Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Sample Size:      Sample Year:     Loci Tested: 
Displaying 1,001 to 1,100 (from 7,008) records   Pages: 11 12 13 14 15 16 17 18 19 20 of 71  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1,001  A*33-B*52-DRB1*15  Brazil South Ribeirao Preto 0.3000184
 1,002  A*33-B*53-DRB1*11  Brazil South Ribeirao Preto 0.3000184
 1,003  A*33-B*14:02-DRB1*03:01-DQB1*02  Mexico Jalisco, Zapopan 0.2976168
 1,004  A*33-B*18-DRB1*07-DQB1*02  Mexico Jalisco, Zapopan 0.2976168
 1,005  A*33-B*27-DRB1*01-DQB1*05  Mexico Jalisco, Zapopan 0.2976168
 1,006  A*33-B*35-DRB1*03:01-DQB1*02  Mexico Jalisco, Zapopan 0.2976168
 1,007  A*33-B*44-DRB1*03:01-DQB1*02  Mexico Jalisco, Zapopan 0.2976168
 1,008  A*33-B*51-DRB1*11-DQB1*03:01  Mexico Jalisco, Zapopan 0.2976168
 1,009  A*33-B*58-DRB1*13-DQB1*06  Mexico Jalisco, Zapopan 0.2976168
 1,010  A*33:01-B*14:02-C*08:02-DRB1*03:01  Germany DKMS - Austria minority 0.29401,698
 1,011  A*33-B*14:02-DRB1*11-DQB1*03:01  Mexico Veracruz, Veracruz city 0.2907171
 1,012  A*33-B*44-DRB1*01-DQB1*05  Mexico Veracruz, Veracruz city 0.2907171
 1,013  A*33:01-B*14:02-C*08:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.2900975
 1,014  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.2900975
 1,015  A*33:01-B*55:01-DRB1*15:02  Israel Georgia Jews 0.28904,471
 1,016  A*33:03-B*58:01-C*03:02-DRB1*09:01  Germany DKMS - China minority 0.28801,282
 1,017  A*33:01:01-B*15:02:01-C*08:01:01-DRB1*12:02:01-DQB1*03:01:01  India Karnataka Kannada Speaking 0.2870174
 1,018  A*33:01:02-B*18:01:01-C*07:01:01-DRB1*03:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 0.2870174
 1,019  A*33:03:01-B*07:02:01-C*07:02:01-DRB1*14:04:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.2870174
 1,020  A*33:03:01-B*07:05:01-C*07:02:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 1,021  A*33:03:01-B*07:05:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  India Karnataka Kannada Speaking 0.2870174
 1,022  A*33:03:01-B*07:06-C*07:06-DRB1*04:08:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 1,023  A*33:03:01-B*15:02:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 0.2870174
 1,024  A*33:03:01-B*15:02:01-C*15:02:01-DRB1*15:02:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 1,025  A*33:03:01-B*15:18:01-C*07:04:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 1,026  A*33:03:01-B*35:01:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  India Karnataka Kannada Speaking 0.2870174
 1,027  A*33:03:01-B*35:03:01-C*04:01:01-DRB1*07:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 1,028  A*33:03:01-B*38:01:01-C*07:02:01-DRB1*04:03:01-DQB1*03:03:02  India Karnataka Kannada Speaking 0.2870174
 1,029  A*33:03:01-B*39:01:01-C*12:04:02-DRB1*07:01:01-DQB1*02:02:01  India Karnataka Kannada Speaking 0.2870174
 1,030  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*01:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 1,031  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*07:01:01-DQB1*06:01:01  India Karnataka Kannada Speaking 0.2870174
 1,032  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*11:01:01-DQB1*03:01:01  India Karnataka Kannada Speaking 0.2870174
 1,033  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*13:02:01-DQB1*02:01:07  India Karnataka Kannada Speaking 0.2870174
 1,034  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*15:02:01-DQB1*06:02:01  India Karnataka Kannada Speaking 0.2870174
 1,035  A*33:03:01-B*44:03:02-C*07:06-DRB1*07:01:01-DQB1*02:02:01  India Karnataka Kannada Speaking 0.2870174
 1,036  A*33:03:01-B*50:01:01-C*06:02:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 1,037  A*33:03:01-B*51:01:01-C*05:01:01-DRB1*11:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 1,038  A*33:03:01-B*51:01:01-C*15:02:01-DRB1*14:04:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.2870174
 1,039  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*01:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 1,040  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 1,041  A*33:03:01-B*58:01:01-C*07:01:02-DRB1*13:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.2870174
 1,042  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
 1,043  A*33:03-B*58:01-C*03:02-DRB1*13:01  Hong Kong Chinese BMDR 0.28597,595
 1,044  A*33:01-B*49:01-DRB1*11:04  Israel Poland Jews 0.285013,871
 1,045  A*33:03:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2810356
 1,046  A*33:03:01-B*51:01:01-C*16:02:01-DRB1*01:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2810356
 1,047  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.2810356
 1,048  A*33:03-B*44:03-C*07:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:01  Sri Lanka Colombo 0.2801714
 1,049  A*33:03-B*58:01-C*03:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.2801714
 1,050  A*33:03-B*58:01-C*03:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*26:01  Sri Lanka Colombo 0.2801714
 1,051  A*33-B*35-DRB1*03  Iran pop 4 0.2801855
 1,052  A*33-B*58-DRB1*07  Iran pop 4 0.2801855
 1,053  A*33:03-B*58:01  USA African American pop 4 0.28002,411
 1,054  A*33:03-C*03:02  Italy pop 5 0.2800975
 1,055  A*33-B*58-DRB1*03  Russia Moscow Pop 2 0.28002,000
 1,056  A*33-B*07-DRB1*01-DQB1*05  Mexico Veracruz Rural 0.2773539
 1,057  A*33-B*14:02-DRB1*07-DQB1*03:03  Mexico Tlaxcala, Tlaxcala city 0.2762181
 1,058  A*33-B*18-DRB1*03:01-DQB1*02  Mexico Tlaxcala, Tlaxcala city 0.2762181
 1,059  A*33-B*35-DRB1*13-DQB1*06  Mexico Sinaloa Rural 0.2732183
 1,060  A*33-B*40:02-DRB1*07-DQB1*02  Mexico Sinaloa Rural 0.2732183
 1,061  A*33-B*14-DRB1*15:01  Colombia Barranquilla 0.2700188
 1,062  A*33-B*35-DRB1*03:01  Colombia Barranquilla 0.2700188
 1,063  A*33-B*39-DRB1*08:01  Colombia Barranquilla 0.2700188
 1,064  A*33-B*39-DRB1*13:01  Colombia Barranquilla 0.2700188
 1,065  A*33-B*40-DRB1*04:01  Colombia Barranquilla 0.2700188
 1,066  A*33-B*50-DRB1*11:01  Colombia Barranquilla 0.2700188
 1,067  A*33-B*58-DRB1*11:02  Colombia Barranquilla 0.2700188
 1,068  A*33-B*78-DRB1*01:01  Colombia Barranquilla 0.2700188
 1,069  A*33:03-B*44:03-C*07:06-DRB1*14:04-DQB1*05:03  India East UCBB 0.26972,403
 1,070  A*33:03:01-B*07:02:01-C*07:02:01-DRB1*04:03:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,071  A*33:03:01-B*15:18:01-C*07:04:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,072  A*33:03:01-B*35:03:01-C*03:02:02-DRB1*13:02:01-DQB1*04:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,073  A*33:03:01-B*37:01:01-C*06:02:01-DRB1*15:02:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,074  A*33:03:01-B*40:01:02-C*03:04:01-DRB1*13:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,075  A*33:03:01-B*40:06:01-C*07:06-DRB1*15:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 0.2688186
 1,076  A*33:03:01-B*51:01:01-C*07:06-DRB1*15:01:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,077  A*33:03:01-B*51:01:01-C*14:02:01-DRB1*15:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,078  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*04:08:01-DQB1*06:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,079  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*15:02:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,080  A*33:03:01-B*58:01:01-C*14:02:01-DRB1*15:01:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,081  A*33:03:01-B*58:01:01-C*16:02:01-DRB1*04:03:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 1,082  A*33:01-B*14:02-DRB1*04:04  Israel Libya Jews 0.26803,739
 1,083  A*33-B*14:02-DRB1*01-DQB1*05  Mexico Veracruz, Xalapa 0.2674187
 1,084  A*33:01-B*14:02-DRB1*01:02  Israel Libya Jews 0.26303,739
 1,085  A*33:01-B*58:01-C*03:02-DRB1*12:01-DQB1*03:01  Malaysia Peninsular Malay 0.2629951
 1,086  A*33:01-B*14:02-DRB1*11:01  Israel Tunisia Jews 0.26109,070
 1,087  A*33:01:01-B*08:01:01-C*08:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 0.2604192
 1,088  A*33:01:01-B*18:01:01-C*15:02:01:01-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.2604192
 1,089  A*33:03:01-B*13:02:01-C*03:02:02-DRB1*10:01:01-DQB1*02:01:01  Russia Bashkortostan, Tatars 0.2604192
 1,090  A*33:03:01-B*18:01:01-C*12:03:01:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Tatars 0.2604192
 1,091  A*33:03:01-B*35:03:01-C*03:02:02-DRB1*15:02-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 1,092  A*33:03:01-B*44:02:01:01-C*05:01:01:02-DRB1*13:02:01-DQB1*06:09:01  Russia Bashkortostan, Tatars 0.2604192
 1,093  A*33:03:01-B*44-C*03:02:02-DRB1*15:01:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.2604192
 1,094  A*33:03:01-B*49:01:01-C*07:01:01-DRB1*11:04:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.2604192
 1,095  A*33:03:01-B*58:01:01-C*08:22-DRB1*13:02:01-DQB1*06:09:01  Russia Bashkortostan, Tatars 0.2604192
 1,096  A*33:01-B*14:02-C*08:02-DRB1*01:01-DQA1*05:01-DQB1*05:01-DPB1*04:01  USA San Diego 0.2600496
 1,097  A*33:01-B*14:02-C*08:02-DRB1*11:04-DQA1*01:01-DQB1*03:01-DPB1*04:02  USA San Diego 0.2600496
 1,098  A*33:01-B*14:02-C*12:03-DRB1*11:04-DQA1*05:01-DQB1*02:01-DPB1*02:01  USA San Diego 0.2600496
 1,099  A*33:01-B*15:03-C*02:10-DRB1*04:04-DQA1*03:01-DQB1*04:02-DPB1*04:01  USA San Diego 0.2600496
 1,100  A*33:01-B*27:05-C*02:02-DRB1*04:04-DQA1*01:01-DQB1*03:02-DPB1*04:01  USA San Diego 0.2600496

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 1,001 to 1,100 (from 7,008) records   Pages: 11 12 13 14 15 16 17 18 19 20 of 71  


   

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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