ArticleBMC medical genomics2015
ASEQ: fast allele-specific studies from next-generation sequencing data.
Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
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- Allele-resolved monosome and polysome sequencing identifies cis-variants affecting mRNA translation.Life science alliance · 2026Article
- Modified meiosis in the tardigrade Hypsibius exemplaris maintains heterozygosity across the genome.Genetics · 2026Article
- Modified meiosis in the tardigradebioRxiv : the preprint server for biology · 2026Article
- Bayesian estimation of allele-specific expression in the presence of phasing uncertainty.Bioinformatics (Oxford, England) · 2025Article
- Integrative Computational Analysis of Common EXO5 Haplotypes: Impact on Protein Dynamics, Genome Stability, and Cancer Progression.Journal of chemical information and modeling · 2025Article
- Statistical framework for calling allelic imbalance in high-throughput sequencing data.Nature communications · 2025Article
- Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis.Scientific reports · 2024Article
- RNA-seq data science: From raw data to effective interpretation.Frontiers in genetics · 2023Review
- Cloud-native distributed genomic pileup operations.Bioinformatics (Oxford, England) · 2023Article
- Comparative genomics of primary prostate cancer and paired metastases: insights from 12 molecular case studies.The Journal of pathology · 2022Article
- Allele expression biases in mixed-ploid sugarcane accessions.Scientific reports · 2022Article
- ASMdb: a comprehensive database for allele-specific DNA methylation in diverse organisms.Nucleic acids research · 2022Article
- Article
- Genomic profiling of late-onset basal cell carcinomas from two brothers with nevoid basal cell carcinoma syndrome.Journal of the European Academy of Dermatology and Venereology : JEADV · 2021Article
- MethHaplo: combining allele-specific DNA methylation and SNPs for haplotype region identification.BMC bioinformatics · 2020Article
- Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer.Cancer cell · 2020Article
- Transient inhibition of mTOR in human pluripotent stem cells enables robust formation of mouse-human chimeric embryos.Science advances · 2020Article
- HaploTypo: a variant-calling pipeline for phased genomes.Bioinformatics (Oxford, England) · 2020Article
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5 authors.
Funding
Abstract
backgroundSingle base level information from next-generation sequencing (NGS) allows for the quantitative assessment of biological phenomena such as mosaicism or allele-specific features in healthy and diseased cells. Such studies often present with computationally challenging burdens that hinder genome-wide investigations across large datasets that are now becoming available through the 1,000 Genomes Project and The Cancer Genome Atlas (TCGA) initiatives.
resultsWe present ASEQ, a tool to perform gene-level allele-specific expression (ASE) analysis from paired genomic and transcriptomic NGS data without requiring paternal and maternal genome data. ASEQ offers an easy-to-use set of modes that transparently to the user takes full advantage of a built-in fast computational engine. We report its performances on a set of 20 individuals from the 1,000 Genomes Project and show its detection power on imprinted genes. Next we demonstrate high level of ASE calls concordance when comparing it to AlleleSeq and MBASED tools. Finally, using a prostate cancer dataset we report on a higher fraction of ASE genes with respect to healthy individuals and show allele-specific events nominated by ASEQ in genes that are implicated in the disease.
conclusionsASEQ can be used to rapidly and reliably screen large NGS datasets for the identification of allele specific features. It can be integrated in any NGS pipeline and runs on computer systems with multiple CPUs, CPUs with multiple cores or across clusters of machines.
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