Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

Population:  Country:  Source of dataset : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 401 to 500 (from 6,869) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 69  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 401  A*02:01-B*27:02-C*02:02-DRB1*16:01-DQB1*05:02  Poland 1.0000200
 402  A*02:01-B*51:01-C*15:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Brazil Puyanawa 1.0000150
 403  A*02-B*35-DRB1*16-DQB1*03:01  Mexico Baja Californa, Mexicali 1.0000100
 404  A*02-B*39-DRB1*16-DQB1*03:01  Mexico Quintana Roo Rural 1.000050
 405  A*02-B*44-DRB1*16  Russia Moscow Pop 2 1.00002,000
 406  A*11:01:01-B*35:02-DRB1*16:01:01  Portugal South 1.000049
 407  A*11:01:01-B*39:06:02-DRB1*16:01:01  Portugal Center 1.000050
 408  A*24:02:01-B*35:03-DRB1*16:01:01  Portugal Center 1.000050
 409  A*24-B*35-DRB1*16-DQB1*03:01  Mexico Quintana Roo Rural 1.000050
 410  A*24-B*39-DRB1*16-DQB1*03:01  Mexico Baja California Rural 1.000050
 411  A*26-B*46-DRB1*16  Philippines National Capital Region 1.000051
 412  A*31-B*15:01-DRB1*16-DQB1*03:01  Mexico Baja California Rural 1.000050
 413  A*32-B*40-C*02-DRB1*16-DQB1*05  Albania 1.0000160
 414  A*33:01-B*07:02:01-DRB1*16:02:02  Portugal Center 1.000050
 415  A*66:01-B*41:02-DRB1*16:01:01  Portugal South 1.000049
 416  B*15:21-DRB1*16:02:01  Philippines Ivatan 1.000050
 417  B*38:02-DRB1*16:02:01  Taiwan Puyuma 1.000050
 418  B*38:02-DRB1*16:02:01  Philippines Ivatan 1.000050
 419  DRB1*16:01-DQB1*05:02  Tunisia Gabes Arab 1.000096
 420  DRB1*16:02-DQA1*01:02-DQB1*05:02  Russia Northwest Slavic 1.0000200
 421  DRB1*16:02-DQB1*05:02  Vietnam Hanoi Kinh 1.0000103
 422  DRB1*16-DRB5*02-DQA1*01-DQB1*05-DPB1*04  USA San Francisco Caucasian 1.0000220
 423  A*02-B*15-DRB1*16  Brazil Para Cord Blood Unit 0.9988841
 424  A*02-B*48-DRB1*16-DQB1*03:01  Mexico Oaxaca, Oaxaca city 0.9934151
 425  A*24-B*39-DRB1*16-DQB1*03:01  Mexico Oaxaca, Oaxaca city 0.9934151
 426  A*24:02:01-B*13:01:01-C*03:04:01-DRB1*16:02:01-DQB1*05:02:01  Vietnam Kinh 0.9900101
 427  A*24-B*39-DRB1*16-DQB1*03:01  Mexico Mexico City Metropolitan Area Rural 0.9868150
 428  A*02-B*39-DRB1*16-DQB1*03:01  Mexico Sinaloa, Culiacán 0.9709103
 429  A*32-B*51-DRB1*16-DQB1*05  Mexico Sinaloa, Culiacán 0.9709103
 430  A*24-B*35-DRB1*16-DQB1*03:01  Mexico Durango, Durango city 0.9677153
 431  A*03:01-B*39:01-C*12:03-DRB1*16:01-DQB1*05:02  Colombia North Wiwa El Encanto 0.961552
 432  A*24-B*40:02-DRB1*16-DQB1*03:01  Mexico Mexico City South 0.961552
 433  A*31-B*39-DRB1*16-DQB1*03:01  Mexico Mexico City South 0.961552
 434  A*01:01-B*50:01-C*04:01-DRB1*16:02-DQA1*01:02-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 435  A*02:01-B*18:01-C*07:02-DRB1*16:02-DQA1*01:02-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 436  A*03:01-B*27:04-C*04:01-DRB1*16:01-DQA1*03:01-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 437  A*03:01-B*55:01-C*14:02-DRB1*16:02-DQA1*01:02-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 438  A*24:02-B*40:06-C*15:02-DRB1*16:02-DQA1*01:02-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 439  A*26:01-B*39:01-C*12:03-DRB1*16:01-DQA1*01:02-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 440  A*26:01-B*51:01-C*16:02-DRB1*16:01-DQA1*01:02-DQB1*05:02  United Arab Emirates Abu Dhabi 0.960052
 441  A*33:01-B*35:01-C*04:01-DRB1*16:01-DQA1*01:01-DQB1*05:01  United Arab Emirates Abu Dhabi 0.960052
 442  A*33:03-B*58:01-C*07:02-DRB1*16:02-DQA1*01:03-DQB1*06:01  United Arab Emirates Abu Dhabi 0.960052
 443  A*66:01-B*40:06-C*03:02-DRB1*16:02-DQA1*01:02-DQB1*06:02  United Arab Emirates Abu Dhabi 0.960052
 444  A*02-B*39-DRB1*16-DQB1*03:01  Mexico Puebla Rural 0.9592833
 445  A*02:01:01-B*27:02:01-C*02:02:02-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.959023,595
 446  A*24-B*48-DRB1*16-DQB1*03:01  Mexico Zacatecas, Fresnillo 0.9524103
 447  DRB1*16:01-DQA1*01:02-DQB1*05:02  USA European American 0.95001,899
 448  A*02-B*35-DRB1*16-DQB1*03:01  Mexico Chiapas, Tuxtla Gutierrez 0.943452
 449  A*02-B*40:02-DRB1*16-DQB1*03:01  Mexico Chiapas, Tuxtla Gutierrez 0.943452
 450  A*02-B*15-DRB1*16:04-DQB1*03:01  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 451  A*68-B*51-DRB1*16:02-DQB1*03:01  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 452  A*02:01-B*27:02-C*02:02-DRB1*16:01  Poland DKMS 0.933120,653
 453  A*02-B*13-C*03-DRB1*16  Myanmar Shan 0.926054
 454  A*24-B*38-C*07-DRB1*16  Myanmar Shan 0.926054
 455  A*24-B*51-DRB1*16-DQB1*03:01  Mexico Chihuahua, Ciudad Juarez 0.9259106
 456  DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.9220833
 457  A*01:01-B*52:01-DRB1*16:01  Israel Kavkazi Jews 0.90802,840
 458  A*02:03-B*38:02-C*07:02-DRB1*16:02-DRB5*01:01-DQB1*05:02  USA NMDP Chinese 0.902599,672
 459  A*01-B*38-C*12-DRB1*16  Iran pop 4 0.9000855
 460  A*02:01-B*27:02-C*02:02-DRB1*16:01  Germany DKMS - Bosnia and Herzegovina minority 0.89601,028
 461  A*02-B*18-DRB1*16-DQB1*05  Mexico Veracruz, Coatzacoalcos 0.892955
 462  A*02-B*39-DRB1*16-DQB1*03:03  Mexico Veracruz, Cordoba 0.892956
 463  A*24-B*39-DRB1*16-DQB1*03:01  Mexico Veracruz, Coatzacoalcos 0.892955
 464  A*24-B*51-DRB1*16-DQB1*03:01  Mexico Veracruz, Coatzacoalcos 0.892955
 465  A*29-B*39-DRB1*16-DQB1*03:01  Mexico Veracruz, Coatzacoalcos 0.892955
 466  A*31-B*35-DRB1*16-DQB1*03:01  Mexico Jalisco, Zapopan 0.8929168
 467  A*69-B*55-DRB1*16-DQB1*03:01  Mexico Veracruz, Cordoba 0.892956
 468  A*02-B*18-DRB1*16-DQA1*01:02-DQB1*05:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.8900112
 469  DRB1*16:01-DQB1*05:02  USA Hispanic pop 2 0.88101,999
 470  A*01-DRB1*16  Macedonia 0.8741286
 471  A*02-B*27-C*02-DRB1*16  Macedonia 0.8741286
 472  A*02-B*27-DRB1*16  Macedonia 0.8741286
 473  A*02-B*44-DRB1*16  Macedonia 0.8741286
 474  B*40-DRB1*16  Macedonia 0.8741286
 475  A*24-B*51-DRB1*16-DQB1*03:01  Mexico Veracruz, Veracruz city 0.8721171
 476  A*24:02-B*35:12-C*04:01-DRB1*16:02-DQB1*03:01  Colombia Bogotá Cord Blood 0.86971,463
 477  A*02-B*35-DRB1*16-DQB1*03:01  Mexico Mexico City North 0.8632751
 478  A*24:02-B*35:14-C*04:01-DRB1*16:02-DQB1*03:01  Mexico Mexico City Mestizo pop 2 0.8600234
 479  B*35:14-C*04:01-DRB1*16:02-DQB1*03:01  Mexico Mexico City Mestizo pop 2 0.8600234
 480  B*40:02-C*03:04-DRB1*16:02-DQB1*03:01  Mexico Mexico City Mestizo pop 2 0.8600234
 481  A*02-B*39-DRB1*16-DQB1*03:01  Mexico Tlaxcala Rural 0.8434830
 482  DRB1*16:02-DQB1*05:02  Georgia Caucasus Tbilisi 0.8403119
 483  A*02:01-B*27:02-C*02:02-DRB1*16:01  Germany DKMS - Croatia minority 0.83402,057
 484  A*01:01-B*18:01-DRB1*16:01-DQB1*05:01  Iran Saqqez-Baneh Kurds 0.833360
 485  A*02:01:01:01-B*44:05:01-C*02:02:02-DRB1*16:01:01-DQB1*05:02  Russia Bashkortostan, Bashkirs 0.8333120
 486  A*02:01-B*49:01-DRB1*16:01-DQB1*06:01  Iran Saqqez-Baneh Kurds 0.833360
 487  A*02:50-B*13:01-DRB1*16:01-DQB1*06:01  Iran Saqqez-Baneh Kurds 0.833360
 488  A*02:50-B*40:01-DRB1*16:01-DQB1*03:02  Iran Saqqez-Baneh Kurds 0.833360
 489  A*24-B*35-DRB1*16-DQB1*03:01  Mexico Veracruz, Orizaba 0.833360
 490  A*26:01-B*08:01-DRB1*16:01-DQB1*02:02  Iran Saqqez-Baneh Kurds 0.833360
 491  A*02-B*39-DRB1*16-DQB1*03:01  Mexico Veracruz Rural 0.8318539
 492  A*24-B*39-DRB1*16-DQB1*03:01  Mexico Veracruz Rural 0.8318539
 493  A*68-B*15:01-DRB1*16-DQB1*03:01  Mexico Tlaxcala, Tlaxcala city 0.8287181
 494  A*31-B*39-DRB1*16-DQB1*03:01  Mexico Chiapas Rural 0.8264121
 495  A*02:01-B*44:02-C*07:04-DRB1*16:01  Germany DKMS - Bosnia and Herzegovina minority 0.82601,028
 496  A*31-B*35-DRB1*16-DQB1*03:01  Mexico Oaxaca Rural 0.8214485
 497  A*02-B*40:02-DRB1*16-DQB1*03:01  Mexico Colima, Colima city 0.819761
 498  A*02-B*40:05-DRB1*16-DQB1*03:01  Mexico Colima, Colima city 0.819761
 499  A*68-B*35-DRB1*16-DQB1*03:01  Mexico Colima, Colima city 0.819761
 500  A*02:01-B*27:02-C*07:02-DRB1*16:01-DQA1*01:02-DQB1*05:02  Kosovo 0.8060124

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 401 to 500 (from 6,869) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 69  


   

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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