Disregarding multimappers leads to biases in the functional assessment of NGS data

作者：Michelle A. Paz, Sarah Warger, Leila Taher · 发表于：BMC Genomics · 年份：2024 · DOI：10.1186/s12864-024-10344-9 · 被引用次数：10 · 研究领域：Chromosomal and Genetic Variations、Single-cell and spatial transcriptomics、Genomic variations and chromosomal abnormalities

BACKGROUND: Standard ChIP-seq and RNA-seq processing pipelines typically disregard sequencing reads whose origin is ambiguous ("multimappers"). This usual practice has potentially important consequences for the functional interpretation of the data: genomic elements belonging to clusters composed of highly similar members are left unexplored. RESULTS: In particular, disregarding multimappers leads to the underrepresentation in epigenetic studies of recently active transposable elements, such as AluYa5, L1HS and SVAs. Furthermore, this common strategy also has implications for transcriptomic analysis: members of repetitive gene families, such the ones including major histocompatibility complex (MHC) class I and II genes, are under-quantified. CONCLUSION: Revealing inherent biases that permeate routine tasks such as functional enrichment analysis, our results underscore the urgency of broadly adopting multimapper-aware bioinformatic pipelines -currently restricted to specific contexts or communities- to ensure the reliability of genomic and transcriptomic studies.