Recognizing and Mitigating Reference Bias in Population Genomics.

Reference bias in population and biodiversity genomics is linked to mapping distortions and downstream analytical errors, spanning five impact classes across studies.

• Why it matters: Mapping reads to a single reference can misassign low-quality mappings and skew results, yet the field still lacks a clear, consistent understanding of consequences.
• What they did: The authors survey the literature to catalog where reference bias occurs, its sources, and its impacts, then propose mitigation via divergence-aware filtering, tool benchmarking, and standardized reporting.
• The result: Impacts are inconsistent in direction and magnitude across studies, implying general rules are premature and motivating divergence-aware workflows and broader reference/pangenome approaches.

AI summary of the abstract · may contain errors · not medical advice · read the paper.