arcasHLA: high resolution HLA typing from RNAseq
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The human leukocyte antigen (HLA) locus plays a critical role in tissue compatibility and regulates the host response to many diseases, including cancers and autoimmune disorders. Recent improvements in the quality and accessibility of next-generation sequencing have made HLA typing from standard short-read data practical. However, this task remains challenging given the high level of polymorphism and homology between HLA genes. HLA typing from RNA sequencing is further complicated by post-transcriptional modifications and bias due to amplification.
To address this, the Rabadan Lab developed arcasHLA, a fast and accurate in silico tool that infers HLA genotypes from RNA sequencing data. Our tool outperforms established tools on the gold-standard benchmark dataset for HLA typing in terms of both accuracy and speed, with an accuracy rate of 100% at two-field resolution for class I genes, and over 99.7% for class II. Furthermore, we evaluate the performance of our tool on a new biological dataset of 447 single-end total RNA samples from nasopharyngeal swabs, and establish the applicability of arcasHLA in metatranscriptome studies.
“arcasHLA: high resolution HLA typing from RNAseq”
AUTHORS: Orenbuch R, Filip I, Comito D, Shaman J, Pe'er I, Rabadan R.
LINK TO PUBLICATION:
Bioinformatics. 2019 Jun 7. pii: btz474. doi: 10.1093/bioinformatics/btz474