ArticleNature genetics2024
Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification.
Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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
26 citing papers in PubMed, 30 citations in OpenAlex.
- Article
- Deciphering protein mutation-phenotype linkages from CRISPR-based tiling mutagenesis screens.Cell systems · 2026Article
- From text to translation: using language models to prioritize variants for clinical review.Genome medicine · 2026Article
- Interpretation, extrapolation and perturbation of single cells.Nature reviews. Genetics · 2026Review
- Language models reveal evidence gaps in variants of uncertain significance.medRxiv : the preprint server for health sciences · 2026Article
- A proteome-wide dependency map of protein interaction motifs.Nature structural & molecular biology · 2026Article
- Article
- The functional landscape of coding variation in the familial hypercholesterolemia geneScience (New York, N.Y.) · 2026Article
- Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.Diabetologia · 2026Review
- Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace.Genome biology · 2026Article
- Scaling perturbations: beyond genome-scale CRISPR screens.bioRxiv : the preprint server for biology · 2026Article
- LDLR variant classification through activity-normalized prime editing screening.bioRxiv : the preprint server for biology · 2025Article
- Endogenous fine-mapping and prioritization of functional regulatory elements in complex genetic loci.Cell genomics · 2025Article
- A functional map of CDK-drug interactions at single amino acid resolution.bioRxiv : the preprint server for biology · 2025Article
- Article
- Extracting and calibrating evidence of variant pathogenicity from population biobank data.American journal of human genetics · 2025Article
- Genetic mechanisms of resistance to targeted KRAS inhibition.bioRxiv : the preprint server for biology · 2025Article
- CRISPR-BEasy: a free web-based service for designing sgRNA tiling libraries for CRISPR-dependent base editing screens.Nucleic acids research · 2025Article
- Article
- Selict-seq profiles genome-wide off-target effects in adenosine base editing.Nucleic acids research · 2025Article
Corrections and comments
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Authors and funding
17 authors at 5 institutions in 4 countries.
Funding
Abstract
CRISPR base editing screens enable analysis of disease-associated variants at scale; however, variable efficiency and precision confounds the assessment of variant-induced phenotypes. Here, we provide an integrated experimental and computational pipeline that improves estimation of variant effects in base editing screens. We use a reporter construct to measure guide RNA (gRNA) editing outcomes alongside their phenotypic consequences and introduce base editor screen analysis with activity normalization (BEAN), a Bayesian network that uses per-guide editing outcomes provided by the reporter and target site chromatin accessibility to estimate variant impacts. BEAN outperforms existing tools in variant effect quantification. We use BEAN to pinpoint common regulatory variants that alter low-density lipoprotein (LDL) uptake, implicating previously unreported genes. Additionally, through saturation base editing of LDLR, we accurately quantify missense variant pathogenicity that is consistent with measurements in UK Biobank patients and identify underlying structural mechanisms. This work provides a widely applicable approach to improve the power of base editing screens for disease-associated variant characterization.
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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.