Zohra Saci

gVCF2CNV converts gVCF files into CNV-compatible signals for large-scale WGS cohorts, achieving high precision in detecting deletions and duplications.

The paper develops predictive models for intellectual disability in autistic children by integrating genetic variants and developmental milestones, achieving an AUC ROC of 0.65 and identifying 10% of ID cases.

The paper identifies a CNV duplication associated with higher cognitive ability and shows gene-dosage effects differ between deletions and duplications across biological processes.

The paper examines CNV frequency differences across genetic ancestry groups and finds lower prevalence of deleterious CNVs in non-European ancestry groups.

The paper investigates the impact of rare high-effect genetic variants on brain morphology and related behavioral traits in adolescents using the ABCD cohort.

This study shows that rare CNVs and PRS-IQ increase ASD risk independently of their effects on cognitive ability, suggesting ASD risk and cognitive ability are distinct outcomes of these variants.

The paper investigates how rare genetic mutations affect brain asymmetry by analyzing CNVs in a cohort of individuals and linking genetic alterations to brain structure and function.

The paper introduces a multi-polygenic risk score approach to study ASD's genetic architecture, finding that multi-PRSs capture similar risk as traditional PRS-ASD but reveal developmental mirroring effects.

The paper investigates how copy number variants in circadian pathway and insomnia risk genes contribute to ASD risk and sleep disturbances in children with ASD.

The paper investigates how eight rare CNVs affect brain structure and phenotypes across 534 carriers, finding structural divergence and phenotypic convergence despite different genetic origins.

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.

The paper quantifies the effect of copy number variants on cognitive ability using genomic data from 24,092 individuals, finding that 10,000 genes modulate intelligence.

The paper introduces a reference-free computational method to identify novel RNAs for prostate cancer diagnosis, finding that 9 unannotated lncRNAs outperform existing biomarkers.