Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 90 (from 90) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*08:02:01-DQB1*04:02-DPB1*04:01  Mexico Chihuahua Tarahumara 7.400044
 2  A*24:02:01-B*48:01-C*08:01-DRB1*08:02:01-DQB1*04:02-DPB1*04:01  Mexico Chihuahua Tarahumara 3.400044
 3  A*02:01:01-B*40:02:01-C*02:02:02-DRB1*04:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Black 2.381073
 4  A*24:03:01-B*40:04:01-C*03:04:01-DRB1*13:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Black 2.381073
 5  A*01:01:01-B*42:01:01-C*12:03:01-DRB1*03:01:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*04:01:01  Brazil Rio de Janeiro Black 1.470668
 6  A*68:02-B*18:01-C*07:04-DRB1*08:04-DQB1*04:02-DPB1*04:01  Tanzania Maasai 1.2780336
 7  A*01:01:01-B*35:02:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 8  A*02:01:01-B*35:01:01-C*17:01:01-DRB1*03:02:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 9  A*30:02:01-B*35:01:01-C*17:01:01-DRB1*04:03:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 10  A*32:01:01-B*39:01:01-C*07:02:01-DRB1*08:01:01-DQA1*04:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 11  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01-DPB1*04:01:01  South African Black 0.3520142
 12  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*04:07:01-DQA1*04:01:01-DQB1*04:02-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 13  A*02:01:01-B*40:01:02-C*03:04:01-DRB1*08:01-DQA1*04:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 14  A*02:01:01-B*40:01:02-C*14:02:01-DRB1*08:01:01-DQA1*05:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 15  A*03:01:01-B*39:06:02-C*12:02:02-DRB1*15:02-DQA1*04:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 16  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*08:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 17  A*02:05:01-B*58:01:01-C*03:02:02-DRB1*08:04:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 18  A*33:01:01-B*39:06:02-C*08:02:01-DRB1*13:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 19  A*68:01:01-B*35:08:01-C*04:01:01-DRB1*04:04:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 20  A*01:01-B*37:01-C*06:02-DRB1*04:04-DQA1*03:01-DQB1*04:02-DPB1*04:01  South Africa Worcester 0.3000159
 21  A*23:01-B*58:02-C*07:01-DRB1*07:01-DQA1*03:01-DQB1*04:02-DPB1*04:01  South Africa Worcester 0.3000159
 22  A*24:02-B*15:35-C*07:02-DRB1*04:05-DQA1*01:01-DQB1*04:02-DPB1*04:01  USA San Diego 0.2600496
 23  A*25:01-B*56:01-C*01:02-DRB1*08:01-DQA1*04:01-DQB1*04:02-DPB1*04:01  USA San Diego 0.2600496
 24  A*31:01-B*15:01-C*01:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*04:01  USA San Diego 0.2600496
 25  A*33:01-B*15:03-C*02:10-DRB1*04:04-DQA1*03:01-DQB1*04:02-DPB1*04:01  USA San Diego 0.2600496
 26  A*02:06-B*40:02-C*15:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:01  Mexico Chiapas Lacandon Mayans 0.2294218
 27  A*29:02-B*44:03-C*16:01-DRB1*08:01-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:01  Mexico Chiapas Lacandon Mayans 0.2294218
 28  A*68:03-B*35:01-C*07:02-DRB1*08:01-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:01  Mexico Chiapas Lacandon Mayans 0.2294218
 29  A*68:03-B*39:05-C*07:02-DRB1*08:01-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:01  Mexico Chiapas Lacandon Mayans 0.2294218
 30  A*23:01-B*44:03-C*04:01-DRB1*04:05-DQA1*03:01-DQB1*04:02-DPB1*04:01  Nicaragua Managua 0.2165339
 31  A*24:02-B*38:01-C*12:03-DRB1*04:02-DQA1*04:01-DQB1*04:02-DPB1*04:01  Nicaragua Managua 0.2165339
 32  A*24:02-B*39:11-C*08:03-DRB1*16:02-DQA1*03:01-DQB1*04:02-DPB1*04:01  Nicaragua Managua 0.2165339
 33  A*26:01-B*07:02-C*07:02-DRB1*08:01-DQA1*04:01-DQB1*04:02-DPB1*04:01  Nicaragua Managua 0.2165339
 34  A*03:01:01-B*50:01:01-C*06:02:01-DRB1*15:01:01-DQB1*04:02:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 35  A*31:01:02-B*15:01:01-C*01:02:01-DRB1*08:02:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 36  A*32:01:01-B*15:01:01-C*07:01:01-DRB1*01:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 37  A*23:01-B*14:03-C*01:02-DRB1*03:02-DQB1*04:02-DPB1*04:01  Panama 0.1900462
 38  A*23:01-B*39:08-C*02:10-DRB1*04:01-DQB1*04:02-DPB1*04:01  Panama 0.1900462
 39  A*24:02-B*49:01-C*07:01-DRB1*08:02-DQB1*04:02-DPB1*04:01  Panama 0.1900462
 40  A*33:01-B*35:01-C*04:01-DRB1*13:02-DQB1*04:02-DPB1*04:01  Panama 0.1900462
 41  A*33:01-B*51:02-C*15:02-DRB1*08:02-DQB1*04:02-DPB1*04:01  Panama 0.1900462
 42  A*03:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.16621,075
 43  DQB1*04:02-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 0.1600496
 44  A*68:02-B*45:01-C*08:04-DRB1*13:02-DQB1*04:02-DPB1*04:01  Tanzania Maasai 0.1597336
 45  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.15911,075
 46  A*03:01:01-B*50:01:01-C*06:02:01-DRB1*04:06:01-DQB1*04:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.155728,927
 47  A*02:01-B*40:01-C*03:04-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.14431,075
 48  A*02:01-B*35:03-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*04:01  Sri Lanka Colombo 0.1401714
 49  A*32:01-B*39:01-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.12441,075
 50  A*03:01-B*39:06-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.10801,075
 51  DRB1*08:01:01-DQB1*04:02-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 0.1010496
 52  A*02:01-B*40:01-C*03:04-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.10033,456,066
 53  DRB1*08:04-DQB1*04:02-DPB1*04:01  Gambia pop 3 0.0726939
 54  DRB1*13:04-DQB1*04:02-DPB1*04:01  Gambia pop 3 0.0726939
 55  A*02:16-B*08:01-C*07:02-DRB1*04:10-DQA1*01:01-DQB1*04:02-DPB1*04:01  Sri Lanka Colombo 0.0700714
 56  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.06303,456,066
 57  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05821,075
 58  A*11:01-B*39:06-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05661,075
 59  A*02:01-B*39:01-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05651,075
 60  A*02:01-B*51:01-C*14:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05651,075
 61  A*30:01-B*44:05-C*02:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05651,075
 62  A*26:01-B*15:34-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05651,075
 63  A*25:01-B*18:01-C*12:03-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05651,075
 64  A*02:01-B*39:01-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.04933,456,066
 65  A*02:01-B*51:01-C*14:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.04833,456,066
 66  DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:01  Hong Kong Chinese HKBMDR. DQ and DP 0.04371,064
 67  A*02:01-B*44:02-C*05:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.04073,456,066
 68  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.04053,456,066
 69  A*26:02-B*51:01-C*15:02-DRB1*04:10-DQA1*03:03-DQB1*04:02-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 70  A*26:03-B*35:01-C*03:03-DRB1*04:10-DQA1*03:03-DQB1*04:02-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 71  A*31:01-B*35:01-C*03:03-DRB1*04:10-DQA1*03:03-DQB1*04:02-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 72  A*24:02-B*39:06-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.02963,456,066
 73  A*02:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.02853,456,066
 74  A*01:01-B*08:01-C*07:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.02563,456,066
 75  A*26:01-B*56:01-C*01:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.02133,456,066
 76  A*24:02-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01863,456,066
 77  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01773,456,066
 78  A*02:01-B*27:05-C*01:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01763,456,066
 79  A*01:01-B*39:06-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01733,456,066
 80  A*02:01-B*27:05-C*02:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01683,456,066
 81  A*68:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01613,456,066
 82  A*03:01-B*40:01-C*03:04-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01603,456,066
 83  A*02:01-B*39:06-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01423,456,066
 84  A*24:02-B*37:01-C*06:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01413,456,066
 85  A*02:01-B*40:02-C*02:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01163,456,066
 86  A*02:01-B*56:01-C*01:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01143,456,066
 87  A*29:02-B*58:01-C*07:01-DRB1*08:04-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01083,456,066
 88  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01063,456,066
 89  A*24:02-B*40:01-C*03:04-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01053,456,066
 90  A*01:01-B*57:01-C*06:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01023,456,066

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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