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 2,001 to 2,100 (from 5,554) records   Pages: 21 22 23 24 25 26 27 28 29 30 of 56  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 2,001  A*01:01-B*08:01-C*07:181-DRB1*13:02-DQB1*06:09-DPB1*04:01  Tanzania Maasai 0.1597336
 2,002  A*01:01-B*18:01-C*04:01-DRB1*01:02-DQB1*06:04-DPB1*04:01  Tanzania Maasai 0.1597336
 2,003  A*01:01-B*37:01-C*04:04-DRB1*01:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,004  A*01:01-B*58:01-C*03:02-DRB1*15:03-DQB1*06:02-DPB1*04:02  Tanzania Maasai 0.1597336
 2,005  A*01:03-B*41:01-C*07:01-DRB1*13:02-DQB1*02:02-DPB1*04:01  Tanzania Maasai 0.1597336
 2,006  A*01:09-B*41:01-C*17:30-DRB1*15:03-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,007  A*01:09-B*44:15-C*04:07-DRB1*01:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,008  A*01:09-B*57:02-C*07:76-DRB1*15:03-DQB1*06:02-DPB1*04:01  Tanzania Maasai 0.1597336
 2,009  A*02:01-B*07:02-C*04:01-DRB1*11:01-DQB1*03:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,010  A*02:01-B*07:02-C*07:01-DRB1*11:189-DQB1*06:09-DPB1*04:01  Tanzania Maasai 0.1597336
 2,011  A*02:01-B*14:02-C*03:04-DRB1*03:01-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,012  A*02:01-B*14:02-C*08:02-DRB1*13:01-DQB1*06:03-DPB1*04:02  Tanzania Maasai 0.1597336
 2,013  A*02:01-B*49:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,014  A*02:01-B*53:01-C*07:01-DRB1*03:01-DQB1*06:09-DPB1*04:02  Tanzania Maasai 0.1597336
 2,015  A*02:02-B*35:01-C*07:04-DRB1*11:01-DQB1*05:01-DPB1*04:02  Tanzania Maasai 0.1597336
 2,016  A*02:05-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:02  Tanzania Maasai 0.1597336
 2,017  A*02:05-B*58:02-C*06:02-DRB1*13:01-DQB1*06:02-DPB1*04:01  Tanzania Maasai 0.1597336
 2,018  A*02:14-B*15:03-C*02:10-DRB1*13:02-DQB1*06:09-DPB1*04:01  Tanzania Maasai 0.1597336
 2,019  A*03:01-B*15:03-C*18:01-DRB1*14:54-DQB1*06:02-DPB1*04:01  Tanzania Maasai 0.1597336
 2,020  A*03:01-B*51:01-C*16:02-DRB1*04:08-DQB1*03:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,021  A*03:01-B*53:01-C*04:39-DRB1*04:05-DQB1*03:02-DPB1*04:02  Tanzania Maasai 0.1597336
 2,022  A*03:01-B*53:01-C*07:18-DRB1*13:02-DQB1*06:04-DPB1*04:02  Tanzania Maasai 0.1597336
 2,023  A*23:01-B*41:01-C*17:01-DRB1*11:04-DQB1*03:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,024  A*24:02-B*13:03-C*06:27-DRB1*03:02-DQB1*06:02-DPB1*04:02  Tanzania Maasai 0.1597336
 2,025  A*24:02-B*18:01-C*07:01-DRB1*03:02-DQB1*06:03-DPB1*04:01  Tanzania Maasai 0.1597336
 2,026  A*24:02-B*18:01-C*07:91-DRB1*03:01-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,027  A*24:02-B*27:03-C*07:22-DRB1*03:01-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,028  A*26:01-B*58:02-C*04:01-DRB1*04:05-DQB1*06:03-DPB1*04:01  Tanzania Maasai 0.1597336
 2,029  A*26:30-B*35:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,030  A*26:30-B*45:01-C*06:02-DRB1*08:04-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,031  A*29:02-B*53:01-C*02:02-DRB1*11:02-DQB1*03:01-DPB1*04:02  Tanzania Maasai 0.1597336
 2,032  A*29:02-B*53:01-C*06:76-DRB1*03:01-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,033  A*29:02-B*81:01-C*17:01-DRB1*03:02-DQB1*04:02-DPB1*04:02  Tanzania Maasai 0.1597336
 2,034  A*29:15-B*27:03-C*02:02-DRB1*03:01-DQB1*02:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,035  A*30:01-B*15:10-C*03:04-DRB1*13:02-DQB1*06:04-DPB1*04:01  Tanzania Maasai 0.1597336
 2,036  A*30:02-B*53:01-C*06:02-DRB1*13:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,037  A*30:10-B*49:01-C*06:157-DRB1*13:02-DQB1*06:04-DPB1*04:02  Tanzania Maasai 0.1597336
 2,038  A*31:04-B*45:01-C*15:05-DRB1*13:02-DQB1*06:04-DPB1*04:01  Tanzania Maasai 0.1597336
 2,039  A*32:01-B*81:01-C*05:11-DRB1*12:01-DQB1*06:09-DPB1*04:02  Tanzania Maasai 0.1597336
 2,040  A*33:03-B*41:01-C*17:01-DRB1*03:01-DQB1*02:01-DPB1*04:02  Tanzania Maasai 0.1597336
 2,041  A*33:03-B*58:02-C*06:02-DRB1*13:01-DQB1*06:02-DPB1*04:02  Tanzania Maasai 0.1597336
 2,042  A*36:01-B*18:01-C*07:01-DRB1*01:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,043  A*36:01-B*58:01-C*07:01-DRB1*01:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,044  A*66:01-B*58:02-C*06:157-DRB1*07:01-DQB1*02:02-DPB1*04:01  Tanzania Maasai 0.1597336
 2,045  A*68:01-B*07:05-C*15:05-DRB1*10:01-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,046  A*68:02-B*15:10-C*03:03-DRB1*11:01-DQB1*03:19-DPB1*04:01  Tanzania Maasai 0.1597336
 2,047  A*68:02-B*15:17-C*07:01-DRB1*04:01-DQB1*06:03-DPB1*04:01  Tanzania Maasai 0.1597336
 2,048  A*68:02-B*18:01-C*02:15-DRB1*01:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,049  A*68:02-B*18:01-C*07:01-DRB1*13:02-DQB1*06:04-DPB1*04:01  Tanzania Maasai 0.1597336
 2,050  A*68:02-B*27:03-C*02:09-DRB1*01:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,051  A*68:02-B*45:01-C*08:04-DRB1*13:02-DQB1*04:02-DPB1*04:01  Tanzania Maasai 0.1597336
 2,052  A*74:01-B*15:03-C*02:10-DRB1*11:01-DQB1*03:19-DPB1*04:02  Tanzania Maasai 0.1597336
 2,053  A*74:01-B*44:03-C*07:01-DRB1*15:03-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,054  A*74:01-B*49:01-C*07:01-DRB1*11:04-DQB1*03:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,055  A*74:01-B*58:02-C*06:02-DRB1*13:01-DQB1*03:03-DPB1*04:01  Tanzania Maasai 0.1597336
 2,056  A*74:01-B*58:02-C*07:01-DRB1*01:02-DQB1*05:01-DPB1*04:01  Tanzania Maasai 0.1597336
 2,057  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.15943,456,066
 2,058  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.15911,075
 2,059  A*02:01-B*18:01-C*07:01-DRB1*11:04-DQB1*03:01-DPB1*04:02  Germany DKMS - German donors 0.15893,456,066
 2,060  A*02:01-B*40:01-C*03:04-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.15843,456,066
 2,061  DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*04:02  China Zhejiang Han pop 2 0.1580833
 2,062  A*03:01-B*35:01-C*04:01-DRB1*13:01-DQB1*06:03-DPB1*04:01  Russia Karelia 0.15781,075
 2,063  A*24:02-B*07:02-C*07:02-DRB1*04:01-DQB1*03:02-DPB1*04:01  Russia Karelia 0.15751,075
 2,064  A*03:01-B*07:02-C*07:02-DRB1*14:01-DQB1*05:03-DPB1*04:01  Russia Karelia 0.15741,075
 2,065  A*02:01:01-B*18:01:01-C*07:01:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.156828,927
 2,066  A*03:01:01-B*50:01:01-C*06:02:01-DRB1*04:06:01-DQB1*04:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.155728,927
 2,067  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.15563,456,066
 2,068  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.15361,075
 2,069  DRB1*14:01:01-DQB1*05:03-DPB1*04:02:01  China Inner Mongolia Autonomous Region Northeast 0.1520496
 2,070  A*24:02:01-B*52:01-C*12:02:01-DRB1*15:02:01-DQB1*06:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.151928,927
 2,071  A*11:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01-DPB1*04:01  Russia Karelia 0.15121,075
 2,072  DRB1*09:01:02-DQB1*03:03-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 0.1510496
 2,073  DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  China Zhejiang Han pop 2 0.1503833
 2,074  A*01-B*08-C*07-DRB1*15-DQB1*06-DPB1*04  Norway ethnic Norwegians 0.15004,510
 2,075  A*03-B*35-C*04-DRB1*04-DQB1*03-DPB1*04  Norway ethnic Norwegians 0.15004,510
 2,076  A*24-B*07-C*07-DRB1*04-DQB1*03-DPB1*04  Norway ethnic Norwegians 0.15004,510
 2,077  A*03:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.14853,456,066
 2,078  A*33:01-B*14:02-C*08:02-DRB1*01:02-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.14833,456,066
 2,079  A*02:01:01-B*40:01:01-C*03:04:01-DRB1*03:01:01-DQB1*05:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.148028,927
 2,080  A*02:11-B*40:06-C*15:02-DRB1*15:01-DQA1*01:03-DQB1*06:01-DPA1*01:03-DPB1*04:01  United Arab Emirates Pop 1 0.1476570
 2,081  A*03:01-B*08:01-C*07:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPA1*01:03-DPB1*04:01  United Arab Emirates Pop 1 0.1475570
 2,082  A*03:01-B*15:01-C*03:04-DRB1*04:01-DQB1*03:02-DPB1*04:01  Germany DKMS - German donors 0.14743,456,066
 2,083  A*32:01:01-B*50:01:01-C*04:01:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.146728,927
 2,084  DRB1*01:02-DQB1*05:01-DPB1*04:01  Gambia pop 3 0.1458939
 2,085  DRB1*09:01-DQB1*02:01-DPB1*04:02  Gambia pop 3 0.1451939
 2,086  DRB1*11:01-DQB1*03:01-DPB1*04:02  Gambia pop 3 0.1451939
 2,087  DRB1*08:02:01-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 0.1450496
 2,088  DRB1*08:03:02-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 0.1450496
 2,089  DQA1*01:03-DQB1*06:01-DPA1*01:03-DPB1*04:01  Hong Kong Chinese HKBMDR. DQ and DP 0.14481,064
 2,090  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.14473,456,066
 2,091  A*02:01-B*40:01-C*03:04-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.14431,075
 2,092  A*02:01-B*27:02-C*02:02-DRB1*16:01-DQB1*05:02-DPB1*04:02  Germany DKMS - German donors 0.14363,456,066
 2,093  DQA1*01:03-DQB1*06:01-DPA1*01:03-DPB1*04:02  Hong Kong Chinese HKBMDR. DQ and DP 0.14331,064
 2,094  DQB1*04:02-DPB1*04:02:01  China Inner Mongolia Autonomous Region Northeast 0.1430496
 2,095  DRB1*11:02-DQB1*03:01-DPB1*04:01  Gambia pop 3 0.1412939
 2,096  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPA1*01:03-DPB1*04:01  United Arab Emirates Pop 1 0.1402570
 2,097  A*01:01-B*15:17-C*07:01-DRB1*13:02-DQA1*01:02-DQB1*06:04-DPA1*01:03-DPB1*04:01  United Arab Emirates Pop 1 0.1402570
 2,098  A*01:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:01  United Arab Emirates Pop 1 0.1402570
 2,099  A*01:01-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPA1*01:03-DPB1*04:02  United Arab Emirates Pop 1 0.1402570
 2,100  A*02:01-B*35:01-C*04:01-DRB1*16:01-DQA1*01:02-DQB1*05:02-DPA1*01:03-DPB1*04:01  United Arab Emirates Pop 1 0.1402570

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 2,001 to 2,100 (from 5,554) records   Pages: 21 22 23 24 25 26 27 28 29 30 of 56  


   

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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