ArticleBMC genomics2024
Disregarding multimappers leads to biases in the functional assessment of NGS data.
Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- The promise of long-read RNA-seq: reducing bias in analyses of allele imbalance.NAR genomics and bioinformatics · 2026Article
- kmerRRR: A k-mer based tool for functional genomics in Repeat Rich Regions.bioRxiv : the preprint server for biology · 2026Article
- MER57E3 transposable elements regulate gene expression in a human cell model of neural development.Genome biology · 2026Article
- Dissecting the contribution of transposable elements to interphase chromosome structure.Genome biology · 2026Article
- Extra-nasal odorant receptors: molecular mechanisms and therapeutic implications.Frontiers in physiology · 2026Review
- Investigating the Physiological Regulation of Transposable Elements In Vivo: Nuclei Preparation from Primary Mouse Tissues for Epigenomic Analyses and Computational Approaches to Interrogate the Repeat Genome.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Fastq-dupaway: a fast and memory-efficient tool for deduplication of single- and paired-end NGS data.Scientific reports · 2025Article
- Long-read RNA sequencing of transposable elements from single cells using CELLO-seq.Nature protocols · 2025Review
- ribofootPrinter: A precision python toolbox for analysis of ribosome profiling data.bioRxiv : the preprint server for biology · 2025Article
- Transcriptomic Profiling Provides Insight into the Molecular Basis of Heterosis in Philippine-RearedInsects · 2025Article
- Genetics of Wool and Cashmere Fibre: Progress, Challenges, and Future Research.Animals : an open access journal from MDPI · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundStandard 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.
resultsIn 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.
conclusionRevealing 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.