Genomics and Rare Diseases

CADD-SV scores structural variants using annotations and random forest models, correlating with known pathogenic and non-coding variants affecting gene expression.

The paper describes the RYR1 variant landscape in a Singapore cohort using whole genome sequencing, identifying pathogenic variants and their allele frequencies across ethnic groups.

The paper describes the process of obtaining an FDA IDE for returning genomic results via WGS in the All of Us Research Program and presents validation results.

The paper develops a machine learning classifier to distinguish ALS-causative from non-ALS-causative variants with high accuracy using nine key mutation assessors.

The paper shows inherited CHD3 variants cause Snijders Blok-Campeau syndrome with variable expressivity, overlapping with de novo variants' phenotypes, and suggests reduced penetrance is not due to expression compensation.

CNV-ClinViewer provides a web tool for clinical interpretation of large copy-number variants by integrating patient and population data with biomedical annotations.

The paper functionally validates a de novo PPP5C variant in a human proband using C. elegans, showing it causes loss-of-function and is likely responsible for the patient's phenotypes.

The paper evaluates unanticipated monogenic disease risks found in newborns through genomic screening, finding most risks are actionable and lead to medical interventions.

Genome Alert! automatically detects changes in variant classifications and gene-disease associations over time, improving clinical interpretation of genomic data with minimal human effort.

This paper introduces a framework to identify rare variant combinations in complex disorders by combining the apriori algorithm with statistical inference, revealing significant associations with phenotypes like ID and schizophrenia.

The paper presents diagnostic analyses of 960 pediatric rare disease families using genomic sequencing and machine learning, finding higher diagnostic rates with long-read sequencing and highlighting challenges in variant interpretation.

The paper examines the relationship between contiguous hydrophobic sequences and functional impact of SNPs, finding strong correlations with disease association and selective constraint.

The paper updates the Regulatory Mendelian Mutation score for GRCh38 and provides a website and API for variant scoring.

seqr is a web-based tool for analyzing rare disease genomic data, enabling variant filtering, annotation, and collaboration, with over 10,000 families analyzed and 300 novel disease genes discovered.

Variomes is a system that curates genomic variants by searching literature and prioritizing clinically actionable variants based on publication volume.

The paper highlights the importance of Middle Eastern genetic variation in improving clinical genome annotation and variant interpretation by presenting a new database with unique variants not found in existing resources.

The paper investigates the functional consequences of SLC6A1 variants, finding haploinsufficiency underlies neurodevelopmental phenotypes and identifying missense residues sensitive to substitution.

The paper evaluates 24 computational methods for predicting non-coding variant function and pathogenicity across four benchmark datasets, finding varying performance across different variant types.

The paper uses missense variant depletion patterns to identify functional sites in ARID family proteins and reveals sub-functionalization through domain-level comparisons.

TADA prioritizes pathogenic CNVs using functional annotations and machine learning, achieving high AUC scores for deletions and duplications.

The paper presents a pipeline to call mitochondrial DNA variants in gnomAD, reporting population frequencies for 10,850 unique mtDNA variants across 56,434 individuals.

The paper uses duplex sequencing to analyze de novo mutations in sperm DNA from older and younger donors, finding higher mutation frequencies and recurrence in older donors.

ModelMatcher connects researchers, clinicians, and stakeholders in rare disease research to accelerate translational studies and collaborations.

PANCO reclassifies variants of uncertain significance in non-coding regions with high accuracy using integrated functional and evolutionary data.

The paper characterizes Arabian Peninsula whole exomes, identifying high inbreeding features and a high burden of potentially deleterious variants.

Vasor is a machine learning model that accurately predicts the pathogenicity of MDR3 missense variants, outperforming existing tools and providing a webserver for predictions.

GeneTerpret streamlines genomic variant interpretation by integrating multiple data sources and ACMG criteria to prioritize potentially causal variants for a given genome and phenotype.

This paper introduces HMC, a high-resolution genetic constraint score for missense variants, improving variant prioritization and gene discovery for developmental disorders.

GREEN-DB annotates and prioritizes non-coding regulatory variants from whole-genome sequencing data by integrating regulatory annotations, constraint metrics, and variant impact scores.

GestaltMatcher improves diagnosis of ultra-rare genetic disorders by matching facial phenotypes to molecular diagnoses using a deep learning model trained on a large dataset of patient photographs.