Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Detecting cell-type-specific allelic expression imbalance by integrative analysis of bulk and single-cell RNA sequencing data.

PLoS genetics - 1 Mar 2021

Fan Jiaxin, Wang Xuran, Xiao Rui, Li Mingyao

Abstract excerpt

Allelic expression imbalance (AEI), quantified by the relative expression of two alleles of a gene in a diploid organism, can help explain phenotypic variations among individuals. Traditional methods detect AEI using bulk RNA sequencing (RNA-seq) data, a data type that averages out cell-to-cell heterogeneity in gene expression across cell types. Since the patterns of AEI may vary across different cell types, it...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Allelic Imbalance
Share to Biomarkers
Share to Gene Expression Profiling

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Expression Regulation

Share to High-Throughput Nucleotide Sequencing

Share to Organ Specificity

Share to Sequence Analysis, RNA

Share to Single-Cell Analysis

Source

Open in PubMed Open full text

Identifiers

PMID: 33661921
DOI: 10.1371/journal.pgen.1009080
PMCID: PMC7963069

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Detecting cell-type-specific allelic expression imbalance by integrative analysis of bulk and single-cell RNA sequencing data.PMID 33661921Read ↗

Detecting cell-type-specific allelic expression imbalance by integrative analysis of bulk and single-cell RNA sequencing dataSemantic proximity Read ↗

Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets.Semantic proximity Read ↗

Imbalance and Composition Correction Ensemble Learning Framework (ICCELF): A novel framework for automated scRNA-seq cell type annotationSemantic proximity Read ↗

iDESC: Identifying differential expression in single-cell RNA sequencing data with multiple subjectsSemantic proximity Read ↗

A unified framework for cell-type-specific eQTL prioritization by integrating bulk and scRNA-seq data.Semantic proximity Read ↗

A unified framework for cell-type-specific eQTLs prioritization by integrating bulk and scRNA-seq dataSemantic proximity Read ↗

Experimental and Computational Methods for Allelic Imbalance Analysis from Single-Nucleus RNA-seq DataSemantic proximity Read ↗

Accurate estimation of cell composition in bulk expression through robust integration of single-cell informationSemantic proximity Read ↗

A compendium of methods: Searching allele specific expression via RNA sequencing.Semantic proximity Read ↗

Single-cell allele-specific expression analysis reveals dynamic and cell-type-specific regulatory effectsSemantic proximity Read ↗

SCDC: Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing ReferencesSemantic proximity Read ↗

Single-cell allele-specific expression analysis reveals dynamic and cell-type-specific regulatory effects.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.