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

• Published in: Bioinformatics Vol. 36; no. 12; pp. 3905 - 3906
• Main Authors: Darby, Charlotte A, Stubbington, Michael J T, Marks, Patrick J, Martínez Barrio, Álvaro, Fiddes, Ian T
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.06.2020
• Subjects: Alleles; Applications Notes; Gene Expression; Humans; Sequence Analysis, RNA; Single-Cell Analysis; Software; Workflow
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btaa264

Abstract Summary Bulk RNA sequencing studies have demonstrated that human leukocyte antigen (HLA) genes may be expressed in a cell type-specific and allele-specific fashion. Single-cell gene expression assays have the potential to further resolve these expression patterns, but currently available methods do not perform allele-specific quantification at the molecule level. Here, we present scHLAcount, a post-processing workflow for single-cell RNA-seq data that computes allele-specific molecule counts of the HLA genes based on a personalized reference constructed from the sample’s HLA genotypes. Availability and implementation scHLAcount is available under the MIT license at https://github.com/10XGenomics/scHLAcount. Supplementary information Supplementary data are available at Bioinformatics online.