901,374
 18  A*02:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  USA Hispanic pop 2 0.09401,999
 19  A*69:01-B*41:01-C*17:01-DRB1*07:01-DQB1*03:03  USA Hispanic pop 2 0.09401,999
 20  A*02:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Spain minority 0.09001,107
 21  A*23:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Austria minority 0.08801,698
 22  A*02:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Portugal minority 0.08501,176
 23  A*01:01-B*41:01-C*17:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  Sri Lanka Colombo 0.0700714
 24  A*23:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.06841,463
 25  A*23:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.06621,510
 26  A*02:01-B*41:01-C*17:01-DRB1*07:01  Poland DKMS 0.056520,653
 27  A*31:01-B*41:01-C*17:01-DRB1*07:01-DQB1*03:03-DPB1*04:02  Russia Karelia 0.05651,075
 28  A*02:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.053323,595
 29  A*24:07-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Malay 0.0526951
 30  A*02:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Bosnia and Herzegovina minority 0.04901,028
 31  A*03:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - United Kingdom minority 0.04801,043
 32  A*68:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - United Kingdom minority 0.04801,043
 33  A*23:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  USA Hispanic pop 2 0.04701,999
 34  A*02:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Netherlands minority 0.04301,374
 35  A*30:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 36  A*30:04-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 37  A*01:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.04104,856
 38  A*23:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - China minority 0.03901,282
 39  A*33:03-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - China minority 0.03901,282
 40  A*01:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - France minority 0.03601,406
 41  A*11:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Netherlands minority 0.03601,374
 42  A*23:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - France minority 0.03601,406
 43  A*02:22-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 44  A*24:02-B*41:01-C*17:01-DRB1*07:01-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 45  A*69:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 46  A*02:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 47  A*23:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 48  A*03:01:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 49  A*24:02:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 50  A*24:02:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 51  A*01:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Greece minority 0.02601,894
 52  A*23:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Greece minority 0.02601,894
 53  A*02:01-B*41:01-C*17:01-DRB1*07:01  Germany DKMS - Croatia minority 0.02402,057
 54  A*23:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02104,856
 55  A*23:01-B*41:01-C*17:01-DRB1*07:01  Poland DKMS 0.020920,653
 56  A*02:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.02012,492
 57  A*29:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.02012,492
 58  A*02:02-B*41:01-C*17:01-DRB1*07:01  Poland DKMS 0.019320,653
 59  A*23:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.014723,595
 60  A*02:01-B*41:01-C*17:01-DRB1*07:01-DQB1*03:03-DPB1*14:01  Germany DKMS - German donors 0.01303,456,066
 61  A*02:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  India UCBB_Central Indian HLA 0.01194,204
 62  A*11:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  India UCBB_Central Indian HLA 0.01194,204
 63  A*32:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  India UCBB_Central Indian HLA 0.01194,204
 64  A*33:03-B*41:01-C*17:01-DRB1*07:01-DQB1*02:02  India UCBB_Central Indian HLA 0.01194,204
 65  A*24:02-B*41:01-C*17:01-DRB1*07:01-DQB1*03:03  Germany DKMS - Turkey minority 0.01004,856
 66  A*33:01-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 67  A*03:01-B*41:01-C*17:01-DRB1*07:01  Poland DKMS 0.009520,653
 68  A*24:02-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.00572,492
 69  A*24:03-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.00572,492
 70  A*24:07-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.00572,492
 71  A*24:10-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.00572,492
 72  A*24:17-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.00572,492
 73  A*24:32-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.00572,492
 74  A*24:55-B*41:01-C*17:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.00572,492
 75  A*02:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.005223,595
 76  A*24:02-B*41:01-C*17:01-DRB1*07:01  Poland DKMS 0.003620,653
 77  A*25:01-B*41:01-C*17:01-DRB1*07:01  Poland DKMS 0.002420,653
 78  A*01:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 79  A*26:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 80  A*68:01:01-B*41:01:01-C*17:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.001823,595

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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