ArticleBioinformatics (Oxford, England)2015
QuASAR: quantitative allele-specific analysis of reads.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 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
57 citing papers in PubMed, 88 citations in OpenAlex.
- Bioinformatics insights into plant genomic imprinting: approaches, challenges, and future perspectives.Briefings in functional genomics · 2026Review
- Self-organizing maps for allele specific expression data reconstruction and identification of anomalous genomic regions.Frontiers in bioinformatics · 2026Article
- Non-Coding RNA in Type 2 Diabetes Cardio-Renal Complications and SGLT2 Inhibitor Response.International journal of molecular sciences · 2025Review
- HPTAS: An Alignment-Free Haplotype Phasing Algorithm Focused on Allele-Specific Studies Using Transcriptome Data.International journal of molecular sciences · 2025Article
- Bayesian estimation of allele-specific expression in the presence of phasing uncertainty.Bioinformatics (Oxford, England) · 2025Article
- Statistical framework for calling allelic imbalance in high-throughput sequencing data.Nature communications · 2025Article
- Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants.Science (New York, N.Y.) · 2025Article
- Population-level allelic dispersion modeling by maelstRom yields genome-wide maps of allele-specific dysregulation during early carcinogenesis.GigaScience · 2025Article
- A comprehensive analysis of allele-specific expression and transcriptomic profiling in pig limbic and endocrine tissues.Frontiers in molecular neuroscience · 2025Article
- Decoding polygenic diseases: advances in noncoding variant prioritization and validation.Trends in cell biology · 2024Review
- Genotype × environment interactions in gene regulation and complex traits.Nature genetics · 2024Review
- Epigenetic variation impacts individual differences in the transcriptional response to influenza infection.Nature genetics · 2024Article
- Exploring the Genetic Predisposition to Epigenetic Changes in Alzheimer's Disease.International journal of molecular sciences · 2023Article
- RNA-seq data science: From raw data to effective interpretation.Frontiers in genetics · 2023Review
- SNPs in 3'UTR miRNA Target Sequences Associated with Individual Drug Susceptibility.International journal of molecular sciences · 2022Review
- Quantification of mutant-allele expression at isoform level in cancer from RNA-seq data.NAR genomics and bioinformatics · 2022Article
- The dynamic, combinatorial cis-regulatory lexicon of epidermal differentiation.Nature genetics · 2021Article
- A Panel of rSNPs Demonstrating Allelic Asymmetry in Both ChIP-seq and RNA-seq Data and the Search for Their Phenotypic Outcomes through Analysis of DEGs.International journal of molecular sciences · 2021Article
- Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases.International journal of molecular sciences · 2021Review
- Replicate sequencing libraries are important for quantification of allelic imbalance.Nature communications · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
motivationExpression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls.
resultsWe present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. AVAILABILITY AND IMPLEMENTATION: http://github.com/piquelab/QuASAR. CONTACT: fluca@wayne.edu or rpique@wayne.edu SUPPLEMENTARY INFORMATION: Supplementary Material is available at Bioinformatics online.
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.