DNA methylation is an essential epigenetic modification that plays a crucial role in regulating gene expression and maintaining genomic stability. With the advancement in sequencing technology, methylation studies have provided valuable insights into the diagnosis of rare diseases through the various identification of episignatures, epivariation, epioutliers, and allele-specific methylation. However, current methylation studies are not without limitations.
View Article and Find Full Text PDFObjective: To execute a large-scale, decentralized, clinical-grade whole exome sequencing study, coined Tapestry, for clinical practice, research discovery, and genomic education.
Patients And Methods: Between July 1, 2020, and May 31, 2024, we invited 1,287,608 adult Mayo Clinic patients to participate in Tapestry. Of those contacted, 114,673 patients were consented and 98,222 (65.
The OmicsFootPrint framework addresses the need for advanced multi-omics data analysis methodologies by transforming data into intuitive two-dimensional circular images and facilitating the interpretation of complex diseases. Utilizing deep neural networks and incorporating the SHapley Additive exPlanations algorithm, the framework enhances model interpretability. Tested with The Cancer Genome Atlas data, OmicsFootPrint effectively classified lung and breast cancer subtypes, achieving high area under the curve (AUC) scores-0.
View Article and Find Full Text PDFMayo Clin Proc
November 2024
Objective: To determine the prevalence, penetrance, and disease expression of cardiomyopathy-related genetic variants in an unselected, richly phenotyped Mayo Clinic population in the setting of preemptive sequencing, with return of incidental findings following the American College of Medical Genetics and Genomics recommendations.
Patients And Methods: We analyzed a quaternary medical center-based biobank cohort (n=983) for reportable variants in 15 cardiomyopathy genes. Prioritization of genetic variants was performed using an internally developed pipeline to identify potentially reportable variants.