Julius O.B. Jacobsen

A Phenotypic Paradigm for Cerebral Palsy Genetics

The paper identifies pathogenic variants in 15.8% of CP patients and finds only 16 of 60 genes have significant CP association.

Blood-based RNA-Seq of 5412 individuals with rare disease identifies new candidate diagnoses in the National Genomic Research Library

The paper uses blood-based RNA-Seq on 5,412 individuals with rare diseases to identify new candidate diagnoses and shows its utility in prioritizing genetic variants.

GA4GH Phenopacket-Driven Characterization of Genotype-Phenotype Correlations in Mendelian Disorders

The paper introduces GPSEA, a tool using GA4GH Phenopackets to analyze genotype-phenotype correlations in Mendelian disorders, identifying 225 significant associations across 85 cohorts.

Towards a standard benchmark for phenotype-driven variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework

PhEval provides a standardized framework to benchmark phenotype-driven variant and gene prioritisation algorithms using real-world patient data and controlled test corpora.

The Unified Phenotype Ontology (uPheno): A framework for cross-species integrative phenomics

The paper introduces uPheno, a framework for cross-species phenomics integration by harmonizing phenotype data across species and ontologies.

A corpus of GA4GH Phenopackets: case-level phenotyping for genomic diagnostics and discovery

The paper presents a large-scale corpus of standardized phenopackets for genomic diagnostics and discovery, curated from literature and useful for software testing and genotype-phenotype analysis.

Critical assessment of variant prioritization methods for rare disease diagnosis within the Rare Genomes Project

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

Rare disease gene association discovery from burden analysis of the 100,000 Genomes Project data

The paper identifies 88 novel rare disease-gene associations using a burden analysis framework on whole genome sequencing data from the 100,000 Genomes Project, with potential clinical impact for undiagnosed cases.

The GA4GH Phenopacket schema: A computable representation of clinical data for precision medicine

The paper introduces the GA4GH Phenopacket schema to standardize the exchange of phenotypic data for precision medicine applications.

Interpretable prioritization of splice variants in diagnostic next-generation sequencing

SQUIRLS prioritizes splice variants by calculating interpretable features and achieving higher accuracy and speed than existing methods in simulated exomes.

SvAnna: efficient and accurate pathogenicity prediction for coding and regulatory structural variants in long-read genome sequencing

SvAnna predicts pathogenicity of structural variants in long-read sequencing data by integrating transcript and regulatory annotations with clinical phenotype data, achieving high accuracy in prioritizing pathogenic variants.

Interpretable Clinical Genomics with a Likelihood Ratio Paradigm

The paper introduces LIRICAL, a likelihood ratio-based framework for genomic diagnostics that improves accuracy and interpretability in phenotype-driven rare disease diagnosis.

Phenopolis: an open platform for harmonization and analysis of sequencing and phenotype data

Phenopolis provides an open platform for integrating and analyzing sequencing and phenotype data to aid in clinical diagnosis and gene discovery.

The Monarch Initiative: Insights across species reveal human disease mechanisms

The paper describes the Monarch Initiative, a platform that integrates multimodal data across species to enhance genotype-phenotype analysis and precision medicine.