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

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. In particular, disregarding multimappers leads to the systematic underrepresentation in epigenetic studies of recently active transposons, such as AluYa5 and L1HS. 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 systematically underquantified. Based on these findings, we strongly advocate for the implementation of multimapper-aware bioinformatic genomic analyses.