hlabud: HLA analysis in R

hlabud provides methods to retrieve sequence alignment data from IMGTHLA and convert the data into convenient R matrices ready for downstream analysis. See the usage examples to learn how to use the data with logistic regression and dimensionality reduction.

For example, let’s consider a simple question about two HLA genotypes.

What amino acid positions are different between these two genotypes?

library(hlabud)
a <- hla_alignments("DRB1")
dosage(a$onehot, c("DRB1*03:01:05", "DRB1*03:02:03"))

##               F26 Y26 D28 E28 F47 Y47 G86 V86
## DRB1*03:01:05   0   1   1   0   1   0   0   1
## DRB1*03:02:03   1   0   0   1   0   1   1   0

From this output, we can conclude that four positions (26, 28, 47, 86) distinguish these two HLA-DRB1 alleles. We see that DRB1*03:01:05 has a Y at position 26 and DRB1*03:02:03 has a F.

Installation

The quickest way to get hlabud is to install from GitHub:

# install.packages("devtools")
devtools::install_github("slowkow/hlabud")

Examples

See the usage examples to get some ideas for how to use hlabud in your analyses.

• Get a one-hot encoded matrix for all HLA-DRB1 alleles

• Convert genotypes to a dosage matrix

• Logistic regression association for amino acid positions

• UMAP embedding of 3,516 HLA-DRB1 alleles

• Get HLA allele frequencies from Allele Frequency Net Database (AFND)

• Compute HLA divergence with the Grantham distance matrix

• Download and unpack all data from the latest IMGTHLA release

• Visualize the 3D molecular structure of HLA proteins and highlight specific amino acid residues

Citation

hlabud provides access to the data in IMGT/HLA database. Therefore, if you use hlabud then please cite the IMGT/HLA paper:

• Robinson J, Barker DJ, Georgiou X, Cooper MA, Flicek P, Marsh SGE. IPD-IMGT/HLA Database. Nucleic Acids Res. 2020;48: D948–D955. doi:10.1093/nar/gkz950

hlabud also provides access to the data in Allele Frequency Net Database (AFND). Therefore, if you use hlabud::hla_frequencies() then please cite the AFND paper:

• Gonzalez-Galarza FF, McCabe A, Santos EJMD, Jones J, Takeshita L, Ortega-Rivera ND, et al. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools. Nucleic Acids Res. 2020;48: D783–D788. doi:10.1093/nar/gkz1029

Additionally, you can also cite the hlabud package like this:

• Slowikowski K. hlabud: methods for access and analysis of the human leukocyte antigen (HLA) gene sequence alignments from IMGT/HLA. R package version 1.0.0.

Related work

I recommend this article for anyone new to HLA, because the beautiful figures help to build intuition:

• La Gruta NL, Gras S, Daley SR, Thomas PG, Rossjohn J. Understanding the drivers of MHC restriction of T cell receptors. Nat Rev Immunol. 2018;18: 467–478.

Learn about the conventions for HLA nomenclature:

• Marsh SGE, Albert ED, Bodmer WF, Bontrop RE, Dupont B, Erlich HA, et al. Nomenclature for factors of the HLA system, 2010. Tissue Antigens. 2010;75: 291–455.

For case-control analysis of HLA genotype data, consider the BIGDAWG R package available on CRAN. Here is the related article:

• Pappas DJ, Marin W, Hollenbach JA, Mack SJ. Bridging ImmunoGenomic Data Analysis Workflow Gaps (BIGDAWG): An integrated case-control analysis pipeline. Hum Immunol. 2016;77: 283–287.