In one paragraphArticle in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
32 authors.
Daniel DanisThe Jackson Institute for Genomic Medicine, 10 Discovery Drive, Farmington CT 06032, USA.
Michael J BamshadDepartment of Pediatrics, Division of Genetic Medicine, University of Washington, 1959 NE Pacific Street, Box 357371, Seattle, WA 98195, USA.ORCID 0000-0002-6025-0015 Leigh C CarmodyThe Jackson Institute for Genomic Medicine, 10 Discovery Drive, Farmington CT 06032, USA.ORCID 0000-0001-7941-2961 Jessica X ChongDepartment of Pediatrics, Division of Genetic Medicine, University of Washington, 1959 NE Pacific Street, Box 357371, Seattle, WA 98195, USA.ORCID 0000-0002-1616-2448 Ben ColemanDepartment of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA.ORCID 0000-0002-4422-1708 Peter J FreemanDivision of Informatics, Imaging and Data Science, The University of Manchester, Manchester, UK.ORCID 0000-0002-5838-5404 Adam KlocperkDepartment of Immunology, 2nd Faculty of Medicine, Charles University and University Hospital in Motol, Prague, Czech Republic.ORCID 0000-0002-1526-4557 Maaike KustersDepartment of Paediatric Immunology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.ORCID 0000-0001-7601-9822 Markus S LadewigDepartment of Ophthalmology, University Clinic Marburg - Campus Fulda, Fulda, Germany.ORCID 0000-0002-6601-4486 Anthony J MarcelloDepartment of Pediatrics, Division of Genetic Medicine, University of Washington, 1959 NE Pacific Street, Box 357371, Seattle, WA 98195, USA.
Christopher J MungallDivision of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID 0000-0002-6601-2165 Monica C Munoz-TorresDepartment of Biomedical Informatics, University of Colorado Anschutz Medical Ccampus.ORCID 0000-0001-8430-6039 Justin T ReeseDivision of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID 0000-0002-2170-2250 Bárbara C S ReisDepartment of Immunology, National Institute of Women's, Children's and Adolescents' Health Fernandes Figueira, Rio de Janeiro, Brazil.ORCID 0000-0001-9725-9665 Catharina SchuetzDepartment of Pediatrics, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Timmy StraussDepartment of Pediatrics, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0001-9969-9517 Jagadish Chandrabose SundaramurthiThe Jackson Institute for Genomic Medicine, 10 Discovery Drive, Farmington CT 06032, USA.ORCID 0000-0002-6670-9157 Kyran WissinkBerlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
David ZoccheNorth West Thames Regional Genetics Service, Northwick Park & St Mark's Hospitals, London, UK.ORCID 0000-0003-1390-0334 Peter N RobinsonBerlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0002-0736-9199 Funding
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
$10.3MThe Human Phenotype Ontology: Accelerating Computational Integration of Clinical Data for GenomicsU24HG011449 · NHGRI · JACKSON LABORATORY · PI Peter Nicholas Robinson · 2021 to 2026
$6.7MIncreasing the Yield and Utility of Pediatric Genomic Medicine with ExomiserR01HD103805 · NICHD · JACKSON LABORATORY · PI Valentina Cipriani, CHRISTOPHER J MUNGALL · 2021 to 2026
$4.3MNHGRI NIH HHS RM1 HG010860NHGRI NIH HHS U24 HG011449NICHD NIH HHS R01 HD103805
6 · The paper itselfAbstract
The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present phenopacket-store. Version 0.1.12 of phenopacket-store includes 4916 phenopackets representing 277 Mendelian and chromosomal diseases associated with 236 genes, and 2872 unique pathogenic alleles curated from 605 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.
Identifiers
PMID38854034
PMCPMC11160806
What OpenQuestion holds
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LicenceCC BY
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