Evidence map›Paper›PMID 42624993›Full record

ArticleNature biomedical engineering2026

Analysing long-read CRISPR experiments with CRISPRLungo.

Gue-Ho Hwang, Benjamin Vyshedskiy, Timothy Barry, Jing Zeng, Sébastien Levesque, John P Manis, Akiko Shimamura, Daniel E Bauer, Luca Pinello

Abstract read
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In one paragraph

Article in Nature biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Gue-Ho HwangMolecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4201-0974
Benjamin VyshedskiyMolecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
Timothy BarryMolecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
Jing ZengDivision of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA.
Sébastien LevesqueDivision of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA.
John P ManisDepartment of Pathology, Harvard Medical School, Boston, MA, USA.
Akiko ShimamuraDivision of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4683-9958
Daniel E BauerDivision of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA. Daniel.Bauer@childrens.harvard.edu.ORCID http://orcid.org/0000-0001-5076-7945
Luca PinelloMolecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA. lpinello@mgh.harvard.edu.ORCID http://orcid.org/0000-0003-1109-3823

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-read sequencing can characterize complex genome editing-induced DNA sequence changes such as large deletions, insertions and inversions that are difficult to detect using short-read sequencing. However, PCR amplification and sequencing errors complicate accurate variant detection, and existing analysis tools are not optimized for gene editing specific allelic outcomes. Here we present CRISPRLungo, a computational pipeline specifically designed for long-read amplicon sequencing of gene edited samples. CRISPRLungo incorporates unique molecular identifier-based error correction and statistical filtering to distinguish true editing events from background noise, enabling robust detection of small indels and structural variants. Through systematic benchmarking using simulated datasets, we demonstrate that CRISPRLungo outperforms existing approaches in both accuracy and read recovery. CRISPRLungo supports both Oxford Nanopore and PacBio platforms and identifies previously undetected structural variant edits such as inversions in published CRISPR datasets. To demonstrate allele-specific edit quantification, we applied CRISPRLungo to analyse edited primary cells from a patient harbouring compound heterozygous SBDS mutations, accurately quantifying SBDS editing outcomes despite contaminating reads from the homologous SBDSP1 pseudogene. To maximize accessibility, we developed a fully client-side web application requiring no installation, making advanced long-read analysis accessible to researchers regardless of computational expertise. CRISPRLungo is freely available at https://github.com/pinellolab/CRISPRLungo with a user-friendly web interface available at https://pinellolab.github.io/CRISPRLungo .

Identifiers

What OpenQuestion holds

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Registered trials

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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.