Line |
Haplotype |
Population |
Frequency (%) |
Sample Size |
Distribution¹ |
1 | A*68:01-B*55:01-C*01:02-DRB1*11:11-DQA1*05:01-DQB1*03:01-DPB1*26:01 | | Sri Lanka Colombo | 0.4202 | | 714 |
|
2 | A*74:01-B*81:01-C*18:01-DRB1*11:118-DQB1*03:19-DPB1*01:01 | | Tanzania Maasai | 0.1597 | | 336 |
|
3 | A*24:02-B*38:01-C*12:03-DRB1*11:11 | | Germany DKMS - Bosnia and Herzegovina minority | 0.0970 | | 1,028 |
|
4 | DRB1*11:11-DQB1*03:01 | | USA Asian pop 2 | 0.0880 | | 1,772 |
|
5 | A*24:02-B*40:06-C*15:02-DRB1*11:11-DQA1*01:01-DQB1*05:03-DPB1*02:01 | | Sri Lanka Colombo | 0.0700 | | 714 |
|
6 | A*33:03-B*55:01-C*01:02-DRB1*11:11-DQA1*05:01-DQB1*03:01-DPB1*26:01 | | Sri Lanka Colombo | 0.0700 | | 714 |
|
7 | A*68:01-B*55:01-C*01:02-DRB1*11:11-DQA1*05:01-DQB1*03:01-DPB1*03:01 | | Sri Lanka Colombo | 0.0700 | | 714 |
|
8 | A*68:01-B*35:01-C*04:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0551 | | 2,492 |
|
9 | A*24:07-B*55:01-C*01:02-DRB1*11:11-DQB1*03:01 | | Malaysia Peninsular Malay | 0.0526 | | 951 |
|
10 | A*02:11-B*15:05-C*03:03-DRB1*11:11-DQB1*03:01 | | USA Asian pop 2 | 0.0440 | | 1,772 |
|
11 | A*26:01-B*55:01-C*01:02-DRB1*11:11-DQB1*03:01 | | USA Asian pop 2 | 0.0440 | | 1,772 |
|
12 | A*02:01-B*18:01-C*07:01-DRB1*11:11 | | Germany DKMS - Romania minority | 0.0410 | | 1,234 |
|
13 | A*03-B*44-DRB1*11:112 | | Chile Santiago | 0.0323 | | 920 |
|
14 | A*03-B*44-DRB1*11:117 | | Chile Santiago | 0.0323 | | 920 |
|
15 | A*01:01-B*51:01-C*16:01-DRB1*11:11 | | Germany DKMS - Greece minority | 0.0260 | | 1,894 |
|
16 | A*02:01-B*51:01-C*14:02-DRB1*11:11 | | Germany DKMS - Greece minority | 0.0260 | | 1,894 |
|
17 | A*11:01-B*56:01-C*01:02-DRB1*11:11 | | Germany DKMS - Greece minority | 0.0260 | | 1,894 |
|
18 | A*68:01-B*15:18-C*07:04-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0242 | | 2,492 |
|
19 | A*01:01-B*58:01-C*07:01-DRB1*11:11 | | Germany DKMS - Croatia minority | 0.0240 | | 2,057 |
|
20 | A*25:01-B*18:01-C*12:03-DRB1*11:11 | | Germany DKMS - Croatia minority | 0.0240 | | 2,057 |
|
21 | A*01-B*49-DRB1*11:117 | | Chile Santiago | 0.0229 | | 920 |
|
22 | A*69-B*55-DRB1*11:117 | | Chile Santiago | 0.0222 | | 920 |
|
23 | A*02:01-B*38:01-DRB1*11:11 | | Israel Ashkenazi Jews pop 3 | 0.0216 | | 4,625 |
|
24 | A*02-B*15-DRB1*11:117 | | Chile Santiago | 0.0205 | | 920 |
|
25 | A*68:01-B*55:01-C*01:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0201 | | 2,492 |
|
26 | A*01-B*40-DRB1*11:117 | | Chile Santiago | 0.0199 | | 920 |
|
27 | A*02-B*51-DRB1*11:117 | | Chile Santiago | 0.0173 | | 920 |
|
28 | A*02-B*51-DRB1*11:112 | | Chile Santiago | 0.0172 | | 920 |
|
29 | A*02-B*15-DRB1*11:112 | | Chile Santiago | 0.0155 | | 920 |
|
30 | A*68-B*51-DRB1*11:117 | | Chile Santiago | 0.0150 | | 920 |
|
31 | A*02:05-B*38:01-DRB1*11:11 | | Israel Poland Jews | 0.0144 | | 13,871 |
|
32 | A*02-B*35-DRB1*11:117 | | Chile Santiago | 0.0138 | | 920 |
|
33 | A*02:01-B*38:01-DRB1*11:11 | | Israel Argentina Jews | 0.0116 | | 4,307 |
|
34 | A*01-B*40-DRB1*11:112 | | Chile Santiago | 0.0109 | | 920 |
|
35 | A*02:05-B*38:01-DRB1*11:11 | | Israel Ashkenazi Jews pop 3 | 0.0108 | | 4,625 |
|
36 | A*32:13-B*51:01-C*12:03-DRB1*11:11-DQB1*03:01 | | Germany DKMS - Turkey minority | 0.0100 | | 4,856 |
|
37 | A*68-B*39-DRB1*11:112 | | Chile Santiago | 0.0097 | | 920 |
|
38 | A*68-B*39-DRB1*11:117 | | Chile Santiago | 0.0092 | | 920 |
|
39 | A*02-B*14-DRB1*11:117 | | Chile Santiago | 0.0091 | | 920 |
|
40 | A*02-B*40-DRB1*11:117 | | Chile Santiago | 0.0091 | | 920 |
|
41 | A*23-B*51-DRB1*11:112 | | Chile Santiago | 0.0091 | | 920 |
|
42 | A*23-B*51-DRB1*11:117 | | Chile Santiago | 0.0091 | | 920 |
|
43 | A*24-B*39-DRB1*11:117 | | Chile Santiago | 0.0091 | | 920 |
|
44 | A*26-B*57-DRB1*11:117 | | Chile Santiago | 0.0091 | | 920 |
|
45 | A*26-B*58-DRB1*11:117 | | Chile Santiago | 0.0091 | | 920 |
|
46 | A*02:05-B*38:01-DRB1*11:11 | | Israel USSR Jews | 0.0088 | | 45,681 |
|
47 | A*02:05-B*38:01-DRB1*11:11 | | Israel USA Jews | 0.0083 | | 6,058 |
|
48 | A*68:02-B*51:01-DRB1*11:11 | | Israel USA Jews | 0.0083 | | 6,058 |
|
49 | A*01-B*49-DRB1*11:112 | | Chile Santiago | 0.0078 | | 920 |
|
50 | A*03-B*18-DRB1*11:117 | | Chile Santiago | 0.0078 | | 920 |
|
51 | A*03-B*44-DRB1*11:111 | | Chile Santiago | 0.0078 | | 920 |
|
52 | A*26-B*38-DRB1*11:117 | | Chile Santiago | 0.0078 | | 920 |
|
53 | A*68-B*39-DRB1*11:111 | | Chile Santiago | 0.0078 | | 920 |
|
54 | A*02:01-B*38:01-DRB1*11:11 | | Israel Poland Jews | 0.0072 | | 13,871 |
|
55 | A*02-B*07-DRB1*11:110 | | Chile Santiago | 0.0070 | | 920 |
|
56 | A*02-B*07-DRB1*11:111 | | Chile Santiago | 0.0070 | | 920 |
|
57 | A*01-B*57-DRB1*11:117 | | Chile Santiago | 0.0068 | | 920 |
|
58 | A*02-B*47-DRB1*11:117 | | Chile Santiago | 0.0068 | | 920 |
|
59 | A*03-B*49-DRB1*11:113 | | Chile Santiago | 0.0068 | | 920 |
|
60 | A*02-B*44-DRB1*11:117 | | Chile Santiago | 0.0060 | | 920 |
|
61 | A*68-B*51-DRB1*11:112 | | Chile Santiago | 0.0058 | | 920 |
|
62 | A*24:02-B*45:01-DRB1*11:11 | | Israel Tunisia Jews | 0.0055 | | 9,070 |
|
63 | A*02-B*18-DRB1*11:117 | | Chile Santiago | 0.0054 | | 920 |
|
64 | A*02:01-B*38:01-DRB1*11:11 | | Israel USSR Jews | 0.0044 | | 45,681 |
|
65 | A*03:01-B*38:01-DRB1*11:11 | | Israel Poland Jews | 0.0036 | | 13,871 |
|
66 | A*02-B*07-DRB1*11:112 | | Chile Santiago | 0.0036 | | 920 |
|
67 | A*02-B*07-DRB1*11:117 | | Chile Santiago | 0.0036 | | 920 |
|
68 | A*30-B*27-DRB1*11:117 | | Chile Santiago | 0.0030 | | 920 |
|
69 | A*02-B*51-DRB1*11:110 | | Chile Santiago | 0.0029 | | 920 |
|
70 | A*02-B*51-DRB1*11:111 | | Chile Santiago | 0.0029 | | 920 |
|
71 | A*26:01:01-B*27:05:02-C*02:02:02-DRB1*11:113-DQB1*03:01:01 | | Poland BMR | 0.0021 | | 23,595 |
|
72 | A*26:01:01-B*51:01:01-C*15:02:01-DRB1*11:11:01-DQB1*03:01:01 | | Poland BMR | 0.0021 | | 23,595 |
|
73 | A*68:01-B*18:01-C*14:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0018 | | 2,492 |
|
74 | A*01:17-B*49:01-DRB1*11:11 | | Israel Poland Jews | 0.0018 | | 13,871 |
|
75 | A*01:36-B*49:01-DRB1*11:11 | | Israel Poland Jews | 0.0018 | | 13,871 |
|
76 | A*01-B*08-DRB1*11:117 | | Chile Santiago | 0.0017 | | 920 |
|
77 | A*24:02-B*51:06-C*12:04-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0013 | | 2,492 |
|
78 | A*24:03-B*51:06-C*12:04-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0013 | | 2,492 |
|
79 | A*24:07-B*51:01-C*12:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0013 | | 2,492 |
|
80 | A*68:01-B*38:01-DRB1*11:11 | | Israel USSR Jews | 0.0011 | | 45,681 |
|
81 | A*32:01-B*45:01-C*06:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0006070 | | 2,492 |
|
82 | A*32:02-B*45:01-C*06:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0006070 | | 2,492 |
|
83 | A*32:08-B*45:01-C*06:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0006070 | | 2,492 |
|
84 | A*24:02-B*41:01-C*17:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0003000 | | 2,492 |
|
85 | A*24:03-B*41:01-C*17:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0003000 | | 2,492 |
|
86 | A*24:07-B*41:01-C*17:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0003000 | | 2,492 |
|
87 | A*24:10-B*41:01-C*17:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0003000 | | 2,492 |
|
88 | A*24:17-B*41:01-C*17:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0003000 | | 2,492 |
|
89 | A*24:32-B*41:01-C*17:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0003000 | | 2,492 |
|
90 | A*24:55-B*41:01-C*17:01-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0003000 | | 2,492 |
|
91 | A*68:01-B*51:01-C*16:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0000255 | | 2,492 |
|
92 | A*24:02-B*35:01-C*12:03-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0000141 | | 2,492 |
|
93 | A*24:02-B*35:03-C*12:02-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0000141 | | 2,492 |
|
94 | A*24:02-B*35:03-C*12:03-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0000141 | | 2,492 |
|
95 | A*24:02-B*35:06-C*12:03-DRB1*11:11-DQB1*03:01 | | India Tamil Nadu | 0.0000141 | | 2,492 |
|
96 | A*02-B*08-DRB1*11:117 | | Chile Santiago | 0.0000000 | | 920 |
|
* Haplotype Frequencies: Total number of copies of the haplotype in the population sample (Haplotypes / 2n) shown in percentages (%).
: 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).