Evidence map›Paper›PMID 42108472›Full record

ArticleGenome biology2026

Designing genome editing experiments with EditABLE.

Demetrios S Maxim, Juliet Sostena, Najani Shanee Johnson, David Wei Wu, Vivek Charu, Jennefer N Carter, Shuchi Anand, George M Church, Vivek Bhalla

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Demetrios S MaximDivision of Nephrology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Juliet SostenaNephrogen Inc., New York, NY, USA.
Najani Shanee JohnsonNephrogen Inc., New York, NY, USA.
David Wei WuMedical Scientist Training Program, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Vivek CharuDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Jennefer N CarterDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Shuchi AnandDivision of Nephrology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
George M ChurchNephrogen Inc., New York, NY, USA.
Vivek BhallaDivision of Nephrology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA. vbhalla@stanford.edu.

Funding

NIDDK NIH HHS 1R41DK138689
6 · The paper itself

Abstract

While many computational tools exist for designing CRISPR-Cas experiments, there is a need for a centralized resource that combines individual tools to predict the most efficient genome editing strategy for a given application. To fill this gap, we develop EditABLE (EditABLE-app.stanford.edu), an online resource that provides optimal CRISPR editors and guide RNAs based on user provided sequence data with functionalities for base editing, prime editing, and integrase-mediated editing. We demonstrate the utility of EditABLE by applying it to one of the most common monogenic disorders, autosomal dominant polycystic kidney disease (ADPKD), identifying specific editing tools across the ADPKD mutation landscape.

Indexed as

CRISPR-Cas SystemsGene EditingSoftwareHumansPolycystic Kidney, Autosomal DominantRNA, Guide, CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas SystemsCRISPR–CasGene therapyGenome editingKidney disease

Identifiers

PMID42108472
PMCPMC13330345

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.