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immunotation

Skill file skills/general/immunotation/SKILL.md in bioMate-AI/biomate-bioconductor-kb. Read the publisher’s upstream source.

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bioconductor-immunotation

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Use bioconductor-immunotation to query the global population frequencies for HLA allele [allele] with a sample size [size]

Required inputs

  • [allele]
  • [size]

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SKILL.md

name: bioconductor-immunotationdescription: MHC (major histocompatibility complex) molecules are cell surface complexes that present antigens to T cells.  The repertoire of antigens presented in a given genetic background largely depends on the sequence of the encoded MHC molecules, and thus, in humans, on the highly variable HLA (human leukocyte antigen) genes of the hyperpolymorphic HLA locus. More than 28,000 different HLA alleles have been reported, with significant differences in allele frequencies between human populations worldwidewhen_to_use: Use when: MHC (major histocompatibility complex) molecules are cell surface complexes that present antigens to T cells; User guide immunotation. Not for: Requires R ≥ 4.1 and Bioconductor ≥ 3.16user-invocable: false

immunotation

Workflows

Standard Workflow

library(immunotation)

# 1. Retrieve valid organisms and chain lookup table for humans
organisms <- get_valid_organisms()
human_chains <- retrieve_chain_lookup_table(organism = "human")

# 2. Map HLA alleles to serotypes and NetMHCpan inputs
allele_list <- c("A*01:01:01", "A*02:01:01", "B*39:01:01")
serotypes <- get_serotypes(allele_list, mhc_type = "MHC-I")
mhcpan_input <- get_mhcpan_input(allele_list, mhc_class = "MHC-I")

# 3. Query allele frequencies in global populations
freq_data <- query_allele_frequencies(
  hla_selection = "A*02:01", 
  hla_sample_size_pattern = "bigger_than", 
  hla_sample_size = 10000, 
  standard = "g"
)

Input/Output Note: Inputs are HLA allele lists and population query parameters; outputs are serotypes, tool-compatible HLA strings, and population frequency tables.

When to Use

  • Converting HLA allele names to serotypes using get_serotypes.
  • Formatting HLA alleles for immunoinformatics tools like NetMHCpan using get_mhcpan_input.
  • Mapping HLA alleles to G groups (get_G_group) or P groups (get_P_group).
  • Querying HLA allele and haplotype frequencies from the Allele Frequency Net Database (AFND) using query_allele_frequencies and query_haplotype_frequencies.
  • Visualizing global allele frequency distributions on a world map using plot_allele_frequency.

When NOT to Use

  • For predicting peptide-MHC binding directly (use tools like NetMHCpan; immunotation only formats the inputs).
  • For non-MHC/HLA gene annotations.

Data Requirements

  • Character vectors of HLA allele names in standard WHO nomenclature (e.g., "A*01:01:01").

Key Parameters

  • organism: Species name (e.g., "human", "mouse") used in retrieve_chain_lookup_table.
  • mhc_type: MHC class type ("MHC-I" or "MHC-II") used in get_serotypes.
  • mhc_class: MHC class ("MHC-I" or "MHC-II") used in get_mhcpan_input.
  • hla_selection: HLA allele or allele group to query.
  • hla_sample_size_pattern: Pattern for filtering sample size (e.g., "bigger_than").
  • hla_sample_size: Minimum sample size for population queries.
  • standard: AFND data standard quality filter (e.g., "g" for Gold, "s" for Silver, "b" for Bronze).

Best Practices

  • Use get_valid_organisms to check if a species is supported before building a lookup table.
  • Convert alleles to G or P groups using get_G_group or get_P_group to resolve ambiguous HLA typings.
  • Filter AFND queries using standard = "g" (Gold standard) to ensure high-quality allele frequency data.

Common Pitfalls

  • Querying MHC-II serotypes with incomplete alpha/beta chain annotations, which returns NA. Ensure both chains are annotated in the MHC restriction ontology (MRO).

Alternatives

  • HLAtools: For general HLA data manipulation and analysis.

Citations

  • Robinson J, Barker DJ, Georgiou X et al. IPD-IMGT/HLA Database. Nucleic Acids Research (2020)
  • Gonzalez-Galarza FF, McCabe A, Santos EJ at al. Allele frequency net database (AFND) 2020 update. Nucleic Acids Research (2020)

References