RNA2HLA: HLA-based quality control of RNA-seq datasets

Area of Science:

• Genomics
• Immunogenetics
• Bioinformatics

Background:

• RNA-sequencing (RNA-seq) is a key tool for transcriptome analysis in biomedical research.
• Accurate sample assignment is critical for studies involving multiple samples from the same individual.
• Existing methods may not sufficiently guarantee sample integrity in complex RNA-seq studies.

Purpose of the Study:

• To introduce RNA2HLA, a novel quality control (QC) tool for RNA-seq data.
• To leverage human leukocyte antigen (HLA) typing for verifying RNA-seq sample allocation.
• To enable precise sample grouping and identification of misassigned samples.

Main Methods:

• Development of RNA2HLA, a bioinformatics tool for HLA-typing from RNA-seq data.
• Application of RNA2HLA for study-wide HLA allele extraction at four-digit resolution.
• Validation of the tool using publicly available RNA-seq datasets.

Main Results:

• RNA2HLA successfully performed HLA-typing on RNA-seq samples, enabling accurate sample allocation.
• The tool identified wrongly assigned samples in existing public datasets, highlighting its QC utility.
• RNA2HLA demonstrated the capability for large-scale HLA-typing from RNA-seq studies.

Conclusions:

• RNA2HLA is an effective tool for quality control in RNA-seq studies by verifying sample identity through HLA typing.
• The tool enhances the reliability of transcriptomic data by ensuring correct sample-to-individual assignments.
• RNA2HLA has broader applications in massive HLA-typing for various research purposes beyond sample QC.