Evidence map›Paper›PMID 37196000›Full record

ArticlePloS one2023

Phenopacket-tools: Building and validating GA4GH Phenopackets.

Daniel Danis, Julius O B Jacobsen, Alex H Wagner, Tudor Groza, Martha A Beckwith, Lauren Rekerle, Leigh C Carmody, Justin Reese, Harshad Hegde, Markus S Ladewig and 8 more

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
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  4. Review
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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.

Daniel DanisThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States of America.ORCID 0000-0003-0900-3411
Julius O B JacobsenWilliam Harvey Research Institute, Queen Mary University of London, London, United Kingdom.ORCID 0000-0002-3265-1591
Alex H WagnerDepartments of Pediatrics and Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, United States of America.
Tudor GrozaEMBL-EBI, Cambridge, United Kingdom.
Martha A BeckwithThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States of America.
Lauren RekerleThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States of America.ORCID 0000-0003-2598-6622
Leigh C CarmodyThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States of America.
Justin ReeseEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America.ORCID 0000-0002-2170-2250
Harshad HegdeEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America.
Markus S LadewigDepartment of Ophthalmology, Klinikum Saarbrücken, Saarbrücken, Germany.ORCID 0000-0002-6601-4486
Berthold SeitzDepartment of Ophthalmology, Saarland University Medical Center, Homburg/Saar, Germany.
Monica Munoz-TorresDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America.
Nomi L HarrisEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America.
Jordi RamblaEuropean Genome-Phenome Archive (EGA) in the Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
Michael BaudisUniversity of Zurich and Swiss Institute of Bioinformatics, Zurich, Switzerland.
Christopher J MungallEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America.
Melissa A HaendelDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America.
Peter N RobinsonThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States of America.ORCID 0000-0002-0736-9199

Funding

The Monarch Initiative: Linking Diseases to Model Organism ResourcesR24OD011883 · OD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HAENDEL, MELISSA A, MUNGALL, CHRISTOPHER J · 2012 to 2024
$16.0M
Improvements to the LinkML framework to support the Phenomics First open science resourceRM1HG010860 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HAENDEL, MELISSA A, MUNGALL, CHRISTOPHER J · 2020 to 2024
$10.3M
Real-time genetic diagnosis at the point of careR01HG011799 · NHGRI · GEISINGER CLINIC · PI WILLIAMS, MARC S. · 2021 to 2025
$4.6M
Increasing the Yield and Utility of Pediatric Genomic Medicine with ExomiserR01HD103805 · NICHD · JACKSON LABORATORY · PI Valentina Cipriani, CHRISTOPHER J MUNGALL · 2021 to 2026
$4.3M
Development and validation of a computable knowledge framework for genomic medicineR35HG011949 · NHGRI · RESEARCH INST NATIONWIDE CHILDREN'S HOSP · PI WAGNER, ALEX HANDLER · 2021 to 2025
$2.4M
Medical Research Council MC_PC_19024NHGRI NIH HHS R01 HG011799NHGRI NIH HHS R35 HG011949NHGRI NIH HHS RM1 HG010860NICHD NIH HHS R01 HD103805NIH HHS R24 OD011883
6 · The paper itself

Abstract

The Global Alliance for Genomics and Health (GA4GH) is a standards-setting organization that is developing a suite of coordinated standards for genomics. The GA4GH Phenopacket Schema is a standard for sharing disease and phenotype information that characterizes an individual person or biosample. The Phenopacket Schema is flexible and can represent clinical data for any kind of human disease including rare disease, complex disease, and cancer. It also allows consortia or databases to apply additional constraints to ensure uniform data collection for specific goals. We present phenopacket-tools, an open-source Java library and command-line application for construction, conversion, and validation of phenopackets. Phenopacket-tools simplifies construction of phenopackets by providing concise builders, programmatic shortcuts, and predefined building blocks (ontology classes) for concepts such as anatomical organs, age of onset, biospecimen type, and clinical modifiers. Phenopacket-tools can be used to validate the syntax and semantics of phenopackets as well as to assess adherence to additional user-defined requirements. The documentation includes examples showing how to use the Java library and the command-line tool to create and validate phenopackets. We demonstrate how to create, convert, and validate phenopackets using the library or the command-line application. Source code, API documentation, comprehensive user guide and a tutorial can be found at https://github.com/phenopackets/phenopacket-tools. The library can be installed from the public Maven Central artifact repository and the application is available as a standalone archive. The phenopacket-tools library helps developers implement and standardize the collection and exchange of phenotypic and other clinical data for use in phenotype-driven genomic diagnostics, translational research, and precision medicine applications.

Indexed as

NeoplasmsSoftwareDatabases, FactualGene LibraryGenomicsHumans

Identifiers

PMID37196000
PMCPMC10191354

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.