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scHLAcount: allele-specific HLA expression from single-cell gene expression data.

Charlotte A Darby1, Michael J T Stubbington2, Patrick J Marks2

  • 1Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.

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Summary

scHLAcount enables allele-specific quantification of human leukocyte antigen (HLA) gene expression from single-cell RNA sequencing data. This workflow provides molecule-level insights into HLA expression patterns, crucial for understanding immune responses.

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Area of Science:

  • Immunogenomics
  • Molecular biology
  • Bioinformatics

Background:

  • Bulk RNA sequencing suggests cell type- and allele-specific human leukocyte antigen (HLA) gene expression.
  • Current single-cell RNA sequencing (scRNA-seq) methods lack allele-specific quantification at the molecule level.

Purpose of the Study:

  • To introduce scHLAcount, a novel post-processing workflow for scRNA-seq data.
  • To enable allele-specific molecule counts for HLA genes.

Main Methods:

  • scHLAcount utilizes a personalized reference built from sample-specific HLA genotypes.
  • It processes scRNA-seq data to derive allele-specific HLA expression.

Main Results:

  • scHLAcount accurately computes allele-specific molecule counts for HLA genes.
  • The workflow enhances the resolution of HLA expression patterns in single cells.

Conclusions:

  • scHLAcount addresses a critical gap in scRNA-seq analysis for immunogenomics.
  • This tool facilitates deeper understanding of HLA expression heterogeneity and its functional implications.