Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 71 (from 71) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*11:01-DQB1*06:02-DPB1*01:01  Congo Kinshasa Bantu 3.000090
 2  A*23:01:01-B*50:01:01-C*02:10:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Black 1.470668
 3  A*30:02:01-B*08:01:01-C*07:01:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Black 1.470668
 4  A*74:01:01-B*42:01:01-C*17:01:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Black 1.470668
 5  A*43:01-B*58:02:01-C*06:02:01-DRB1*15:03:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.7040142
 6  A*01:01:01-B*44:03:02-C*15:13:01-DRB1*04:02:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 7  A*23:01:01-B*42:01:01-C*17:01:01-DRB1*11:01:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 8  A*74:01:01-B*53:01:01-C*04:01:01-DRB1*15:02:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 9  A*02:01-B*42:01-C*17:01-DRB1*11:01-DQA1*01:02-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 10  A*02:02-B*58:02-C*16:01-DRB1*15:03-DQA1*01:01-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 11  A*29:02-B*35:01-C*04:01-DRB1*15:03-DQA1*05:01-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 12  A*30:01-B*07:02-C*07:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 13  A*30:01-B*58:01-C*03:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 14  A*30:02-B*14:02-C*08:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 15  A*30:02-B*45:01-C*06:11-DRB1*07:01-DQA1*02:01-DQB1*06:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 16  A*26:01-B*07:02-C*07:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*01:01  Nicaragua Managua 0.4329339
 17  A*01:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*02:01:02-DPB1*01:01:01  Russian Federation Vologda Region 0.4202119
 18  A*23:01-B*07:02-C*07:01-DRB1*15:03-DQB1*06:02-DPB1*01:01  Panama 0.3800462
 19  DRB1*08:06-DQB1*06:02-DPB1*01:01  Gambia pop 3 0.3775939
 20  A*02:01:01-B*15:03:01-C*08:02:01-DRB1*15:01:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 21  A*23:17-B*15:01:01-C*04:01:01-DRB1*15:03:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 22  A*30:01:01-B*08:01:01-C*07:01:01-DRB1*08:04:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 23  A*30:01:01-B*18:01:01-C*07:04:01-DRB1*11:01:02-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 24  A*30:02:01-B*45:01:01-C*16:01:01-DRB1*01:02:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 25  A*30:02:01-B*57:03:01-C*18:02-DRB1*15:03:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 26  A*30:04:01-B*39:10:01-C*15:05:02-DRB1*15:03:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 27  A*68:02:01-B*07:06:01-C*08:04:01-DRB1*11:01:02-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 28  A*68:02:01-B*15:220-C*07:02:01-DRB1*13:02:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 29  A*68:02:01-B*58:02:01-C*06:02:01-DRB1*08:04:01-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 30  A*02:01:01-B*07:02:01-C*12:03:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*06:02-DPA1*02:01-DPB1*01:01:01  Russia Belgorod region 0.3268153
 31  DRB1*15:03-DQB1*06:02-DPB1*01:01  Gambia pop 3 0.3127939
 32  A*23:01:01-B*39:06:02-C*05:01:01-DRB1*11:04:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 33  A*23:17:01-B*81:01:01-C*08:02:01-DRB1*11:01:02-DQB1*06:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 34  A*29:02:01-B*45:01:01-C*06:02:01-DRB1*15:01:01-DQB1*06:02:01-DPA1*02:01:08-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 35  A*01:01-B*07:02-C*07:02-DRB1*11:01-DQA1*05:01-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 36  A*03:01-B*58:01-C*07:02-DRB1*13:01-DQA1*02:01-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 37  A*03:01-B*58:02-C*06:02-DRB1*13:01-DQA1*01:03-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 38  A*23:01-B*13:03-C*12:03-DRB1*07:01-DQA1*01:02-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 39  A*23:01-B*27:05-C*02:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 40  A*26:01-B*41:01-C*17:01-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 41  A*29:01-B*08:01-C*02:02-DRB1*11:01-DQA1*01:02-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 42  A*30:01-B*42:02-C*17:01-DRB1*12:01-DQA1*01:01-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 43  A*30:02-B*18:01-C*07:01-DRB1*11:01-DQA1*03:01-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 44  A*34:02-B*15:03-C*03:04-DRB1*08:04-DQA1*01:02-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 45  A*43:01-B*44:03-C*07:01-DRB1*15:01-DQA1*05:01-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 46  A*74:01-B*15:03-C*02:10-DRB1*03:17-DQA1*01:02-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 47  A*74:01-B*15:03-C*02:10-DRB1*11:14-DQA1*01:02-DQB1*06:02-DPB1*01:01  South Africa Worcester 0.3000159
 48  A*36:01-B*53:01-C*16:01-DRB1*11:01-DQA1*02:01-DQB1*06:02-DPB1*01:01  USA San Diego 0.2600496
 49  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*01:01  Nicaragua Managua 0.2165339
 50  A*01:02-B*42:01:01-C*17:01:01-DRB1*11:01:02-DQB1*06:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 51  A*03:01:01-B*07:02:01-C*14:03:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*02:06-DPB1*01:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 52  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*13:02:01-DQB1*06:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 53  A*30:01:01-B*42:01:01-C*17:01:01-DRB1*03:02:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*01:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 54  A*01:01-B*07:02-C*04:01-DRB1*15:03-DQB1*06:02-DPB1*01:01  Panama 0.1900462
 55  A*01:01-B*40:02-C*02:02-DRB1*04:07-DQB1*06:02-DPB1*01:01  Panama 0.1900462
 56  A*33:01-B*35:01-C*03:02-DRB1*09:01-DQB1*06:02-DPB1*01:01  Panama 0.1900462
 57  A*34:02-B*15:17-C*05:01-DRB1*11:01-DQB1*06:02-DPB1*01:01  Panama 0.1900462
 58  A*36:01-B*45:01-C*16:01-DRB1*15:03-DQB1*06:02-DPB1*01:01  Panama 0.1900462
 59  A*01:09-B*44:15-C*04:07-DRB1*15:03-DQB1*06:02-DPB1*01:01  Tanzania Maasai 0.1597336
 60  A*30:01-B*15:10-C*04:01-DRB1*11:01-DQB1*06:02-DPB1*01:01  Tanzania Maasai 0.1597336
 61  A*30:09-B*53:01-C*04:01-DRB1*11:01-DQB1*06:02-DPB1*01:01  Tanzania Maasai 0.1597336
 62  A*36:01-B*81:01-C*04:01-DRB1*15:03-DQB1*06:02-DPB1*01:01  Tanzania Maasai 0.1597336
 63  A*66:01-B*58:02-C*06:02-DRB1*13:01-DQB1*06:02-DPB1*01:01  Tanzania Maasai 0.1597336
 64  A*68:02-B*07:05-C*07:05-DRB1*13:01-DQB1*06:02-DPB1*01:01  Tanzania Maasai 0.1597336
 65  A*68:02-B*15:10-C*03:04-DRB1*10:01-DQB1*06:02-DPB1*01:01  Tanzania Maasai 0.1597336
 66  A*31:01-B*51:01-C*14:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*01:01  Sri Lanka Colombo 0.1401714
 67  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*01:01  Russia Karelia 0.12451,075
 68  DQA1*01:02-DQB1*06:02-DPA1*02:01-DPB1*01:01  Hong Kong Chinese HKBMDR. DQ and DP 0.04541,064
 69  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*01:01  Germany DKMS - German donors 0.04543,456,066
 70  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*01:01  Germany DKMS - German donors 0.01853,456,066
 71  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*01:01  Germany DKMS - German donors 0.01163,456,066

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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