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  B*39:01-DRB1*04:04  Taiwan Ami 5.200098
 2  A*02:01-B*39:01-DRB1*04:04-DQB1*03:02  USA South Dakota Lakota Sioux 5.1000302
 3  A*24:02-B*39:01-C*07:02-DRB1*04:04  Russia Bering Island Aleuts 3.8462104
 4  A*24:02-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*02:01  Russia Karelia 1.27031,075
 5  A*68:01-B*39:01-C*03:04-DRB1*04:04-DQB1*04:02  Colombia North Chimila Amerindians 1.063847
 6  A*68:01-B*39:01-C*03:04-DRB1*04:04-DQB1*04:03  Colombia North Chimila Amerindians 1.063847
 7  A*68:16-B*39:01-C*03:04-DRB1*04:04-DQB1*04:02  Colombia North Chimila Amerindians 1.063847
 8  B*39:01-DRB1*04:04  Taiwan Puyuma 1.000050
 9  A*24:02:01-B*39:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 10  A*31:01-B*39:01-DRB1*04:04-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 11  A*68:01-B*39:01-DRB1*04:04-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 12  A*02:01-B*39:01-DRB1*04:04-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 13  A*24:02:01:01-B*39:01:01:03-C*07:02:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.52751,510
 14  A*24:02:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02  Russia Bashkortostan, Bashkirs 0.4167120
 15  A*24:02-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Russia Karelia 0.36131,075
 16  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQA1*03:01:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 17  A*24:02-B*39:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.3030330
 18  A*68:01-B*39:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.3030330
 19  A*03:01:01-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 20  A*30:01:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02  Russia Bashkortostan, Tatars 0.2604192
 21  A*02:06-B*39:01-C*03:04-DRB1*04:04-DQB1*04:02-DPB1*14:01  Panama 0.1900462
 22  A*02:01-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*02:01  Russia Karelia 0.16191,075
 23  A*36-B*39:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 24  A*11:01:01-B*39:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 25  A*26:01-B*39:01-C*12:03-DRB1*04:04-DQB1*05:02  Italy pop 5 0.1400975
 26  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 27  A*02:01-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Russia Karelia 0.13411,075
 28  A*24:02-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*04:02  Russia Karelia 0.12171,075
 29  A*02:01:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.11531,734
 30  A*24:02-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*03:01  Russia Karelia 0.10431,075
 31  A*02:01-B*39:01-DRB1*04:04  Israel Argentina Jews 0.08484,307
 32  A*31:08-B*39:01-DRB1*04:04  Israel USSR Jews 0.081145,681
 33  A*68:01-B*39:01-C*07:02-DRB1*04:04  Germany DKMS - Romania minority 0.08101,234
 34  A*68:01-B*39:01-C*12:03-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPB1*04:01  Sri Lanka Colombo 0.0700714
 35  A*03:01:01:01-B*39:01:01:03-C*07:02:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.06851,510
 36  A*31:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.06022,492
 37  A*31:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India South UCBB 0.059411,446
 38  A*68:01-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*04:02  Russia Karelia 0.05651,075
 39  B*39:01-DRB1*04:04  Italy pop 5 0.0500975
 40  A*03:01-B*39:01-C*12:03-DRB1*04:04  Germany DKMS - Croatia minority 0.04902,057
 41  A*02:01-B*39:01-C*07:02-DRB1*04:04  Germany DKMS - China minority 0.03901,282
 42  A*03:01-B*39:01-C*07:02-DRB1*04:04  Germany DKMS - France minority 0.03601,406
 43  A*11:01-B*39:01-C*07:02-DRB1*04:04  Germany DKMS - France minority 0.03601,406
 44  A*26:01-B*39:01-C*07:02-DRB1*04:04  Germany DKMS - Netherlands minority 0.03601,374
 45  A*01:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 46  A*24:02:01:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 47  A*02:01-B*39:01-C*07:02-DRB1*04:04  Hong Kong Chinese BMDR 0.03267,595
 48  A*02:01-B*39:01-C*12:03-DRB1*04:04  Germany DKMS - Greece minority 0.03201,894
 49  A*02:01-B*39:01-C*12:03-DRB1*04:04  Germany DKMS - Austria minority 0.02901,698
 50  A*24:02-B*39:01-C*12:03-DRB1*04:04  Germany DKMS - Croatia minority 0.02902,057
 51  A*32:01-B*39:01-C*12:03-DRB1*04:04  Germany DKMS - Austria minority 0.02901,698
 52  A*26:01-B*39:01-DRB1*04:04  Israel Argentina Jews 0.02464,307
 53  A*68:01-B*39:01-C*12:03-DRB1*04:04  Germany DKMS - Croatia minority 0.02402,057
 54  A*31:01-B*39:01-DRB1*04:04  Israel Argentina Jews 0.02314,307
 55  A*11:01-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02  USA Asian pop 2 0.02201,772
 56  A*24:02-B*39:01-DRB1*04:04  Israel USSR Jews 0.021245,681
 57  A*02:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.02104,856
 58  A*11:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India East UCBB 0.02082,403
 59  A*31:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India East UCBB 0.02082,403
 60  A*33:03-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India East UCBB 0.02082,403
 61  A*11:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India South UCBB 0.019311,446
 62  A*02:01-B*39:01-DRB1*04:04  Israel USSR Jews 0.018345,681
 63  A*24:02-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India South UCBB 0.017911,446
 64  A*03:02-B*39:01-DRB1*04:04  Israel Argentina Jews 0.01754,307
 65  A*24:02-B*39:01-C*07:02-DRB1*04:04  Poland DKMS 0.014420,653
 66  A*31:08-B*39:01-DRB1*04:04  Israel Argentina Jews 0.01304,307
 67  A*02:01-B*39:01-DRB1*04:04  Hong Kong Chinese cord blood registry 0.01283,892
 68  A*02:01:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.00925,266
 69  A*03:02-B*39:01-DRB1*04:04  Israel USSR Jews 0.008745,681
 70  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.007223,595
 71  A*68:02-B*39:01-DRB1*04:04  Israel USSR Jews 0.006145,681
 72  A*03:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India South UCBB 0.004411,446
 73  A*24:02-B*39:01-DRB1*04:04  Israel Arab pop 2 0.004112,301
 74  A*32:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India South UCBB 0.003511,446
 75  A*11:01-B*39:01-DRB1*04:04  Israel USSR Jews 0.003445,681
 76  A*26:01-B*39:01-C*12:03-DRB1*04:04  Poland DKMS 0.002820,653
 77  A*03:01-B*39:01-DRB1*04:04  Israel USSR Jews 0.002645,681
 78  A*24:04-B*39:01-DRB1*04:04  Israel USSR Jews 0.002545,681
 79  A*03:01-B*39:01-C*07:02-DRB1*04:04  Poland DKMS 0.002520,653
 80  A*01:01:01-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002323,595
 81  A*30:01-B*39:01-C*12:03-DRB1*04:04  Poland DKMS 0.002320,653
 82  A*68:01-B*39:01-DRB1*04:04  Israel USSR Jews 0.002245,681
 83  A*24:02:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002123,595
 84  A*24:02:01-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*06:03:01  Poland BMR 0.002123,595
 85  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*02:01:01  Poland BMR 0.002123,595
 86  A*02:01:01-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002023,595
 87  A*02:06-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02  India South UCBB 0.001111,446
 88  A*01:01-B*39:01-C*12:04-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.00075302,492
 89  A*24:07-B*39:01-DRB1*04:04  Israel USSR Jews 0.000547045,681
 90  A*24:26-B*39:01-DRB1*04:04  Israel USSR Jews 0.000547045,681

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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