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- W4282598052 abstract "ABSTRACT The human leukocyte antigen (HLA) locus plays a central role in adaptive immune function and has significant clinical implications for tissue transplant compatibility and allelic disease associations. Studies using bulk-cell RNA sequencing have demonstrated that HLA transcription may be regulated in an allele-specific manner and single-cell RNA sequencing (scRNA-seq) has the potential to better characterize these expression patterns. However, quantification of allele-specific expression (ASE) for HLA loci requires sample-specific reference genotyping due to extensive polymorphism. While genotype prediction from bulk RNA sequencing is well described, the feasibility of predicting HLA genotypes directly from single-cell data is unknown. Here we evaluate and expand upon several computational HLA genotyping tools by comparing predictions from human single-cell data to gold-standard, molecular genotyping. The highest 2-field accuracy averaged across all loci was 76% by arcasHLA and increased to 86% using a composite model of multiple genotyping tools. We also developed a highly accurate model (AUC 0.93) for predicting HLA-DRB345 copy number in order to improve genotyping accuracy of the HLA-DRB locus. Genotyping accuracy improved with read depth and was reproducible at repeat sampling. Using a metanalytic approach, we also show that HLA genotypes from PHLAT and OptiType can generate ASE ratios that are highly correlated (R 2 = 0.8 and 0.94, respectively) with those derived from gold-standard genotyping. Highlights - Benchmarking of HLA genotype prediction accuracy from 5’- and 3’-based single-cell RNA-seq data compared to molecular HLA genotyping - Quantification of transcript coverage by 5’- and 3’-based single cell sequencing methods - Accurate prediction of complex HLA-DRB345 copy numbers using supervised learning - Balancing accuracy and performance through composite HLA genotyping - Meta-analytic approach to summarizing allele-specific expression of HLA genotypes at single-cell level" @default.
- W4282598052 created "2022-06-14" @default.
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- W4282598052 date "2022-06-12" @default.
- W4282598052 modified "2023-10-16" @default.
- W4282598052 title "Prediction of HLA genotypes from single-cell transcriptome data" @default.
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- W4282598052 doi "https://doi.org/10.1101/2022.06.09.495569" @default.
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