ReviewCommunications biology2023
Transcriptome-wide association studies: recent advances in methods, applications and available databases.
Review in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 2 of them syntheses that pooled it.
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
108 citing papers in PubMed, 2 syntheses or guidelines pooled it, 127 citations in OpenAlex.
- Integrative bioinformatics frameworks for abdominal aortic aneurysm using GWAS meta-analysis, biological network construction, and structural modeling.Scientific reports · 2025Pooled it
- Hippocampal transcriptome-wide association study and pathway analysis of mitochondrial solute carriers in Alzheimer's disease.Translational psychiatry · 2024Pooled it
- Review
- Integrating genomics, multi-omics, CRISPR and speed breeding for stress-resilient vegetable legume improvement.Functional & integrative genomics · 2026Review
- FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.PLoS genetics · 2026Article
- Post-genome-wide association study variant-to-function challenges in asthma research.The Journal of allergy and clinical immunology · 2026Review
- Genetics-Informed Mapping Identifies a CRIM1-Associated Endocardial Inflammatory Remodeling State in Acute Myocardial Infarction.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies.Genome biology · 2026Article
- Multi-ancestry gene expression models amplify transcriptome-wide association study discovery and validation.Nature communications · 2026Article
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Transcriptome-informed brain cartography of polygenic risk and association with brain structure in major psychiatric disorders.Molecular psychiatry · 2026Article
- Genetic architecture of the murine serum metabolome reveals carboxyl esterases as master regulators of circulating fatty acid metabolism.bioRxiv : the preprint server for biology · 2026Article
- Pathway-level epigenetic modeling illuminates the methylation architecture to asthma risk across tissues.Epigenetics & chromatin · 2026Article
- Cross-trait mapping of shared susceptibility across inflammatory bowel disease and spondyloarthropathies.Journal of translational medicine · 2026Article
- Orchestrating multi-state QTL analysis with Bioconductor.BMC bioinformatics · 2026Article
- APOE*4 risk-modifying genes and drug targets in Alzheimer's disease through cell-type-specific genomic analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Causal Relationship Between Blood Proteome and Retinitis Pigmentosa: A Mendelian Randomization Study.Translational vision science & technology · 2026Article
- Causal variants in animal genomes: approaches to identification, phenotypic impact, and implications for selective breeding.BMC genomics · 2026Review
- PHEWAS, TWAS, Mendelian Randomization in Osteoporosis Research: the good, the bad, and the ugly.Current osteoporosis reports · 2026Review
- FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.bioRxiv : the preprint server for biology · 2026Article
48 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association study has identified fruitful variants impacting heritable traits. Nevertheless, identifying critical genes underlying those significant variants has been a great task. Transcriptome-wide association study (TWAS) is an instrumental post-analysis to detect significant gene-trait associations focusing on modeling transcription-level regulations, which has made numerous progresses in recent years. Leveraging from expression quantitative loci (eQTL) regulation information, TWAS has advantages in detecting functioning genes regulated by disease-associated variants, thus providing insight into mechanisms of diseases and other phenotypes. Considering its vast potential, this review article comprehensively summarizes TWAS, including the methodology, applications and available resources.
Indexed as
Identifiers
What Socratic 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 Socratic graph.