Analytical ambiguity is an inherent and expected feature of reverse sequence-specific oligonucleotide (rSSO)-based HLA genotyping and reflects the size of the candidate allele space compatible with a given probe pattern at the analytical interpretation level. However, ambiguity is often treated as a binary attribute, which may obscure differences in its magnitude across platforms. We conducted a between-subject comparison of two commercial rSSO HLA typing platforms, One Lambda (386 patients; 6176 allele-level observations) and Immucor GTI (1003 patients; 16,048 allele-level observations). Analytical ambiguity was quantified as candidate allele count (CandidateCount) across eight HLA loci (A, B, C, DRB1, DQB1, DQA1, DPB1 and DPA1). Generalized estimating equations with a negative binomial family were used to account for within-patient clustering, with rate ratios estimated using Immucor GTI as the reference and p-values adjusted for multiple testing. Four loci showed significantly larger analytical candidate allele spaces on One Lambda than on Immucor GTI after Benjamini-Hochberg correction, with the largest effect observed at DPA1, where mean CandidateCount values were more than doubled (18.3 vs. 8.3). Moderate but significant differences were also observed at HLA-A, DQB1 and DPB1, whereas no significant platform differences were detected at HLA-B, HLA-C, DRB1 or DQA1. These findings demonstrate that analytical ambiguity differs between commercial rSSO HLA typing platforms in a locus-specific manner. Quantitative characterization of ambiguity at the raw interpretation level may help set expectations regarding locus-specific resolution burden and support workflow planning in laboratories using rSSO as a first-line typing approach.
Yuan et al. (Wed,) studied this question.