Evidence map›Paper›PMID 37719152›Full record

ArticleCell genomics2023

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox.

Sjors Middelkamp, Freek Manders, Flavia Peci, Markus J van Roosmalen, Diego Montiel González, Eline J M Bertrums, Inge van der Werf, Lucca L M Derks, Niels M Groenen, Mark Verheul and 8 more

Abstract read
In one paragraph

Article in Cell genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  13. Mitochondrial HNature communications · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Sjors MiddelkampPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Freek MandersPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Flavia PeciPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Markus J van RoosmalenPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Diego Montiel GonzálezPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Eline J M BertrumsPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Inge van der WerfPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Lucca L M DerksPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Niels M GroenenPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Mark VerheulPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Laurianne TrabutPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Cayetano Pleguezuelos-ManzanoOncode Institute, Utrecht, the Netherlands.
Arianne M BrandsmaPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Evangelia AntoniouDepartment of Pediatric Hematology and Oncology, University Hospital Essen, Essen, Germany.
Dirk ReinhardtDepartment of Pediatric Hematology and Oncology, University Hospital Essen, Essen, Germany.
Marc BieringsPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Mirjam E BelderbosPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Ruben van BoxtelPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

Indexed as

cancerFanconi anemiahematopoietic stem cellsmutational signaturesprimary template-directed amplificationsingle-cell sequencingsomatic mutationsstructural variantswhole-genome amplificationwhole-genome sequencing

Identifiers

PMID37719152
PMCPMC10504672

What OpenQuestion holds

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LicenceCC BY
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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.