Quantify genetic variants' regulatory potential via a hybrid sequence-oriented model
Abstract
Understanding how noncoding DNA determines gene expression is critical for decoding the functional genome. Leveraging a hybrid sequence-oriented architecture, we developed SVEN to model (and predict) tissue-specific transcriptomic impacts for large-scale structural variants across over 200 tissues and cell lines. We expect that SVEN will enable more effective in silico analysis and interpretation of human genome-wide disease-related genetic variants.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 0
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- RegVar: Tissue-specific Prioritization of Noncoding Regulatory Variants
Hao Xin Lu, Luyu Ma, … Chenggang Zhang·Genomics Proteomics & BioinformaticsPeer-reviewed·Dec 29, 2021
- Structural variants are a major source of gene expression differences in humans and often affect multiple nearby genes
Alexandra J. Scott, Colby Chiang, Ira M. Hall·Genome ResearchPeer-reviewed·Dec 1, 2021
- The impact of structural variation on human gene expression
Colby Chiang, Alexandra J Scott, … Ira M Hall·Nature GeneticsPeer-reviewed·Apr 3, 2017
- Machine learning-based prediction of human structural variation and characterization of associated sequence determinants
Daven Lim, Runyang Nicolas Lou, … Peter H. Sudmant·bioRxiv·Jul 15, 2026
- CADD-SV - a framework to score the effects of structural variants in health and disease
Philip Kleinert, Martin Kircher·Genome ResearchPeer-reviewed·Apr 1, 2022
- POSTRE: a tool to predict the pathological effects of human structural variants
Víctor Sánchez-Gaya, Álvaro Rada-Iglesias·Nucleic Acids ResearchPeer-reviewed·Mar 31, 2023