Genomic variations and chromosomal abnormalities

SVIM detects and characterizes structural variants from long-read sequencing data, outperforming existing tools on simulated and real datasets.

This study investigates the association between rare copy number variants (CNVs) and neurodevelopmental problems (NPs) in children, finding sex-specific effects in anxiety/depression.

The paper investigates 17p13.3 deletions between YWHAE/CRK and PAFAH1B1, identifying white matter lesions and hypermobility, and narrows the critical region to 345 kb with RTN4RL1 as a candidate gene.

The paper investigates how large genomic deletions affect chromatin interactions and states in human brain development using Hi-C and ChIP-Seq analyses.

The paper identifies complex structural variants in Mendelian disorders using short-read and long-read sequencing, showing their clinical significance and the utility of long-read technology for resolution.

The paper investigates the effects of pathogenic CNVs on physical traits in UK Biobank adults, finding 214 significant associations with traits like weight and body fat.

CODEX2 improves CNV detection sensitivity and reduces false discoveries in whole-exome and targeted sequencing data.

The paper introduces CrowdVariant, a crowdsourcing framework to classify copy number variants (CNVs) using NGS data, and identifies 1,781 high-confidence CNVs in a reference sample.

This study examines the medical consequences of pathogenic CNVs in adults using UK Biobank data, finding significant associations between CNVs and various health outcomes.

Ximmer improves CNV calling accuracy and consistency from exome data through systematic quality control, parameter adjustment, and confidence calibration.

The paper shows that rare secondary mutations in functionally intolerant genes affect the expressivity of neurodevelopmental disorders in individuals with primary mutations.

This paper presents an integrative framework to detect structural variants in cancer genomes using multiple methods and finds that non-coding structural variation significantly impacts genome function in cancer cells.

The paper uses long-read sequencing to analyze structural variations in the SK-BR-3 breast cancer cell line, revealing complex rearrangements and novel gene fusions.

The paper develops MDTS, a method for detecting de novo copy number deletions in parent-offspring trios from targeted sequencing, achieving higher precision and scalability than existing tools.

The paper compares low-coverage whole-genome sequencing strategies to array-based methods for detecting copy number variations, finding WGS more efficient and accurate.

This study validates large-scale structural variations detected by optical mapping in subterranean clover using Illumina short reads, showing BOM detects total SV sizes but lacks precision in location and quantity.

GtTR is a Bayesian method for estimating absolute tandem repeat copy numbers using targeted sequencing and reference data, achieving high accuracy in population-scale genotyping.

npInv detects and genotypes NAHR inversions using long read sub-alignment, identifying 30 inversions in NA12878 with 94% accuracy, including 15 novel ones.

MAD-seq detects low-level mosaic chromosomal aneuploidy using a new sequencing assay and analysis method, revealing previously unrecognized aneuploidy in public datasets.

SVEngine simulates genome structural variations with cancer clonal evolution features, producing sequence data with variants and ground truth BED files.

The paper identifies genetic interactions within the 16p11.2 deletion that modulate neurodevelopmental phenotypes in Drosophila and links these interactions to human brain networks.

The paper identifies recurrent copy number variants in low-mappability regions using PopSV, finding they are 5 times more common in germline than somatic CNVs.

SV-plaudit enables rapid manual curation of thousands of structural variants through a cloud-based framework with image visualization and collaborative reporting.

NextSV is a meta-caller for structural variants from low-coverage long-read sequencing data, providing sensitive and stringent call sets with balanced performance.

The paper uses whole genome optical mapping to reveal complex chained fusion events and novel sequences in cancer genomes that are not detected by short-read sequencing.

This study uses nanopore sequencing to identify structural variants in breast cancer with high specificity and sensitivity, revealing repetitive DNA as a major source of variation.

The paper introduces open-source tools for detecting structural variations using long-read sequencing, achieving high sensitivity and precision in complex regions and identifying novel variants in human genomes.

This study uses whole-genome sequencing and a new algorithm to comprehensively characterize copy number variants in epilepsy patients and controls, finding enrichment of rare exonic and non-coding variants.

SvABA detects structural variants and indels using genome-wide local assembly, showing improved sensitivity and specificity, especially for small variants and complex rearrangements in cancer genomes.

The paper introduces MEM, a method to identify deletion CNVs in WES and WGS trio data by clustering Mendelian errors, achieving high validation rates and detecting additional de novo deletions and contamination.