Line |
Haplotype |
Population |
Frequency (%) |
Sample Size |
Distribution¹ |
501 | A*02:01-B*38:01-C*12:03-DRB1*15:02 | | Poland DKMS | 0.0040 | | 20,653 |
|
502 | A*74:01-B*38:02-C*07:02-DRB1*15:02 | | Hong Kong Chinese BMDR | 0.0039 | | 7,595 |
|
503 | A*01:01-B*38:01-DRB1*15:02 | | Israel Morocco Jews | 0.0038 | | 36,718 |
|
504 | A*24:02-B*38:02-C*07:02-DRB1*15:01-DQB1*06:01 | | India West UCBB | 0.0038 | | 5,829 |
|
505 | A*24:05-B*38:01-DRB1*15:01 | | Israel Iraq Jews | 0.0038 | | 13,270 |
|
506 | A*25:01:01-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*06:03:01 | | Poland BMR | 0.0037 | | 23,595 |
|
507 | A*01:17-B*38:01-DRB1*15:02 | | Israel Poland Jews | 0.0036 | | 13,871 |
|
508 | A*01:36-B*38:01-DRB1*15:02 | | Israel Poland Jews | 0.0036 | | 13,871 |
|
509 | A*30:01-B*38:01-DRB1*15:01 | | Israel USSR Jews | 0.0034 | | 45,681 |
|
510 | A*24:02-B*38:02-C*07:02-DRB1*15:02-DRB5*01:01-DQB1*05:02 | | USA NMDP Chinese | 0.0032 | | 99,672 |
|
511 | A*02:02-B*38:01-DRB1*15:01 | | Israel Tunisia Jews | 0.0032 | | 9,070 |
|
512 | A*01:06-B*38:01-DRB1*15:01 | | Israel YemenJews | 0.0032 | | 15,542 |
|
513 | A*02:01-B*38:01-C*12:03-DRB1*15:19 | | Poland DKMS | 0.0032 | | 20,653 |
|
514 | A*29:01-B*38:01-DRB1*15:02 | | Israel Poland Jews | 0.0031 | | 13,871 |
|
515 | A*33:03-B*38:02-C*07:02-DRB1*15:02-DQB1*05:01 | | India South UCBB | 0.0029 | | 11,446 |
|
516 | A*31:08-B*38:01-DRB1*15:01 | | Israel USSR Jews | 0.0029 | | 45,681 |
|
517 | A*68:02-B*38:01-DRB1*15:02 | | Israel Morocco Jews | 0.0028 | | 36,718 |
|
518 | A*24:04-B*38:01-DRB1*15:02 | | Israel Morocco Jews | 0.0027 | | 36,718 |
|
519 | A*31:01-B*38:01-C*12:03-DRB1*15:01 | | Poland DKMS | 0.0027 | | 20,653 |
|
520 | A*02:17-B*38:01-C*12:03-DRB1*15:01 | | Poland DKMS | 0.0025 | | 20,653 |
|
521 | A*30:01-B*38:01-C*12:03-DRB1*15:01 | | Poland DKMS | 0.0025 | | 20,653 |
|
522 | A*24:02-B*38:01-DRB1*15:02 | | Israel YemenJews | 0.0025 | | 15,542 |
|
523 | A*03:01-B*38:01-DRB1*15:02 | | Israel Morocco Jews | 0.0025 | | 36,718 |
|
524 | A*11:01-B*38:01-C*07:02-DRB1*15:01 | | Poland DKMS | 0.0024 | | 20,653 |
|
525 | A*68:01-B*38:01-C*12:03-DRB1*15:02 | | Poland DKMS | 0.0024 | | 20,653 |
|
526 | A*68:01-B*38:01-C*12:03-DRB1*15:19 | | Poland DKMS | 0.0024 | | 20,653 |
|
527 | A*68:02-B*38:01-DRB1*15:01 | | Israel Poland Jews | 0.0022 | | 13,871 |
|
528 | A*68:02-B*38:01-DRB1*15:02 | | Israel Poland Jews | 0.0022 | | 13,871 |
|
529 | A*29:02:01-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*06:03:01 | | Poland BMR | 0.0022 | | 23,595 |
|
530 | A*66:01-B*38:01-DRB1*15:02 | | Israel Poland Jews | 0.0022 | | 13,871 |
|
531 | A*74:03-B*38:01-C*07:02-DRB1*15:02-DQB1*05:03 | | India Tamil Nadu | 0.0021 | | 2,492 |
|
532 | A*74:03-B*38:02-C*07:02-DRB1*15:02-DQB1*05:03 | | India Tamil Nadu | 0.0021 | | 2,492 |
|
533 | A*66:01:01-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*06:03:01 | | Poland BMR | 0.0021 | | 23,595 |
|
534 | A*03:01:01-B*38:01:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01 | | Poland BMR | 0.0021 | | 23,595 |
|
535 | A*26:01:01-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*03:03:02 | | Poland BMR | 0.0021 | | 23,595 |
|
536 | A*29:01:01-B*38:01:01-C*12:03:18-DRB1*15:01:01-DQB1*06:02:01 | | Poland BMR | 0.0021 | | 23,595 |
|
537 | A*68:01:02-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*05:02:01 | | Poland BMR | 0.0021 | | 23,595 |
|
538 | A*66:01:01-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*03:01:01 | | Poland BMR | 0.0020 | | 23,595 |
|
539 | A*30:02-B*38:01-DRB1*15:01 | | Israel Morocco Jews | 0.0020 | | 36,718 |
|
540 | A*02:01:01-B*38:01:01-C*02:02:02-DRB1*15:01:01-DQB1*06:02:01 | | Poland BMR | 0.0018 | | 23,595 |
|
541 | A*02:01-B*38:02-C*07:02-DRB1*15:04-DQB1*05:02 | | India South UCBB | 0.0016 | | 11,446 |
|
542 | A*74:03-B*38:01-C*07:02-DRB1*15:01-DQB1*05:02 | | India Tamil Nadu | 0.0014 | | 2,492 |
|
543 | A*74:03-B*38:01-C*07:02-DRB1*15:06-DQB1*05:02 | | India Tamil Nadu | 0.0014 | | 2,492 |
|
544 | A*74:03-B*38:02-C*07:02-DRB1*15:01-DQB1*05:02 | | India Tamil Nadu | 0.0014 | | 2,492 |
|
545 | A*74:03-B*38:02-C*07:02-DRB1*15:06-DQB1*05:02 | | India Tamil Nadu | 0.0014 | | 2,492 |
|
546 | A*03:04-B*38:01-DRB1*15:02 | | Israel Morocco Jews | 0.0014 | | 36,718 |
|
547 | A*66:01-B*38:01-DRB1*15:02 | | Israel USSR Jews | 0.0013 | | 45,681 |
|
548 | A*02:05-B*38:01-C*12:03-DRB1*15:02 | | Poland DKMS | 0.0012 | | 20,653 |
|
549 | A*02:05-B*38:01-C*12:03-DRB1*15:19 | | Poland DKMS | 0.0012 | | 20,653 |
|
550 | A*30:02-B*38:01-DRB1*15:01 | | Israel USSR Jews | 0.0011 | | 45,681 |
|
551 | A*01:17-B*38:01-DRB1*15:02 | | Israel USSR Jews | 0.0011 | | 45,681 |
|
552 | A*01:36-B*38:01-DRB1*15:02 | | Israel USSR Jews | 0.0011 | | 45,681 |
|
553 | A*03:02-B*38:01-DRB1*15:02 | | Israel USSR Jews | 0.0011 | | 45,681 |
|
554 | A*30-B*38-DRB1*15 | | Brazil South East Cord Blood | 0.0010 | | 11,409 |
|
555 | A*03:01-B*38:01-DRB1*15:02 | | Israel USSR Jews | 0.0009970 | | 45,681 |
|
556 | A*03:02-B*38:01-DRB1*15:01 | | Israel Morocco Jews | 0.0009910 | | 36,718 |
|
557 | A*31:01-B*38:01-DRB1*15:01 | | Israel USSR Jews | 0.0009240 | | 45,681 |
|
558 | A*31:01-B*38:01-DRB1*15:02 | | Israel USSR Jews | 0.0009220 | | 45,681 |
|
559 | A*03:01-B*38:01-C*12:03-DRB1*15:01 | | Poland DKMS | 0.0007000 | | 20,653 |
|
560 | A*24:02-B*38:02-C*07:02-DRB1*15:02-DRB5*01:01-DQB1*05:02 | | USA NMDP Mexican or Chicano | 0.0001910 | | 261,235 |
|
561 | A*24:02-B*38:02-C*07:02-DRB1*15:02-DRB5*01:01-DQB1*05:02 | | USA NMDP European Caucasian | 0.0000528 | | 1,242,890 |
|
562 | A*02:06-B*38:02-C*07:02-DRB1*15:02-DRB5*01:01-DQB1*05:02 | | USA NMDP European Caucasian | 0.0000402 | | 1,242,890 |
|
563 | A*11:01-B*38:02-C*07:02-DRB1*15:02-DRB5*01:01-DQB1*05:02 | | USA NMDP European Caucasian | 0.0000336 | | 1,242,890 |
|
564 | A*02:06-B*38:02-C*07:02-DRB1*15:02-DRB5*01:01-DQB1*05:02 | | USA NMDP African American pop 2 | 0.0000300 | | 416,581 |
|
565 | A*26:01-B*38:02-C*07:02-DRB1*15:02-DRB5*01:02-DQB1*05:01 | | USA NMDP South Asian Indian | 0.0000220 | | 185,391 |
|
* 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).