Ryan L. Collins

The paper identifies polygenic risk factors and rare variants in unexplained familial cancers using whole genome sequencing and family history data.

The paper evaluates how dataset characteristics affect biologically-informed neural network performance using simulations and empirical testing with prostate cancer data.

The paper identifies WAPL as a novel cohesinopathy gene and driver of a genomic disorder, showing its role in developmental delay and other anomalies through clinical, in vitro, and in vivo analyses.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

This study identifies tissue-specific cancer genes using a statistical framework applied to a large dataset, revealing that tissue specificity is common in cancer genes.

The paper investigates the functional role of recursive splicing in CADM2, showing that its deletion leads to altered gene expression and behavioral changes in neurodevelopmental disorders.

The paper identifies chr22q as a regulatory hub where genetic risk for neuropsychiatric conditions is associated with coordinated gene expression downregulation in brain tissue.

This study identifies rare germline structural variants as risk factors for pediatric solid tumors, particularly neuroblastoma, by analyzing genome sequencing data from affected children and controls.

This study identifies germline rare variants associated with clear and non-clear cell RCC, accounting for population stratification, and finds distinct risk patterns and somatic associations.

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

The paper develops a method to infer compound heterozygosity from exome sequencing data, achieving high accuracy in phasing rare variants for recessive disease diagnosis.

This study identifies molecular and functional changes in mouse and human models of 16p11.2 reciprocal genomic disorder, revealing context-specific disruptions in energy metabolism, RNA processing, and neuronal development.

GATK-gCNV detects rare copy number variants from exome sequencing data, achieving high recall in benchmarking and generating a reference catalog of rare coding CNVs in the UK Biobank.

This study identifies 3,154 high-confidence structural variants in Parkinson's disease using short-read sequencing and validates some with long-read data, highlighting limitations of short-read methods.

This study identifies 114 genome-wide significant rare CNV-disease associations across 30 neurological disorders, revealing 38 novel triplosensitive genes and developing a model to predict dosage sensitivity.

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 describes the role of the Centers for Mendelian Genomics in advancing gene discovery through data sharing, collaboration, and resource development over the past decade.

The paper uses the ABC Model to map enhancer-gene regulation across 131 cell types and tissues, linking GWAS variants to disease genes, particularly in IBD.

This study evaluates genome sequencing as a single diagnostic approach for fetal structural anomalies, showing it detects nearly all variants from standard tests and provides higher diagnostic yield than individual tests.

The paper compares structural variant detection using short-read and long-read sequencing in three trios, showing lrWGS finds more SVs but srWGS has high concordance in non-repetitive regions.

The paper functionally annotates rare structural variants in the human brain by integrating SV calling with RNA-seq data to assess their regulatory effects and prioritize pathogenic deletions.

The paper evaluates potential drug targets using loss-of-function genetic variants from gnomAD, highlighting the importance of deep curation and targeted recall studies for drug discovery.

From 125,748 exomes and 15,708 genomes, 443,769 high-confidence predicted loss-of-function variants yield LOEUF, a continuous gene intolerance score tracking mouse lethality, cell essentiality, and disease associations.

The paper develops an expression-based annotation metric to improve rare variant interpretation by filtering false-positive loss-of-function variants and identifying pathogenic variants in highly expressed exons.

Short-read genome sequencing of 14,891 diverse genomes yields 433,371 structural variants (SVs) for gnomAD; loss-constrained genes also resist duplication, and clinical SV carrier rates are benchmarked.

The paper analyzes loss-of-function variants in LRRK2 across large genomic datasets to assess the safety of partial LRRK2 inhibition as a Parkinson's disease therapy.

The paper systematically studies uORF variants in 15,708 genomes, showing they are under strong negative selection and contribute to disease.

The paper analyzes multi-nucleotide variants (MNVs) in 125,748 exomes and 15,708 genomes, identifying their distribution, mutational origins, and functional implications.

This study identifies a large number of structural variants in human genomes using multiple sequencing technologies and presents them as a gold standard for future studies.

This study examines the role of noncoding variation in autism spectrum disorder using whole genome sequencing of 2,076 genomes, finding no significant association after correction for multiple testing.