ArticleAmerican journal of human genetics2019
IMPACT: Genomic Annotation of Cell-State-Specific Regulatory Elements Inferred from the Epigenome of Bound Transcription Factors.
Article in American journal of human genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 70 citations in OpenAlex.
- Skeletal muscle eQTL meta-analysis implicates genes in the genetic architecture of muscular and cardiometabolic traits.American journal of human genetics · 2025Pooled it
- GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region.Nature communications · 2024Pooled it
- Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis.Nature genetics · 2022Pooled it
- Identifying independent causal cell types for human diseases and risk variants.Cell genomics · 2026Article
- Accurate, sensitive, and efficient chromatin accessibility quantification at target loci using UNIChro-seq.Nature communications · 2026Article
- Genetics of skeletal proportions across two different populations.American journal of human genetics · 2026Article
- Cross-Ancestry Polygenic Prediction: Comparing Methods and Assessing Transferability Across Traits.Genetic epidemiology · 2026Article
- Mixed-model and transcriptome-wide association analyses identify transcription factors and genes associated with colorectal cancer susceptibility.Nature communications · 2026Article
- Multi-ancestry genome-wide and transcriptome-wide association analyses identified new risk loci and genes for inflammatory bowel disease.medRxiv : the preprint server for health sciences · 2025Article
- Enhancing disease risk gene discovery by integrating transcription factor-linked trans-variants into transcriptome-wide association analyses.Nucleic acids research · 2025Article
- Powerful mapping ofmedRxiv : the preprint server for health sciences · 2024Article
- The regulation and differentiation of regulatory T cells and their dysfunction in autoimmune diseases.Nature reviews. Immunology · 2024Review
- A statistical approach for identifying single nucleotide variants that affect transcription factor binding.iScience · 2024Article
- The genetic basis of autoimmunity seen through the lens of T cell functional traits.Nature communications · 2024Review
- Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability.Nature genetics · 2023Article
- Modeling tissue co-regulation estimates tissue-specific contributions to disease.Nature genetics · 2023Article
- Article
- Blood cell traits' GWAS loci colocalization with variation in PU.1 genomic occupancy prioritizes causal noncoding regulatory variants.Cell genomics · 2023Article
- Colocalization of blood cell traits GWAS associations and variation in PU.1 genomic occupancy prioritizes causal noncoding regulatory variants.bioRxiv : the preprint server for biology · 2023Article
- Integrating transcription factor occupancy with transcriptome-wide association analysis identifies susceptibility genes in human cancers.Nature communications · 2022Article
Corrections and comments
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Authors and funding
13 authors at 7 institutions in 4 countries.
Funding
Abstract
Despite significant progress in annotating the genome with experimental methods, much of the regulatory noncoding genome remains poorly defined. Here we assert that regulatory elements may be characterized by leveraging local epigenomic signatures where specific transcription factors (TFs) are bound. To link these two features, we introduce IMPACT, a genome annotation strategy that identifies regulatory elements defined by cell-state-specific TF binding profiles, learned from 515 chromatin and sequence annotations. We validate IMPACT using multiple compelling applications. First, IMPACT distinguishes between bound and unbound TF motif sites with high accuracy (average AUPRC 0.81, SE 0.07; across 8 tested TFs) and outperforms state-of-the-art TF binding prediction methods, MocapG, MocapS, and Virtual ChIP-seq. Second, in eight tested cell types, RNA polymerase II IMPACT annotations capture more cis-eQTL variation than sequence-based annotations, such as promoters and TSS windows (25% average increase in enrichment). Third, integration with rheumatoid arthritis (RA) summary statistics from European (N = 38,242) and East Asian (N = 22,515) populations revealed that the top 5% of CD4
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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.