ArticleProceedings of the National Academy of Sciences of the United States of America2020
A method for scoring the cell type-specific impacts of noncoding variants in personal genomes.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 22 citations in OpenAlex.
- Modeling combinatorial regulation from single-cell multi-omics provides regulatory units underpinning cell type landscape using cRegulon.Genome biology · 2025Article
- Longitudinal analysis of epigenome-wide DNA methylation reveals novel loci associated with BMI change in East Asians.Clinical epigenetics · 2024Article
- Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.Nature genetics · 2024Article
- Protocol for using GRPath to identify putative gene regulation paths in complex human diseases.STAR protocols · 2022Article
- Article
- DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.Bioinformatics (Oxford, England) · 2022Article
- Scalable approaches for functional analyses of whole-genome sequencing non-coding variants.Human molecular genetics · 2022Review
- Unfolding the genotype-to-phenotype black box of cardiovascular diseases through cross-scale modeling.iScience · 2022Article
- Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Openness weighted association studies: leveraging personal genome information to prioritize non-coding variants.Bioinformatics (Oxford, England) · 2021Article
- DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers.Genomics, proteomics & bioinformatics · 2021Article
- OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions.Nucleic acids research · 2021Article
- Modeling regulatory network topology improves genome-wide analyses of complex human traits.Nature communications · 2021Article
- hReg-CNCC reconstructs a regulatory network in human cranial neural crest cells and annotates variants in a developmental context.Communications biology · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
A person's genome typically contains millions of variants which represent the differences between this personal genome and the reference human genome. The interpretation of these variants, i.e., the assessment of their potential impact on a person's phenotype, is currently of great interest in human genetics and medicine. We have developed a prioritization tool called OpenCausal which takes as inputs 1) a personal genome and 2) a reference context-specific TF expression profile and returns a list of noncoding variants prioritized according to their impact on chromatin accessibility for any given genomic region of interest. We applied OpenCausal to 6,430 samples across 18 tissues derived from the GTEx project and found that the variants prioritized by OpenCausal are highly enriched for eQTLs and caQTLs. We further propose a strategy to integrate the predicted open scores with genome-wide association studies (GWAS) data to prioritize putative causal variants and regulatory elements for a given risk locus (i.e., fine-mapping analysis). As an initial example, we applied this method to a GWAS dataset of human height and found that the prioritized putative variants and elements are correlated with the phenotype (i.e., heights of individuals) better than others.
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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.