Genomic variations and chromosomal abnormalities

The paper introduces iCNV, a statistical framework for detecting and genotyping DNA copy number variations from sequencing and array data, improving sensitivity and accuracy.

The paper identifies dup19q13.33 as a novel syndrome locus associated with neurodevelopmental disorders and highlights four candidate genes for further study.

The paper analyzes copy number variations in 100 twin pairs enriched for neurodevelopmental disorders, finding no postzygotic de novo CNVs but higher rates of CNVs overlapping nervous system genes in discordant pairs.

The paper identifies a mitochondrial transporter interactome disruption in 22q11.2 syndrome, linking it to synapse function and behavior.

SV2 is a machine-learning algorithm that improves structural variant genotyping and detects de novo mutations from paired-end sequencing data.

The paper introduces a pipeline to analyze complex local DNA mutations using long-read sequencing and presents a catalog of rearrangements in a human cell line.

OMSV identifies large structural variations from optical maps with high accuracy, outperforming existing methods and detecting many missed by sequencing.

GRIDSS detects genomic rearrangements with high sensitivity and specificity using a positional de Bruijn graph assembler, outperforming existing methods on simulated and tumor data.

This study investigates the association between copy number variants on chromosome 21 and congenital heart defects in Down syndrome, finding no direct link but suggesting ethnic differences in CNV patterns.

The paper presents an algorithm to reconstruct cancer karyotypes from short read data using graph theory and integer linear programming, showing it can correctly infer a large portion of karyotypes even with noisy data.

The paper introduces NAIBR, a method for identifying structural variants from linked-read sequencing data, showing improved performance over existing methods.

This study uses nanopore sequencing to detect and phase structural variants in patient genomes, identifying novel variants missed by short-read sequencing.

This paper develops tools to identify copy number variations and translocations in cancer cells using Hi-C data, finding 105 amplifications, 45 deletions, and 90 translocations in cancer cell lines.

Canvas SPW identifies inherited and de novo copy number variants in pedigree sequencing data by supporting various family structures and providing automated scoring and filtering options.

VaPoR validates structural variations using long-read sequencing data with high accuracy and efficiency, outperforming manual methods.

The paper introduces a tiered prioritisation approach to identify high-impact gene fusions in cancer genomes by improving variant annotation, interpretation, and visualisation.

The paper investigates how structural variations in yeast genomes affect gene expression and quantitative traits, finding that copy number variants significantly influence phenotypes and reproductive isolation.

This paper validates the analytical and clinical utility of FirstStepDx PLUS, a chromosomal microarray optimized for neurodevelopmental conditions, showing its effectiveness in detecting copy number variants using buccal and blood samples.

The paper reports a family with a 15q11.2 BP1-BP2 duplication showing variable phenotypes, suggesting gene expression level changes may affect cognitive development.