Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 801 to 900 (from 4,129) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 42  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 801  A*33:03-B*44:03-C*07:06-DRB1*13:01-DQB1*06:03  India Northeast UCBB 0.1689296
 802  A*26:01-B*38:01-C*12:03-DRB1*13:01-DQB1*06:03-DPB1*04:01  Russia Karelia 0.16891,075
 803  A*03:01:01:01-B*38:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.16841,510
 804  A*03:01-B*35:03-C*04:01-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.16832,492
 805  A*31:01-B*51:01-C*14:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.16755,849
 806  A*11:01-B*07:02-C*07:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Russia Karelia 0.16351,075
 807  A*26:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.16245,849
 808  A*11:01-B*35:03-C*04:01-DRB1*13:01-DQB1*06:03  India Central UCBB 0.16204,204
 809  A*02:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  Germany DKMS - Italy minority 0.16101,159
 810  DRB1*13:02-DQB1*06:03  Italy pop 5 0.1600975
 811  A*01:01-B*08:01-C*07:04-DRB1*13:02-DQB1*06:03-DPB1*02:01  Tanzania Maasai 0.1597336
 812  A*02:01-B*14:02-C*08:02-DRB1*13:01-DQB1*06:03-DPB1*04:02  Tanzania Maasai 0.1597336
 813  A*02:05-B*58:02-C*06:66-DRB1*13:01-DQB1*06:03-DPB1*133:01  Tanzania Maasai 0.1597336
 814  A*03:01-B*14:02-C*08:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Tanzania Maasai 0.1597336
 815  A*03:01-B*15:03-C*02:10-DRB1*01:02-DQB1*06:03-DPB1*17:01  Tanzania Maasai 0.1597336
 816  A*24:02-B*18:01-C*07:01-DRB1*03:02-DQB1*06:03-DPB1*04:01  Tanzania Maasai 0.1597336
 817  A*26:01-B*58:02-C*04:01-DRB1*04:05-DQB1*06:03-DPB1*04:01  Tanzania Maasai 0.1597336
 818  A*30:04-B*41:01-C*02:09-DRB1*13:01-DQB1*06:03-DPB1*131:01  Tanzania Maasai 0.1597336
 819  A*68:02-B*08:01-C*07:02-DRB1*13:02-DQB1*06:03-DPB1*02:01  Tanzania Maasai 0.1597336
 820  A*68:02-B*15:10-C*08:04-DRB1*13:01-DQB1*06:03-DPB1*133:01  Tanzania Maasai 0.1597336
 821  A*68:02-B*15:17-C*07:01-DRB1*04:01-DQB1*06:03-DPB1*04:01  Tanzania Maasai 0.1597336
 822  A*26:01:01-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*06:03:01  Poland BMR 0.159723,595
 823  A*26:01-B*38:01-C*12:03-DRB1*13:01-DQB1*06:03  India North UCBB 0.15935,849
 824  A*26:01-B*38:01-C*12:03-DRB1*13:01-DQB1*06:03  USA NMDP American Indian South or Central America 0.15925,926
 825  A*03:01-B*35:01-C*04:01-DRB1*13:01-DQB1*06:03-DPB1*04:01  Russia Karelia 0.15781,075
 826  A*24:02-B*18:01-C*12:03-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.15622,492
 827  A*03-B*07-DRB1*15:01-DQA1*01:02-DQB1*06:03  Brazil Paraná Caucasian 0.1560641
 828  A*25:01:01-B*15:01:01:01-C*03:03:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.15421,510
 829  DQB1*06:03-DPB1*14:01  China Inner Mongolia Autonomous Region Northeast 0.1530496
 830  A*01:01-B*55:01-C*01:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.15274,204
 831  A*02:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.15251,510
 832  A*11:01-B*35:03-C*04:01-DRB1*13:01-DQB1*06:03  India South UCBB 0.152511,446
 833  A*01:01-B*57:01-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 834  A*02:01-B*44:02-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 835  A*02:01-B*57:02-DRB1*15:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 836  A*03:01-B*07:02-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 837  A*03:01-B*35:01-DRB1*16:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 838  A*03:01-B*44:02-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 839  A*11:01-B*18:07-DRB1*15:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 840  A*24:02-B*39:01-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 841  A*24:02-B*40:02-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 842  A*25:01-B*44:02-DRB1*15:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 843  A*31:01-B*15:01-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 844  A*31:01-B*39:06-DRB1*13:02-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 845  A*32:01-B*15:01-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 846  A*36-B*15:01-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 847  A*68:01-B*39:01-DRB1*13:03-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 848  A*74:01-B*39:01-DRB1*11:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 849  A*24:02-B*35:01-C*04:01-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.15004,856
 850  A*03:01:01-B*38:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.147223,595
 851  A*68:01-B*35:01-C*04:01-DRB1*13:01-DQB1*06:03  India East UCBB 0.14492,403
 852  A*68:01-B*51:01-C*16:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.14215,849
 853  A*26:01-B*38:01-C*12:03-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.14131,463
 854  A*02:01-B*35:03-C*04:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  Sri Lanka Colombo 0.1401714
 855  A*03:01-B*35:03-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  Sri Lanka Colombo 0.1401714
 856  A*11:01-B*37:01-C*06:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  Sri Lanka Colombo 0.1401714
 857  A*11:01-B*37:01-C*06:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:01  Sri Lanka Colombo 0.1401714
 858  A*24:02-B*35:01-C*04:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*13:01  Sri Lanka Colombo 0.1401714
 859  A*24:02-B*40:06-C*04:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  Sri Lanka Colombo 0.1401714
 860  A*33:03-B*35:03-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:01  Sri Lanka Colombo 0.1401714
 861  A*01:01-B*18:01-C*05:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 862  A*01:01-B*35:02-C*04:01-DRB1*11:04-DQB1*06:03  USA Hispanic pop 2 0.14001,999
 863  A*01:01-B*37:01-C*06:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 864  A*01:01-B*44:02-C*07:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 865  A*01:01-B*55:01-C*07:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 866  A*01:01-B*58:01-C*03:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 867  A*02:01:01-B*18:01:01-C*03:03:01-DRB1*08:03:02-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 868  A*02:01:01-B*35:03:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 869  A*02:01-B*15:01-C*04:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 870  A*02:01-B*35:08-C*04:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 871  A*02:01-B*38:01-C*12:03-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 872  A*02:01-B*40:01-C*03:04-DRB1*11:01-DQB1*06:03  Italy pop 5 0.1400975
 873  A*02:01-B*44:02-C*07:01-DRB1*11:03-DQB1*06:03  Italy pop 5 0.1400975
 874  A*02:01-B*51:01-C*01:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 875  A*02:01-B*51:01-C*15:02-DRB1*13:01-DQB1*06:03  USA Hispanic pop 2 0.14001,999
 876  A*02:02-B*51:01-C*16:01-DRB1*15:01-DQB1*06:03  Italy pop 5 0.1400975
 877  A*02:06-B*40:02-C*02:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 878  A*02:17-B*44:02-C*01:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 879  A*03:01:01-B*13:01:01-C*04:03:01-DRB1*15:02:02-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 880  A*03:01:01-B*35:03:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 881  A*03:01:01-B*38:14-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 882  A*03:01-B*35:01-C*04:01-DRB1*13:01-DQB1*06:03  USA Hispanic pop 2 0.14001,999
 883  A*03:01-B*38:01-C*12:03-DRB1*13:01-DQB1*06:03  USA Hispanic pop 2 0.14001,999
 884  A*03:01-B*47:01-C*06:02-DRB1*11:01-DQB1*06:03  Italy pop 5 0.1400975
 885  A*03:01-B*51:01-C*04:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 886  A*03:01-B*51:01-C*05:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 887  A*03:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 888  A*11:01:01-B*52:01:01-C*12:02:01-DRB1*15:02:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 889  A*11:01:01-B*52:01:01-C*12:02:02-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 890  A*11:01:01-B*55:01:01-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 891  A*11:01:01-B*55:01:01-C*03:04:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 892  A*11:01-B*35:01-C*04:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 893  A*24:02:01-B*35:03:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 894  A*24:02:01-B*39:01:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 895  A*24:02:01-B*40:06:01-C*12:02:02-DRB1*12:02:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 896  A*24:02:01-B*44:03:02-C*07:01:01-DRB1*07:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 897  A*24:02:01-B*52:01:01-C*12:02:02-DRB1*09:01:02-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 898  A*24:02-B*18:01-C*15:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 899  A*24:02-B*35:03-C*04:01-DRB1*15:01-DQB1*06:03  Italy pop 5 0.1400975
 900  A*24:02-B*51:01-C*01:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975

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).


Displaying 801 to 900 (from 4,129) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 42  


   

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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