GENOMIC REFERENCE BIAS, STRUCTURAL VARIATION, AND INTERPRETIVE UNCERTAINTY IN HUMAN PANGENOME-BASED GENETIC ANALYSIS

Human pangenome references replace the exclusive reliance on a single linear genome sequence with models that preserve diverse assembled haplotypes and alternative genomic paths. This change can improve detection and genotyping of alleles that are in-completely represented by conventional references, particularly structural variants in repeat-rich and duplicated regions. Yet greater sequence inclusiveness does not automatically resolve uncertainty in read placement, haplotype assignment, coordinate translation, or clinical interpretation. This review examines reference bias as a combination of alignment, ascertainment, representation, and downstream interpretation effects. Drawing on seven peer-reviewed studies, it evaluates graph construction, sequence-resolved structural variation, haplotype-informed genotyping, population representativeness, locus-specific complexity, clinical evidence requirements, and reproducibility. Particular attention is given to distinguishing observed molecular sequence from probabilistic genotypes and causal biological claims. The synthesis argues that technical gains should be measured against task-specific truth sets, independently confirmed where necessary, and reported with explicit reference provenance and uncertainty. Pan-genome systems are most valuable when additional allelic diversity strengthens scientific inference without concealing the limits of the underlying observations.