z-logo
open-access-imgOpen Access
scHLAcount: allele-specific HLA expression from single-cell gene expression data
Author(s) -
Charlotte A. Darby,
Michael J. T. Stubbington,
Patrick Marks,
Álvaro Martínez Barrio,
Ian T. Fiddes
Publication year - 2020
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa264
Subject(s) - human leukocyte antigen , allele , gene , biology , computational biology , rna , genotype , gene expression , genetics , rna seq , transcriptome , antigen
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom