immunogenetr

June 5, 2026 · View on GitHub

immunogenetr is a comprehensive toolkit for clinical HLA informatics. It is built on tidyverse principles and makes use of genotype list string (GL string, https://glstring.org/) for storing and using HLA genotype data.

Specific functionalities of this library include:

Coercion of HLA data in tabular format to and from GL string.
Calculation of matching and mismatching in all directions, with multiple output formats.
Automatic formatting of HLA data for searching within a GL string.
Truncation of molecular HLA data to a specific number of fields.
Reading HLA genotypes in HML files and extracting the GL string.

Installation
Usage
Citation
License
Disclaimer

Installation

You may install immunogenetr from CRAN with the below line of code:

install.packages("immunogenetr")

Usage

To demonstrate some functionality of immunogenetr we will use an internal dataset to perform match grades for a putative recipient/donor pair.

library(immunogenetr)
library(tidyverse)

# The "HLA_typing_1" dataset is installed with immunogenetr, and contains high resolution typing at all classical
# HLA loci for ten individuals.

kable_hla(HLA_typing_1)

patient	A1	A2	C1	C2	B1	B2	DRB345_1	DRB345_2	DRB1_1	DRB1_2	DQA1_1	DQA1_2	DQB1_1	DQB1_2	DPA1_1	DPA1_2	DPB1_1	DPB1_2
1	`A*24:02`	`A*29:02`	`C*07:04`	`C*16:01`	`B*44:02`	`B*44:03`	`DRB5*01:01`	`DRB5*01:01`	`DRB1*15:01`	`DRB1*15:01`	`DQA1*01:02`	`DQA1*01:02`	`DQB1*06:02`	`DQB1*06:02`	`DPA1*01:03`	`DPA1*01:03`	`DPB1*03:01`	`DPB1*04:01`
2	`A*02:01`	`A*11:05`	`C*07:01`	`C*07:02`	`B*07:02`	`B*08:01`	`DRB3*01:01`	`DRB4*01:03`	`DRB1*03:01`	`DRB1*04:01`	`DQA1*03:03`	`DQA1*05:01`	`DQB1*02:01`	`DQB1*03:01`	`DPA1*01:03`	`DPA1*01:03`	`DPB1*04:01`	`DPB1*04:01`
3	`A*02:01`	`A*26:18`	`C*02:02`	`C*03:04`	`B*27:05`	`B*54:01`	`DRB3*02:02`	`DRB4*01:03`	`DRB1*04:04`	`DRB1*14:54`	`DQA1*01:04`	`DQA1*03:01`	`DQB1*03:02`	`DQB1*05:02`	`DPA1*01:03`	`DPA1*02:02`	`DPB1*02:01`	`DPB1*05:01`
4	`A*29:02`	`A*30:02`	`C*06:02`	`C*07:01`	`B*08:01`	`B*13:02`	`DRB4*01:03`	`DRB4*01:03`	`DRB1*04:01`	`DRB1*07:01`	`DQA1*02:01`	`DQA1*03:01`	`DQB1*02:02`	`DQB1*03:02`	`DPA1*01:03`	`DPA1*02:01`	`DPB1*01:01`	`DPB1*16:01`
5	`A*02:05`	`A*24:02`	`C*07:18`	`C*12:03`	`B*35:03`	`B*58:01`	`DRB3*02:02`	`DRB3*02:02`	`DRB1*03:01`	`DRB1*14:54`	`DQA1*01:04`	`DQA1*05:01`	`DQB1*02:01`	`DQB1*05:03`	`DPA1*01:03`	`DPA1*02:01`	`DPB1*10:01`	`DPB1*124:01`
6	`A*01:01`	`A*24:02`	`C*07:01`	`C*14:02`	`B*49:01`	`B*51:01`	`DRB3*03:01`	`DRBX*NNNN`	`DRB1*08:01`	`DRB1*13:02`	`DQA1*01:02`	`DQA1*04:01`	`DQB1*04:02`	`DQB1*06:04`	`DPA1*01:03`	`DPA1*01:04`	`DPB1*04:01`	`DPB1*15:01`
7	`A*03:01`	`A*03:01`	`C*03:03`	`C*16:01`	`B*15:01`	`B*51:01`	`DRB4*01:01`	`DRBX*NNNN`	`DRB1*01:01`	`DRB1*07:01`	`DQA1*01:01`	`DQA1*02:01`	`DQB1*02:02`	`DQB1*05:01`	`DPA1*01:03`	`DPA1*01:03`	`DPB1*04:01`	`DPB1*04:01`
8	`A*01:01`	`A*32:01`	`C*06:02`	`C*07:02`	`B*08:01`	`B*37:01`	`DRB3*02:02`	`DRB5*01:01`	`DRB1*03:01`	`DRB1*15:01`	`DQA1*01:02`	`DQA1*05:01`	`DQB1*02:01`	`DQB1*06:02`	`DPA1*01:03`	`DPA1*02:01`	`DPB1*04:01`	`DPB1*14:01`
9	`A*03:01`	`A*30:01`	`C*07:02`	`C*12:03`	`B*07:02`	`B*38:01`	`DRB3*01:01`	`DRB5*01:01`	`DRB1*03:01`	`DRB1*15:01`	`DQA1*01:02`	`DQA1*05:01`	`DQB1*02:01`	`DQB1*06:02`	`DPA1*01:03`	`DPA1*01:03`	`DPB1*04:01`	`DPB1*04:01`
10	`A*02:05`	`A*11:01`	`C*07:18`	`C*16:02`	`B*51:01`	`B*58:01`	`DRB3*03:01`	`DRB5*01:01`	`DRB1*13:02`	`DRB1*15:01`	`DQA1*01:02`	`DQA1*01:03`	`DQB1*06:01`	`DQB1*06:09`	`DPA1*01:03`	`DPA1*01:03`	`DPB1*02:01`	`DPB1*104:01`

immunogenetr uses genotype list strings (GL strings) for most functions, including the matching and mismatching functions. To easily convert the genotypes found in “HLA_typing_1” to GL strings we can use the HLA_columns_to_GLstring function:

HLA_typing_1_GLstring <- HLA_typing_1 %>%
  mutate(GL_string = HLA_columns_to_GLstring(., HLA_typing_columns = A1:DPB1_2), .after = patient) %>%
  # Note the syntax for the `HLA_columns_to_GLstring` arguments - when this function is used inside
  # of a `mutate` function to make a new column in a data frame, "." is used in the first argument
  # to tell the function to use the working data frame as the source of the HLA typing columns.
  select(patient, GL_string)

kable_hla(HLA_typing_1_GLstring)

patient	GL_string
1	`HLA-A24:02+HLA-A29:02^HLA-C07:04+HLA-C16:01^HLA-B44:02+HLA-B44:03^HLA-DRB501:01+HLA-DRB501:01^HLA-DRB115:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:02^HLA-DQB106:02+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB103:01+HLA-DPB104:01`
2	`HLA-A02:01+HLA-A11:05^HLA-C07:01+HLA-C07:02^HLA-B07:02+HLA-B08:01^HLA-DRB301:01^HLA-DRB401:03^HLA-DRB103:01+HLA-DRB104:01^HLA-DQA103:03+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB103:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`
3	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
4	`HLA-A29:02+HLA-A30:02^HLA-C06:02+HLA-C07:01^HLA-B08:01+HLA-B13:02^HLA-DRB401:03+HLA-DRB401:03^HLA-DRB104:01+HLA-DRB107:01^HLA-DQA102:01+HLA-DQA103:01^HLA-DQB102:02+HLA-DQB103:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB101:01+HLA-DPB116:01`
5	`HLA-A02:05+HLA-A24:02^HLA-C07:18+HLA-C12:03^HLA-B35:03+HLA-B58:01^HLA-DRB302:02+HLA-DRB302:02^HLA-DRB103:01+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB105:03^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB110:01+HLA-DPB1124:01`
6	`HLA-A01:01+HLA-A24:02^HLA-C07:01+HLA-C14:02^HLA-B49:01+HLA-B51:01^HLA-DRB303:01^HLA-DRB108:01+HLA-DRB113:02^HLA-DQA101:02+HLA-DQA104:01^HLA-DQB104:02+HLA-DQB106:04^HLA-DPA101:03+HLA-DPA101:04^HLA-DPB104:01+HLA-DPB1*15:01`
7	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`
8	`HLA-A01:01+HLA-A32:01^HLA-C06:02+HLA-C07:02^HLA-B08:01+HLA-B37:01^HLA-DRB302:02^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB104:01+HLA-DPB114:01`
9	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`
10	`HLA-A02:05+HLA-A11:01^HLA-C07:18+HLA-C16:02^HLA-B51:01+HLA-B58:01^HLA-DRB303:01^HLA-DRB501:01^HLA-DRB113:02+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:03^HLA-DQB106:01+HLA-DQB106:09^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB102:01+HLA-DPB1104:01`

The “HLA_typing_1_GLstring” data frame now contains a row with a GL string for each individual, containing their full HLA genotype in a single string. Let’s select one individual to act as a recipient, and one to act as a donor.

# Select one case each for recipient and donor.
HLA_typing_1_GLstring_recipient <- HLA_typing_1_GLstring %>%
  filter(patient == 7) %>%
  rename(GL_string_recipient = GL_string, case = patient)

HLA_typing_1_GLstring_donor <- HLA_typing_1_GLstring %>%
  filter(patient == 9) %>%
  rename(GL_string_donor = GL_string) %>%
  select(-patient)

# Combine the tables so recipient and donor are on the same row.
HLA_typing_1_recip_donor <- bind_cols(
  HLA_typing_1_GLstring_recipient,
  HLA_typing_1_GLstring_donor
  )

kable_hla(HLA_typing_1_recip_donor)

case	GL_string_recipient	GL_string_donor
7	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`

We now have a data frame with a recipient and donor HLA genotype on one row. Let’s try out some of the mismatching functions on this data.

HLA_typing_1_recip_donor_mismatches <- HLA_typing_1_recip_donor %>%
  mutate(A_MM_GvH = HLA_mismatch_logical(
                      GL_string_recipient,
                      GL_string_donor,
                      "HLA-A",
                      direction = "GvH"),
                    .after = case) %>%
  mutate(A_MM_HvG = HLA_mismatch_logical(
                      GL_string_recipient,
                      GL_string_donor,
                      "HLA-A",
                      direction = "HvG"),
                    .after = A_MM_GvH)

kable_hla(HLA_typing_1_recip_donor_mismatches)

case	A_MM_GvH	A_MM_HvG	GL_string_recipient	GL_string_donor
7	FALSE	TRUE	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`

The HLA_mismatch_logical function determines if there are any mismatches at a particular locus. We’ve determined that at the HLA-A locus there are not any mismatches in the graft-versus-host direction, but are in the host-versus-graft direction. We can use the HLA_mismatched_alleles function to tell us what those mismatches are:

HLA_typing_1_recip_donor_mismatched_allles <- HLA_typing_1_recip_donor %>%
  mutate(A_HvG_MMs = HLA_mismatched_alleles(
                        GL_string_recipient,
                        GL_string_donor,
                        "HLA-A",
                        direction = "HvG"),
                      .after = case)

kable_hla(HLA_typing_1_recip_donor_mismatched_allles)

case	A_HvG_MMs	GL_string_recipient	GL_string_donor
7	`HLA-A*30:01`	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`

The HLA_mismatched_alleles function reported that the “HLA-A*30:01” allele was mismatched in the HvG direction. Sometimes, however, we simply want to know how many mismatches are at a particular locus. We can do that with the HLA_mismatch_number function:

# Determine the number of bidirectional mismatches at several loci.
HLA_typing_1_recip_donor_MM_number <- HLA_typing_1_recip_donor %>%
  mutate(ABCDRB1_MM = HLA_mismatch_number(
                        GL_string_recipient,
                        GL_string_donor,
                        c("HLA-A", "HLA-B", "HLA-C", "HLA-DRB1"),
                        direction = "bidirectional"),
                      .after = case)

kable_hla(HLA_typing_1_recip_donor_MM_number)

case	ABCDRB1_MM	GL_string_recipient	GL_string_donor
7	`HLA-A=1, HLA-B=2, HLA-C=2, HLA-DRB1=2`	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`

We might want to calculate an HLA match summary for stem cell transplantation. We can use the HLA_match_summarry_HCT function for this:

# The match_grade argument of "Xof8" will return the number of matches at the HLA-A, B, C, and DRB1 loci.
HLA_typing_1_recip_donor_8of8_matching <- HLA_typing_1_recip_donor %>%
  mutate(ABCDRB1_matching = HLA_match_summary_HCT(
                              GL_string_recipient,
                              GL_string_donor,
                              direction = "bidirectional",
                              match_grade = "Xof8"),
                            .after = case)

kable_hla(HLA_typing_1_recip_donor_8of8_matching)

case	ABCDRB1_matching	GL_string_recipient	GL_string_donor
7	1	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`

Clearly, this recipient and donor are not a great match. Let’s see how we could use this workflow to find the best-matched donor from several options. To do this, we’ll choose a case from “HLA_typing_1” and compare it to all the cases in that data set:

# Select one case to be the recipient.
HLA_typing_1_GLstring_candidate <- HLA_typing_1_GLstring %>%
  filter(patient == 3) %>%
  select(GL_string) %>%
  rename(GL_string_recip = GL_string)

# Join the recipient to the 10-donor list and perform matching
HLA_typing_1_GLstring_donors <- HLA_typing_1_GLstring %>%
  rename(GL_string_donor = GL_string, donor = patient) %>%
  cross_join(HLA_typing_1_GLstring_candidate) %>%
  mutate(ABCDRB1_matching = HLA_match_summary_HCT(
                              GL_string_recip,
                              GL_string_donor,
                              direction = "bidirectional",
                              match_grade = "Xof8"),
                            .after = donor) %>%
  arrange(desc(ABCDRB1_matching))

kable_hla(HLA_typing_1_GLstring_donors)

donor	ABCDRB1_matching	GL_string_donor	GL_string_recip
3	8	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
2	1	`HLA-A02:01+HLA-A11:05^HLA-C07:01+HLA-C07:02^HLA-B07:02+HLA-B08:01^HLA-DRB301:01^HLA-DRB401:03^HLA-DRB103:01+HLA-DRB104:01^HLA-DQA103:03+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB103:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
5	1	`HLA-A02:05+HLA-A24:02^HLA-C07:18+HLA-C12:03^HLA-B35:03+HLA-B58:01^HLA-DRB302:02+HLA-DRB302:02^HLA-DRB103:01+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB105:03^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB110:01+HLA-DPB1124:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
1	0	`HLA-A24:02+HLA-A29:02^HLA-C07:04+HLA-C16:01^HLA-B44:02+HLA-B44:03^HLA-DRB501:01+HLA-DRB501:01^HLA-DRB115:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:02^HLA-DQB106:02+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB103:01+HLA-DPB104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
4	0	`HLA-A29:02+HLA-A30:02^HLA-C06:02+HLA-C07:01^HLA-B08:01+HLA-B13:02^HLA-DRB401:03+HLA-DRB401:03^HLA-DRB104:01+HLA-DRB107:01^HLA-DQA102:01+HLA-DQA103:01^HLA-DQB102:02+HLA-DQB103:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB101:01+HLA-DPB116:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
6	0	`HLA-A01:01+HLA-A24:02^HLA-C07:01+HLA-C14:02^HLA-B49:01+HLA-B51:01^HLA-DRB303:01^HLA-DRB108:01+HLA-DRB113:02^HLA-DQA101:02+HLA-DQA104:01^HLA-DQB104:02+HLA-DQB106:04^HLA-DPA101:03+HLA-DPA101:04^HLA-DPB104:01+HLA-DPB1*15:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
7	0	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
8	0	`HLA-A01:01+HLA-A32:01^HLA-C06:02+HLA-C07:02^HLA-B08:01+HLA-B37:01^HLA-DRB302:02^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB104:01+HLA-DPB114:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
9	0	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
10	0	`HLA-A02:05+HLA-A11:01^HLA-C07:18+HLA-C16:02^HLA-B51:01+HLA-B58:01^HLA-DRB303:01^HLA-DRB501:01^HLA-DRB113:02+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:03^HLA-DQB106:01+HLA-DQB106:09^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB102:01+HLA-DPB1104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`

We can see that donor 3 is the only donor with an 8/8 match for the recipient.

Citation

If you use immunogenetr in your research, please cite:

Coskun B, Brown NK. Immunogenetr: A comprehensive toolkit for clinical HLA informatics. Human Immunology. 2026;87(1):111619. doi:%5B10.1016/j.humimm.2025.111619](https://doi.org/10.1016/j.humimm.2025.111619)

You can also get the citation from R with citation("immunogenetr").

License

This project is licensed under the GNU General Public License v3.0.

Disclaimer

This library is intended for research use. Any application making use of this package in a clinical setting will need to be independently validated according to local regulations.

patient	GL_string
1	`HLA-A24:02+HLA-A29:02^HLA-C07:04+HLA-C16:01^HLA-B44:02+HLA-B44:03^HLA-DRB501:01+HLA-DRB501:01^HLA-DRB115:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:02^HLA-DQB106:02+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB103:01+HLA-DPB104:01`
2	`HLA-A02:01+HLA-A11:05^HLA-C07:01+HLA-C07:02^HLA-B07:02+HLA-B08:01^HLA-DRB301:01^HLA-DRB401:03^HLA-DRB103:01+HLA-DRB104:01^HLA-DQA103:03+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB103:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`
3	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
4	`HLA-A29:02+HLA-A30:02^HLA-C06:02+HLA-C07:01^HLA-B08:01+HLA-B13:02^HLA-DRB401:03+HLA-DRB401:03^HLA-DRB104:01+HLA-DRB107:01^HLA-DQA102:01+HLA-DQA103:01^HLA-DQB102:02+HLA-DQB103:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB101:01+HLA-DPB116:01`
5	`HLA-A02:05+HLA-A24:02^HLA-C07:18+HLA-C12:03^HLA-B35:03+HLA-B58:01^HLA-DRB302:02+HLA-DRB302:02^HLA-DRB103:01+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB105:03^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB110:01+HLA-DPB1124:01`
6	`HLA-A01:01+HLA-A24:02^HLA-C07:01+HLA-C14:02^HLA-B49:01+HLA-B51:01^HLA-DRB303:01^HLA-DRB108:01+HLA-DRB113:02^HLA-DQA101:02+HLA-DQA104:01^HLA-DQB104:02+HLA-DQB106:04^HLA-DPA101:03+HLA-DPA101:04^HLA-DPB104:01+HLA-DPB1*15:01`
7	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`
8	`HLA-A01:01+HLA-A32:01^HLA-C06:02+HLA-C07:02^HLA-B08:01+HLA-B37:01^HLA-DRB302:02^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB104:01+HLA-DPB114:01`
9	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`
10	`HLA-A02:05+HLA-A11:01^HLA-C07:18+HLA-C16:02^HLA-B51:01+HLA-B58:01^HLA-DRB303:01^HLA-DRB501:01^HLA-DRB113:02+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:03^HLA-DQB106:01+HLA-DQB106:09^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB102:01+HLA-DPB1104:01`

donor	ABCDRB1_matching	GL_string_donor	GL_string_recip
3	8	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
2	1	`HLA-A02:01+HLA-A11:05^HLA-C07:01+HLA-C07:02^HLA-B07:02+HLA-B08:01^HLA-DRB301:01^HLA-DRB401:03^HLA-DRB103:01+HLA-DRB104:01^HLA-DQA103:03+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB103:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
5	1	`HLA-A02:05+HLA-A24:02^HLA-C07:18+HLA-C12:03^HLA-B35:03+HLA-B58:01^HLA-DRB302:02+HLA-DRB302:02^HLA-DRB103:01+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB105:03^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB110:01+HLA-DPB1124:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
1	0	`HLA-A24:02+HLA-A29:02^HLA-C07:04+HLA-C16:01^HLA-B44:02+HLA-B44:03^HLA-DRB501:01+HLA-DRB501:01^HLA-DRB115:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:02^HLA-DQB106:02+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB103:01+HLA-DPB104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
4	0	`HLA-A29:02+HLA-A30:02^HLA-C06:02+HLA-C07:01^HLA-B08:01+HLA-B13:02^HLA-DRB401:03+HLA-DRB401:03^HLA-DRB104:01+HLA-DRB107:01^HLA-DQA102:01+HLA-DQA103:01^HLA-DQB102:02+HLA-DQB103:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB101:01+HLA-DPB116:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
6	0	`HLA-A01:01+HLA-A24:02^HLA-C07:01+HLA-C14:02^HLA-B49:01+HLA-B51:01^HLA-DRB303:01^HLA-DRB108:01+HLA-DRB113:02^HLA-DQA101:02+HLA-DQA104:01^HLA-DQB104:02+HLA-DQB106:04^HLA-DPA101:03+HLA-DPA101:04^HLA-DPB104:01+HLA-DPB1*15:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
7	0	`HLA-A03:01+HLA-A03:01^HLA-C03:03+HLA-C16:01^HLA-B15:01+HLA-B51:01^HLA-DRB401:01^HLA-DRB101:01+HLA-DRB107:01^HLA-DQA101:01+HLA-DQA102:01^HLA-DQB102:02+HLA-DQB105:01^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB1*04:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
8	0	`HLA-A01:01+HLA-A32:01^HLA-C06:02+HLA-C07:02^HLA-B08:01+HLA-B37:01^HLA-DRB302:02^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA102:01^HLA-DPB104:01+HLA-DPB114:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
9	0	`HLA-A03:01+HLA-A30:01^HLA-C07:02+HLA-C12:03^HLA-B07:02+HLA-B38:01^HLA-DRB301:01^HLA-DRB501:01^HLA-DRB103:01+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA105:01^HLA-DQB102:01+HLA-DQB106:02^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB104:01+HLA-DPB104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`
10	0	`HLA-A02:05+HLA-A11:01^HLA-C07:18+HLA-C16:02^HLA-B51:01+HLA-B58:01^HLA-DRB303:01^HLA-DRB501:01^HLA-DRB113:02+HLA-DRB115:01^HLA-DQA101:02+HLA-DQA101:03^HLA-DQB106:01+HLA-DQB106:09^HLA-DPA101:03+HLA-DPA101:03^HLA-DPB102:01+HLA-DPB1104:01`	`HLA-A02:01+HLA-A26:18^HLA-C02:02+HLA-C03:04^HLA-B27:05+HLA-B54:01^HLA-DRB302:02^HLA-DRB401:03^HLA-DRB104:04+HLA-DRB114:54^HLA-DQA101:04+HLA-DQA103:01^HLA-DQB103:02+HLA-DQB105:02^HLA-DPA101:03+HLA-DPA102:02^HLA-DPB102:01+HLA-DPB105:01`

Table of Contents

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Citation

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Disclaimer