Genomic variations and chromosomal abnormalities

The paper investigates the role of mosaic copy number variants (mCNVs) in autism spectrum disorder (ASD) by analyzing genetic data from ASD probands and unaffected siblings, finding a significant association between large mCNVs and ASD risk.

Aquila_stLFR is a tool for diploid genome assembly and structural variant calling using stLFR linked-read data, achieving high sensitivity for deletions and specificity for insertions.

The paper analyzes allelic imbalance across 33 tumor types using haplotype-based methods on TCGA data, finding high prevalence of AI and recurrent chromosomal aberrations.

SVIM-asm detects and genotypes six classes of structural variants from haploid and diploid genome assemblies, outperforming existing tools in sensitivity and F1 scores for insertions and deletions.

SCCNV identifies copy number variations from single-cell whole-genome sequencing data by adjusting for amplification bias.

This study evaluates CNV detection performance of DNBSEQ and Illumina platforms using WGS data from NA12878, showing DNBSEQ detects more CNVs with similar sensitivity and precision.

The paper investigates why short-read variant callers fail to detect many insertions by analyzing callsets from long-read technologies and simulating the impact of insertion features on recall.

CamCNV improves detection of rare CNVs from Illumina arrays by using z-score segmentation, achieving 85% sensitivity for deletions and 65% for duplications with reliable false discovery rate control.

The paper identifies 47 high-confidence ASD-associated CNV regions and shows brain-enriched coding and lncRNA genes are overrepresented in these regions.

The paper identifies a chromosomal duplication of chromosome 1q in a subset of polymicrogyria patients, associated with specific clinical features and distinct DNA methylation patterns.

This study investigates electrophysiological network changes in adults with neurodevelopmental risk copy number variants using MEG, finding decreased connectivity and network segregation differences.

The paper estimates the effect sizes of deletions and duplications on autism risk and IQ using statistical models applied to CNV data from multiple cohorts.

This paper develops a Bayesian method to detect copy number variants and assess their association with disease in large-scale studies, finding deletions near MYC and TUSC3 linked to pancreatic cancer.

This study uses long-read sequencing to identify structural variants in breast cancer genomes, showing high accuracy and sensitivity compared to short-read methods.

The paper reports on a girl with a 1q42.3q43 duplication, describing her severe speech and language impairments and identifying potential candidate genes.

This paper introduces LDcnv, a novel algorithm that improves copy number variation detection by integrating genomic correlation structure, showing higher accuracy and precision than existing methods.

cuteSV improves structural variation detection in long-read sequencing by combining signature-based methods with clustering and refinement, achieving better performance on real datasets.

This paper introduces a method to fully characterize complex germline rearrangements using long DNA reads, demonstrating its ability to reconstruct intricate chromosomal translocations.

sideRETRO identifies and genotypes somatic and dimorphic retroCNVs from whole-genome or whole-exome sequencing data with high accuracy.

The paper analyzes structural variation in the glycophorin gene cluster across 6466 genomes, identifies 15 known and 9 new variants, and links structural variants to recombination hotspots.

The paper systematically analyzes non-neuronal defects in Drosophila models of pathogenic copy-number variant genes, identifying developmental issues in multiple tissues and signaling pathways.

The paper introduces SVCurator, a crowdsourcing app for evaluating structural variants in the human genome, finding high concordance among curators and with existing benchmarks.

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 analyzes structural variation in 911 human samples from 54 populations, identifying novel variants and introgressed elements, and highlights the need for diverse high-quality genomes.

The paper examines how structural variants and short tandem repeats affect gene expression and complex traits, identifying high-impact variants associated with multiple genes and GWAS traits.

The paper discovers and genotypes a comprehensive set of structural variants and short tandem repeats using multiple algorithms and replicates, creating a well-characterized map of these variants.

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.

SVJedi genotypes known structural variants from long read sequencing data with high accuracy, outperforming existing methods for long reads.

This paper introduces Mecan4CNA, a method for normalizing copy number variation data, showing improved accuracy and performance in detecting focal regions in cancer genomes.

This study identifies de novo copy number variants in children with ADHD, finding a higher mutation rate compared to controls and associations with known neurodevelopmental disorder loci.