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 101 to 200 (from 847) records   Pages: 1 2 3 4 5 6 7 8 9 of 9  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Vaish 2.8000198
 102  DRB1*15:02-DQA1*01:03-DQB1*05:01  India Northeast Vaish 2.8000198
 103  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Vaish 2.8000198
 104  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Kayastha 2.8000190
 105  DRB1*15:02-DQA1*01:03-DQB1*06:01  Algeria pop 2 2.8000106
 106  DRB1*15-DQA1*01:03-DQB1*06:01  Italy pop 2 2.800053
 107  DQA1*01:03-DQB1*06:01  Israel Yemenite Jews 2.700076
 108  DQA1*01:03-DQB1*06:03  Gambia 2.7000146
 109  DRB1*15:02-DQA1*01:03  Israel Ashkenazi Jews pop 2 2.7000132
 110  DRB1*15:02-DQA1*01:03-DQB1*06:01  Iran Fars Parsi 2.700073
 111  DQA1*01:03-DQB1*06:01  Israel Ashkenazi Jews pop 2 2.6000132
 112  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*05:01  South Korea pop 1 2.6000324
 113  DRB1*13:01-DQA1*01:03-DQB1*06:03  India Northeast Kayastha 2.6000190
 114  DRB1*15:02-DQA1*01:03-DQB1*06:01  South Korea pop 5 2.6000467
 115  DRB1*13:01-DQA1*01:03-DQB1*06:03  China Urumqi Han 2.500059
 116  DQA1*01:03-DQB1*06:03  Israel Iranian Jews 2.4000101
 117  DRB1*15:02-DQA1*01:03-DQB1*06:01  China Urumqi Kazak 2.400042
 118  A*02:01-B*38:01-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03  Brazil Puyanawa 2.3333150
 119  DRB1*13:01-DQA1*01:03-DQB1*03:01  Russia Siberia Sulamai Ket 2.300022
 120  DRB1*13:01-DQA1*01:03-DQB1*06:05/06:09  Russia Tuva Todja 2.300022
 121  DRB1*13:03-DQA1*01:03-DQB1*06:02/06:11  Russia Tuva Todja 2.300022
 122  DRB1*15:01-DQA1*01:03-DQB1*06:01  Russia Tuva pop3 2.300044
 123  DRB1*15:01-DQA1*01:03-DQB1*06:01  Russia Siberia Sulamai Ket 2.300022
 124  DRB1*15:02-DQA1*01:03-DQB1*05:01  India Northeast Rastogi 2.3000196
 125  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*05:01  South Korea pop 2 2.2000207
 126  DRB1*13:01-DQA1*01:03-DQB1*06:03  Italy Sardinia Tempio 2.200091
 127  DRB1*15:02-DQA1*01:03-DQB1*06:01  Greece pop3 2.2000246
 128  DRB1*08:03-DQA1*01:03-DQB1*05:01  Russia Siberia Ulchi 2.100073
 129  DRB1*13:01-DQA1*01:03-DQB1*06:02  Russia Siberia Dudinka Nganasan 2.100024
 130  DRB1*13:01-DQA1*01:03-DQB1*06:03  India Northeast Rastogi 2.1000196
 131  DRB1*13:01-DQA1*01:03-DQB1*06:03/06:14  Russia Siberia Dudinka Nganasan 2.100024
 132  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Mathur 2.1000155
 133  A*02:01-B*40:02-C*02:02-DRB1*13:01-DQA1*01:03-DQB1*06:03  Brazil Puyanawa 2.0000150
 134  DRB1*13:01-DQA1*01:03-DQB1*06:03  Tunisia 2.0000100
 135  DRB1*13:01-DQA1*01:03-DQB1*06:03  Cameroon Yaounde 2.000092
 136  DRB1*13:01-DQA1*01:03-DQB1*06:03  England pop 6 2.0000177
 137  DRB1*13:01-DQA1*01:03-DQB1*06:03/06:14  Russia Siberia Khabarovsk Evenki 2.000025
 138  DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  South Korea pop 11 2.0000149
 139  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Rastogi 2.0000196
 140  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Rajbanshi 2.000098
 141  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Rastogi 2.0000196
 142  DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*09:01  South Korea pop 1 2.0000324
 143  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01  United Arab Emirates Abu Dhabi 1.920052
 144  A*02-B*44-DRB1*13-DQA1*01:03-DQB1*06:03  Georgia Svaneti Region Svan 1.900080
 145  A*26-B*38-DRB1*13:01-DRB3*02:02-DQA1*01:03-DQB1*06:03  Spain Murcia 1.9000173
 146  A*26-B*38-DRB1*13-DQA1*01:03-DQB1*06:03  Georgia Svaneti Region Svan 1.900080
 147  DRB1*11:04-DQA1*01:03  Israel Moroccan Jews 1.9000113
 148  DRB1*15-DQA1*01:03-DQB1*06:01  Russia Smolensk 1.9000156
 149  DRB1*15-DQA1*01:03-DQB1*06:01  Belarus Brest Region 1.9000105
 150  DRB1*15-DQA1*01:03-DQB1*06:02  Russia Arkhangelsk 1.900081
 151  DRB1*13:01-DQA1*01:03-DQB1*06:03  India Northeast Shia 1.8000190
 152  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Uttar Pradesh 1.8000202
 153  DRB1*15:02-DQA1*01:03-DQB1*06:01  USA San Francisco Caucasian 1.8000220
 154  A*26:01-B*38:01-C*12:03-E*01:03:01-F*01:01:01-G*01:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Portugal Azores Terceira Island 1.7544130
 155  DQA1*01:03-DQB1*06:01  Israel Libyan Jews 1.7000119
 156  DQA1*01:03-DQB1*06:09  Ecuador African 1.700058
 157  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:01  South Korea pop 2 1.7000207
 158  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Lachung 1.700058
 159  DRB1*15:02-DQA1*01:03-DQB1*06:01  Italy Sardinia Lanusei 1.700087
 160  DRB1*13:01-DQA1*01:03-DQB1*06:03  Mexico Highlands Mestizos 1.6000160
 161  DRB1*15:02-DQA1*01:03-DQB1*06:01  Italy Sardinia Oristano 1.600091
 162  A*02:01-B*45:01-C*16:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 1.5000100
 163  A*11-B*52-DRB1*15:02-DQA1*01:03-DQB1*06:01  Morocco 1.500096
 164  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:01  South Korea pop 1 1.5000324
 165  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:02  South Korea pop 2 1.5000207
 166  DRB1*13:01-DQA1*01:03-DQB1*06:03  Ethiopia Amhara 1.500098
 167  DRB1*13:01-DQA1*01:03-DQB1*06:05/06:09  Russia Siberia Khanty Mansi 1.500068
 168  DRB1*15:01-DQA1*01:03-DQB1*05:03  India Northeast Mathur 1.5000155
 169  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Mech 1.500063
 170  DRB1*15-DQA1*01:03-DQB1*06:01  Belarus Vitebsk Region 1.500070
 171  DRB1*08:01-DQA1*01:03-DQB1*06:02  Russia Siberia Polygus Evenk 1.400035
 172  DRB1*11:01:01-DQA1*01:03-DQB1*03:01  Russia Siberia Polygus Evenk 1.400035
 173  DRB1*13:01-DQA1*01:03-DQB1*06:03  Australia New South Wales Aborigine 1.4000177
 174  DRB1*14:03-DQA1*01:03-DQB1*06:02  Russia Siberia Polygus Evenk 1.400035
 175  DRB1*14:03-DQA1*01:03-DQB1*06:03  Russia Siberia Polygus Evenk 1.400035
 176  DRB1*15:01-DQA1*01:03-DQB1*06:02/06:11  Russia Siberia Khanty Mansi 1.400068
 177  DRB1*15:02-DQA1*01:03-DQB1*06:01  Russia Siberia Khanty Mansi 1.400068
 178  DRB1*15:02-DQA1*01:03-DQB1*06:01  India Northeast Sunni 1.4000188
 179  A*25-B*18-DRB1*13-DQA1*01:03-DQB1*06:03  Russia, South Ural, Chelyabinsk region, Nagaybaks 1.3400112
 180  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*09:01  USA San Diego 1.3020496
 181  A*02-B*08-DRB1*13-DQA1*01:03-DQB1*06:03  Georgia Svaneti Region Svan 1.300080
 182  A*02-B*44-DRB1*13-DQA1*01:03-DQB1*06:02  Georgia Svaneti Region Svan 1.300080
 183  DRB1*13:01-DQA1*01:03-DQB1*06:03  India Northeast Mathur 1.3000155
 184  DRB1*13:01-DQA1*01:03-DQB1*06:12  Equatorial Guinea Bioko Island Bubi 1.3000100
 185  DRB1*13:01-DRB3*02:02-DQA1*01:03-DQB1*06:03-DPB1*04:01  USA San Francisco Caucasian 1.3000220
 186  DRB1*13:01-DRB3*02:02-DQA1*01:03-DQB1*06:03-DPB1*04:01  USA San Francisco Caucasian 1.3000220
 187  DRB1*15:01-DQA1*01:03-DQB1*06:01  India Northeast Sunni 1.3000188
 188  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*02:02  China Zhejiang Han pop 2 1.2849833
 189  DQA1*01:03-DQB1*03:03  China, Xinjiang Uyghur Autonomous Region Hui 1.250040
 190  A*03:01-B*38:01-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03  Kosovo 1.2100124
 191  DQA1*01:03-DQB1*06:03  Japan Fukuoka 1.200086
 192  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:02  South Korea pop 1 1.2000324
 193  DRB1*13:01-DQA1*01:03-DQB1*06:03  Ethiopia Oromo 1.200083
 194  DRB1*13:01-DQA1*01:03-DQB1*06:03  India Northeast Sunni 1.2000188
 195  DRB1*13:01-DQA1*01:03-DQB1*06:03/06:14  Russia Siberia Irkutsk Tofalar 1.200043
 196  DRB1*13:01-DQA1*01:03-DQB1*06:04  Cameroon Yaounde 1.200092
 197  DRB1*13:01-DQA1*01:03-DQB1*06:04  Ethiopia Oromo 1.200083
 198  DRB1*15:02-DQA1*01:03-DQB1*06:01  Russia Siberia Irkutsk Tofalar 1.200043
 199  DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*09:01  South Korea pop 2 1.2000207
 200  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 1.1633833

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 847) records   Pages: 1 2 3 4 5 6 7 8 9 of 9  


   

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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