Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 95 (from 95) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DQA1*01:02-DQB1*06:05:01  Israel Ethiopian Jews 9.5000122
 2  DRB1*13:02-DQB1*06:05:01  Israel Ethiopian Jews 9.5000122
 3  DRB1*13:02-DQA1*01:02-DQB1*06:05  Ethiopia Oromo 7.800083
 4  DRB1*13:02-DQA1*01:02-DQB1*06:05:01/06:09  Equatorial Guinea Bioko Island Bubi 7.5000100
 5  DRB1*13:02-DQA1*01:02-DQB1*06:05  Ethiopia Amhara 6.600098
 6  DRB1*13:02-DQA1*01:02-DQB1*06:05/06:09  Russia Tuva Todja 4.600022
 7  DRB1*13:02-DQA1*01:02-DQB1*06:05/06:09  Russia Siberia Kushun Buryat 4.000025
 8  DRB1*13:01-DQA1*01:03-DQB1*06:05:01/06:09  Equatorial Guinea Bioko Island Bubi 3.8000100
 9  DRB1*13:02-DQA1*01:02-DQB1*06:05  South Korea pop 1 3.7000324
 10  DQA1*01:02-DQB1*06:05:01  Israel Iranian Jews 3.0000101
 11  DRB1*13:02-DQB1*06:05:01  Israel Iranian Jews 3.0000101
 12  DRB1*13:02-DQA1*01:02-DQB1*06:05/06:09  Russia Siberia Khanty Mansi 2.900068
 13  DRB1*13:02-DQA1*01:02-DQB1*06:05  Morocco Souss Region 2.600098
 14  DRB1*13:01-DQA1*01:03-DQB1*06:05/06:09  Russia Tuva Todja 2.300022
 15  DRB1*13:02-DQA1*01:02-DQB1*06:05/06:09  Russia Tuva pop3 2.300044
 16  DRB1*13:02-DQA1*01:02-DQB1*06:05/06:09  Russia Siberia Irkutsk Tofalar 2.300043
 17  DRB1*13:02-DQB1*06:05-DPB1*02:01  South Korea pop 1 2.3000324
 18  DRB1*13:02-DQA1*01:02-DQB1*06:05-DPB1*02:01  South Korea pop 1 2.2000324
 19  DRB1*13:01-DQA1*01:03-DQB1*06:05/06:09  Russia Siberia Khanty Mansi 1.500068
 20  DRB1*13:02-DQA1*01:02-DQB1*06:05/06:09  Russia Siberia Ulchi 1.400073
 21  DQA1*01:02-DQB1*06:05:01  Israel Libyan Jews 1.3000119
 22  DQA1*01:02-DQB1*06:05:01  Israel Yemenite Jews 1.300076
 23  DRB1*13:01-DQA1*01:02-DQB1*06:05:01/06:09  Equatorial Guinea Bioko Island Bubi 1.3000100
 24  DRB1*13:02-DQB1*06:05:01  Israel Yemenite Jews 1.300076
 25  DRB1*13:02-DQB1*06:05:01  Israel Libyan Jews 1.3000119
 26  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Vietnam Hanoi Kinh pop 2 1.2000170
 27  DRB1*13:01-DQA1*01:02-DQB1*06:05/06:09  Russia Tuva pop3 1.100044
 28  DRB1*13:02-DQB1*06:05  Philippines 1.000034
 29  DRB1*13:01-DQB1*06:05-DMB*01:01  Ecuadorean Amerindians 0.666775
 30  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*07:01:01-DQB1*06:05:02  India Karnataka Kannada Speaking 0.5750174
 31  DRB1*13:02-DQB1*06:05  Cretan Islanders 0.4032124
 32  A*31:01:02-B*13:01:01-C*04:03:01-DRB1*13:02:01-DQB1*06:05:01  India Karnataka Kannada Speaking 0.2870174
 33  A*33:03:01-B*58:08:02-C*03:02:01-DRB1*15:01:01-DQB1*06:05:02  India Karnataka Kannada Speaking 0.2870174
 34  A*03:01-B*35:03-C*05:01-DRB1*07:01-DQA1*02:01-DQB1*06:05-DPB1*02:01  USA San Diego 0.2600496
 35  A*30:02-B*18:01-C*04:01-DRB1*14:01-DQA1*01:01-DQB1*06:05-DPB1*05:01  USA San Diego 0.2600496
 36  A*02:03-B*55:02-C*12:03-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Chinese 0.2577194
 37  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Chinese 0.2577194
 38  A*02:01-B*51:01-C*01:02-DRB1*04:04-DQA1*03:01-DQB1*06:05-DPB1*04:01  Nicaragua Managua 0.2165339
 39  A*68:03-B*35:43-C*02:02-DRB1*04:04-DQA1*03:01-DQB1*06:05-DPB1*04:02  Nicaragua Managua 0.2165339
 40  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Malay 0.2103951
 41  A*30:02-B*44:03-C*07:01-DRB1*13:02-DQB1*06:05-DPB1*02:01  Panama 0.1900462
 42  A*02:05-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Indian 0.1845271
 43  A*33:01-B*15:01-C*03:03-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Indian 0.1845271
 44  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*07:01:01-DQB1*06:05:02  India Kerala Malayalam speaking 0.1400356
 45  A*33:03:01-B*58:01:01-C*12:02:01-DRB1*15:01:01-DQB1*06:05:02  India Kerala Malayalam speaking 0.1400356
 46  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.09492,492
 47  A*02:01-B*15:02-C*03:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Malay 0.0526951
 48  A*02:03-B*18:01-C*12:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Malay 0.0526951
 49  A*11:01-B*18:02-C*07:04-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Malay 0.0526951
 50  A*24:07-B*40:10-C*03:04-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Malay 0.0526951
 51  A*33:01-B*18:01-C*03:02-DRB1*15:31-DQB1*06:05  Malaysia Peninsular Malay 0.0526951
 52  A*24:02-B*35:01-C*03:60-DRB1*15:01-DQA1*01:02-DQB1*06:05-DPA1*02:01-DPB1*01:01  United Arab Emirates Pop 1 0.0467570
 53  A*74:01-B*15:03-C*02:02-DRB1*13:02-DQB1*06:05  USA African American pop 4 0.04402,411
 54  DRB1*13:02-DQB1*06:05  USA Asian pop 2 0.04401,772
 55  DRB1*13:02-DQB1*06:05  USA African American pop 4 0.04302,411
 56  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.04012,492
 57  A*30:02-B*53:01-C*04:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.04012,492
 58  A*02:03-B*15:02-C*08:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.02012,492
 59  A*03:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.02012,492
 60  A*03:02-B*40:01-C*03:04-DRB1*13:01-DQB1*06:05  India Tamil Nadu 0.02012,492
 61  A*31:01-B*40:01-C*03:04-DRB1*13:02-DQB1*06:05  USA Asian pop 2 0.01101,772
 62  A*31:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  USA Asian pop 2 0.01101,772
 63  A*33:03-B*40:01-C*03:04-DRB1*13:02-DQB1*06:05  USA Asian pop 2 0.01101,772
 64  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  USA Asian pop 2 0.01101,772
 65  A*31:01-B*57:01-C*04:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.01002,492
 66  A*33:03-B*07:02-C*07:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.01002,492
 67  A*33:03-B*58:01-C*03:02-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.01002,492
 68  A*68:01-B*58:01-C*03:02-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.01002,492
 69  A*11:01-B*39:01-C*12:03-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00382,492
 70  A*02:11-B*55:01-C*01:02-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00212,492
 71  DRB1*13:02-DQA1*01:02-DQB1*06:05-DPA1*01:03-DPB1*04:02  Pakistan Mixed Punjabi 0.0013389
 72  DRB1*15:07-DQA1*01:02-DQB1*06:05-DPA1*01:03-DPB1*04:02  Pakistan Mixed Punjabi 0.0013389
 73  A*02:06-B*55:01-C*01:02-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00122,492
 74  A*24:02-B*55:01-C*01:02-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00112,492
 75  A*01:01-B*40:06-C*15:02-DRB1*16:01-DQB1*06:05  India Tamil Nadu 0.00083402,492
 76  A*01:01-B*40:06-C*15:02-DRB1*16:02-DQB1*06:05  India Tamil Nadu 0.00083402,492
 77  A*32:01-B*55:01-C*05:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00066302,492
 78  A*32:01-B*55:02-C*05:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00066302,492
 79  A*32:02-B*55:01-C*05:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00066302,492
 80  A*32:02-B*55:02-C*05:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00066302,492
 81  A*32:08-B*55:01-C*05:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00066302,492
 82  A*32:08-B*55:02-C*05:01-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00066302,492
 83  A*24:02-B*52:01-C*12:02-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00055702,492
 84  A*24:07-B*52:01-C*12:02-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00055702,492
 85  A*11:01-B*58:34-C*12:03-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00053202,492
 86  A*11:03-B*58:34-C*12:03-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00053202,492
 87  A*11:04-B*58:34-C*12:03-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00053202,492
 88  A*11:122-B*58:34-C*12:03-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00053202,492
 89  A*11:24-B*58:34-C*12:03-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00053202,492
 90  A*31:01-B*40:06-C*15:02-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00023602,492
 91  A*24:02-B*39:01-C*12:04-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00001742,492
 92  A*24:03-B*39:01-C*12:04-DRB1*14:01-DQB1*06:05  India Tamil Nadu 0.00001742,492
 93  A*68:01-B*07:02-C*07:02-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00000432,492
 94  A*33:03-B*15:01-C*03:03-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00000032,492
 95  A*33:03-B*15:05-C*03:03-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.00000032,492

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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