Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 101 to 200 (from 3,437) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 35  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*24:02:01-B*51:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Black 1.470668
 102  A*30:02:01-B*14:02:01-C*08:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 103  A*30:02:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*03:01:01-DPB1*105:01:01  Brazil Rio de Janeiro Black 1.470668
 104  A*66:01:01-B*35:03:01-C*04:01:01-DRB1*13:03:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*11:01:01  Brazil Rio de Janeiro Black 1.470668
 105  DRB1*07:01-DQB1*02:02  Spain Tenerife Island 1.470083
 106  A*33:03-B*44:03-C*07:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*02:01  Sri Lanka Colombo 1.4006714
 107  A*01:01-B*40:01-DRB1*03:01:01-DQB1*02:02  USA South Dakota Lakota Sioux 1.4000302
 108  A*02:01-B*44:02-DRB1*07:01-DQB1*02:02  USA South Dakota Lakota Sioux 1.4000302
 109  DRB1*07:01-DQB1*02:02-DPB1*01:01  Ireland South 1.4000250
 110  A*02-B*50-DRB1*07-DQA1*02-DQB1*02:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 1.3400112
 111  A*24-B*13-DRB1*07-DQA1*02-DQB1*02:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 1.3400112
 112  A*03:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Puyanawa 1.3333150
 113  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Italy pop 5 1.3300975
 114  A*02:11-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India East UCBB 1.32552,403
 115  A*02:02-B*15:03-C*02:02-E*01:03:01-F*01:01:01-G*01:01-DRB1*09:01:02-DQA1*03:03-DQB1*02:02  Portugal Azores Terceira Island 1.3158130
 116  DQA1*02:01-DQB1*02:02-DPA1*02:01-DPB1*17:01  Hong Kong Chinese HKBMDR. DQ and DP 1.31121,064
 117  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Ireland South 1.3000250
 118  A*68:01-B*58:02-C*06:02-DRB1*07:01-DQA1*03:01-DQB1*02:02-DPB1*04:02  South Africa Worcester 1.3000159
 119  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*13:01  South Korea pop 11 1.3000149
 120  DRB1*07:01-DQB1*02:02-DPB1*02:01  Ireland South 1.3000250
 121  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*04:02  USA San Francisco Caucasian 1.3000220
 122  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*04:02  USA San Francisco Caucasian 1.3000220
 123  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  Nicaragua Managua 1.2987339
 124  B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 1.2800234
 125  A*33:03-B*44:03-C*07:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  Sri Lanka Colombo 1.2605714
 126  DRB1*04:05-DQB1*02:02  Cretan Islanders 1.2097124
 127  A*30:01-B*44-DRB1*07:01-DQB1*02:02  Tunisia pop 3 1.2000104
 128  A*32:01-B*14:01-C*08:02-DRB1*07:01-DQB1*02:02  Ireland South 1.2000250
 129  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*02:01  South Korea pop 2 1.2000207
 130  DRB1*07-DRB4*01-DQB1*02:02  Macedonia pop 2 1.200080
 131  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*13:01:01  Brazil Rio de Janeiro Parda 1.1765170
 132  A*24:02:01-B*35:08:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 1.1764170
 133  DRB1*07:01-DQB1*02:02-DPB1*15:01  Gambia pop 3 1.1611939
 134  A*02:11-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Central UCBB 1.15544,204
 135  A*24:02:01-B*44:03:02-C*07:06-DRB1*07:01:01-DQB1*02:02:01  India Karnataka Kannada Speaking 1.1490174
 136  A*29:01-B*44:02-DRB1*07:01-DQB1*02:02  Mexico Chihuahua Chihuahua City Pop 2 1.136488
 137  A*33:03:01-B*44:03:02-C*07:06-DRB1*07:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 1.1208186
 138  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 1.1181186
 139  A*33:01-B*44:03-C*07:01-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Indian 1.1070271
 140  A*33:01-B*44:03-C*07:01-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Malay 1.1041951
 141  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*02:01  South Korea pop 1 1.1000324
 142  DRB1*07:01-DQB1*02:02-DPB1*03:01  Ireland South 1.1000250
 143  DRB1*07:01-DQB1*02:02-DPB1*17:01  South Korea pop 1 1.1000324
 144  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*11:01  USA San Francisco Caucasian 1.1000220
 145  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*11:01  USA San Francisco Caucasian 1.1000220
 146  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 1.0753186
 147  A*29:02-B*44:03-C*15:02-DRB1*04:07-DQB1*02:02  Colombia North Chimila Amerindians 1.063847
 148  DRB1*07:01-DQB1*02:02-DPB1*17:01  Gambia pop 3 1.0626939
 149  A*30:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 1.05641,510
 150  B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 1.0490143
 151  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  USA San Diego 1.0420496
 152  A*29:02:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 1.0417192
 153  A*02-B*51-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Paraná Caucasian 1.0152641
 154  A*03:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Poland 1.0000200
 155  A*03:01-B*57:03-C*18:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Puyanawa 1.0000150
 156  A*03-B*07-DRB1*07-DQA1*02:01-DQB1*02:02  Jordan Amman 1.0000146
 157  A*23:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  Poland 1.0000200
 158  A*31-B*07-DRB1*07-DQA1*02:01-DQB1*02:02  Jordan Amman 1.0000146
 159  A*02:01:01-B*35:01:01-C*03:03:01-DRB1*07:01:01-DQB1*02:02:01  Vietnam Kinh 0.9900101
 160  A*11:01:01-B*15:02:01-C*08:01:01-DRB1*07:01:01-DQB1*02:02:01  Vietnam Kinh 0.9900101
 161  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.9727521
 162  A*29:02-B*40:11-C*16:01-DRB1*07:01-DQB1*02:02  Colombia North Wiwa El Encanto 0.961552
 163  A*30:01-B*14:02-C*04:01-DRB1*01:02-DQB1*02:02  Colombia North Wiwa El Encanto 0.961552
 164  A*33:18-B*44:45-C*04:01-DRB1*07:01-DQB1*02:02  Colombia North Wiwa El Encanto 0.961552
 165  A*02:01-B*44:03-C*04:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 166  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 167  A*03:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 168  A*11:01-B*44:03-C*04:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 169  A*24:17-B*44:03-C*05:01-DRB1*12:02-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 170  A*29:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 171  A*30:01-B*51:01-C*06:02-DRB1*04:02-DQA1*03:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 172  A*31:01-B*38:01-C*04:01-DRB1*04:05-DQA1*03:03-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 173  A*31:01-B*44:03-C*04:01-DRB1*04:05-DQA1*03:03-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 174  A*33:03-B*35:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 175  A*68:01-B*51:01-C*16:01-DRB1*11:01-DQA1*05:05-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 176  A*74:01-B*14:02-C*08:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 177  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02-DPB1*02:01  Panama 0.9500462
 178  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.937323,595
 179  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.9300215
 180  A*02-B*44-DRB1*07-DQA1*02-DQB1*02:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.8900112
 181  A*11-B*27-DRB1*07-DQA1*02-DQB1*02:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.8900112
 182  A*01:01-B*51:01-C*14:02-E*01:01:01-F*01:01:01-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.8772130
 183  A*03:01-B*44:02-C*05:01-E*01:03:02-F*01:01:01-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.8772130
 184  A*24:02-B*50:01-C*06:02-E*01:01:01-F*01:01:01-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.8772130
 185  A*32:01-B*14:01-C*08:02-E*01:01:01-F*01:01:01-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.8772130
 186  DRB1*07:01-DQB1*02:02-DPB1*01:01  Gambia pop 3 0.8756939
 187  DRB1*04:05-DQB1*02:02-DPB1*04:02  Gambia pop 3 0.8708939
 188  A*33:03:01-B*35:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  India Karnataka Kannada Speaking 0.8620174
 189  A*02-B*07-DRB1*07-DQA1*02-DQB1*02:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.8600112
 190  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.8600234
 191  B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.8600234
 192  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.859823,595
 193  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.85835,829
 194  A*23:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.85504,335
 195  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*07:01:01-DQA1*02:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.8403119
 196  A*33:03-B*44:03-C*07:01-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Malay 0.8403951
 197  A*02:01:01:01-B*50:01:01-C*06:02:01:02-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.8333120
 198  A*02:01:01-B*51:01:01-C*01:02:01-DRB1*07:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.8333120
 199  A*24:02:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.8333120
 200  A*26:01-B*08:01-DRB1*16:01-DQB1*02:02  Iran Saqqez-Baneh Kurds 0.833360

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 101 to 200 (from 3,437) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 35  


   

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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