A5101807474- Genomic variations and chromosomal abnormalities
- Cancer Genomics and Diagnostics
- Genomics and Rare Diseases
- Autism Spectrum Disorder Research
- Health, Environment, Cognitive Aging
- Lipoproteins and Cardiovascular Health
- Molecular Biology Techniques and Applications
- Congenital heart defects research
- Williams Syndrome Research
- Genomics and Phylogenetic Studies
- Genetic Associations and Epidemiology
- Cardiac Valve Diseases and Treatments
Broad Institute
2017-2024
Background: Despite a proposed causal role for low-density lipoprotein cholesterol (LDL-C) in aortic stenosis (AS), randomized controlled trials of lipid-lowering therapy failed to prevent severe AS. We aimed assess the impact on AS and peak velocity across valve conferred by lifelong alterations LDL-C levels mediated protein-disrupting variants three clinically significant genes LDL metabolism ( LDLR , APOB PCSK9 ). Methods: utilized sequencing data electronic health records from UK Biobank...
ABSTRACT Individuals with autism spectrum disorder (ASD) or related neurodevelopmental disorders (NDDs) often carry disruptive mutations in genes that are depleted of functional variation the broader population. We build upon this observation and exome sequencing from 154,842 individuals to explore allelic diversity rare protein-coding contributing risk for ASD NDDs. Using an integrative statistical model, we jointly analyzed protein-truncating variants (PTVs), damaging missense variants,...
SUMMARY Copy number variants (CNVs) are major contributors to genetic diversity and disease. To date, exome sequencing (ES) has been generated for millions of individuals in international biobanks, human disease studies, clinical diagnostic screening. While standardized methods exist detecting short (single nucleotide insertion/deletion variants) using tools such as the Genome Analysis ToolKit (GATK), technical challenges have confounded similarly uniform large-scale CNV analyses from ES...
Abstract We propose, implement, and evaluate a novel method (GATK gCNV) for accurate discovery of rare common copy-number variations (CNVs) from read-depth data obtained whole genome sequencing (WGS), exome (WES), or custom gene panels. GATK gCNV utilizes sophisticated Bayesian model to learn bias factors arising library preparation. This accounts ploidy sex chromosomes autosomal aneuploidies, treats GC probabilistically, automatically determines the necessary level complexity in data-driven...
Abstract We propose and evaluate a novel algorithm for inferring germline somatic copy number variation from whole exome sequencing (WES) genome (WGS) data. Starting with the depth of aligned short reads cohort samples, we use Bayesian model learning bias simultaneously detecting CNV events using hidden Markov change-point detection. A unified framework is used to call both CNVs. Denoising event discovery are performed self-consistently achieve maximum accuracy. In contrast previous methods,...
Abstract The presence of somatic copy-number alterations in tumor genomes can be used to predict both patient sensitivity treatments as well outcomes. inclusion allelic data improves statistical power detect events and allows for discovery copy-neutral events. We present GATK ACNV, an variation method built on the Genome Analysis Toolkit. ACNV is a tool detecting activity from whole exome genome sequencing by segmenting into regions constant copy number estimating ratio minor-allele fraction...