ArticleGenome biology2014
Allelic mapping bias in RNA-sequencing is not a major confounder in eQTL studies.
Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
44 citing papers in PubMed, 81 citations in OpenAlex.
- The landscape of allele-specific expression in human kidneys.Science advances · 2026Article
- MCPtaggR: R package for accurate genotype calling in reduced representation sequencing data by eliminating error-prone markers based on genome comparison.DNA research : an international journal for rapid publication of reports on genes and genomes · 2024Article
- Identifying novel regulatory effects for clinically relevant genes through the study of the Greek population.BMC genomics · 2023Article
- Allele-specific analysis reveals exon- and cell-type-specific regulatory effects of Alzheimer's disease-associated genetic variants.Translational psychiatry · 2022Article
- Targeted RNA-seq improves efficiency, resolution, and accuracy of allele specific expression for human term placentas.G3 (Bethesda, Md.) · 2021Article
- Article
- Zea mays RNA-seq estimated transcript abundances are strongly affected by read mapping bias.BMC genomics · 2021Article
- A vast resource of allelic expression data spanning human tissues.Genome biology · 2020Article
- The GTEx Consortium atlas of genetic regulatory effects across human tissues.Science (New York, N.Y.) · 2020Article
- ReQTL: identifying correlations between expressed SNVs and gene expression using RNA-sequencing data.Bioinformatics (Oxford, England) · 2020Article
- Loss of Imprinting in Human Placentas Is Widespread, Coordinated, and Predicts Birth Phenotypes.Molecular biology and evolution · 2020Article
- Mining GWAS and eQTL data for CF lung disease modifiers by gene expression imputation.PloS one · 2020Article
- Article
- Single cell transcriptome in aneuploidies reveals mechanisms of gene dosage imbalance.Nature communications · 2019Article
- A statistical method for joint estimation of cis-eQTLs and parent-of-origin effects under family trio design.Biometrics · 2019Article
- Quantification of allelic differential expression using a simple Fluorescence primer PCR-RFLP-based method.Scientific reports · 2019Article
- Human genes escaping X-inactivation revealed by single cell expression data.BMC genomics · 2019Article
- Extensive cellular heterogeneity of X inactivation revealed by single-cell allele-specific expression in human fibroblasts.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Modified penetrance of coding variants by cis-regulatory variation contributes to disease risk.Nature genetics · 2018Article
- Advances in Transcriptomics: Investigating Cardiovascular Disease at Unprecedented Resolution.Circulation research · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
Abstract
backgroundRNA sequencing (RNA-seq) is the current gold-standard method to quantify gene expression for expression quantitative trait locus (eQTL) studies. However, a potential caveat in these studies is that RNA-seq reads carrying the non-reference allele of variant loci can have lower probability to map correctly to the reference genome, which could bias gene quantifications and cause false positive eQTL associations. In this study, we analyze the effect of this allelic mapping bias in eQTL discovery.
resultsWe simulate RNA-seq read mapping over 9.5 M common SNPs and indels, with 15.6% of variants showing biased mapping rate for reference versus non-reference reads. However, removing potentially biased RNA-seq reads from an eQTL dataset of 185 individuals has a very small effect on gene and exon quantifications and eQTL discovery. We detect only a handful of likely false positive eQTLs, and overall eQTL SNPs show no significant enrichment for high mapping bias.
conclusionOur results suggest that RNA-seq quantifications are generally robust against allelic mapping bias, and that this does not have a severe effect on eQTL discovery. Nevertheless, we provide our catalog of putatively biased loci to allow better controlling for mapping bias to obtain more accurate results in future RNA-seq studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.