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• eMERGE Geisinger eGenomic Medicine (GeM) - MyCode Project Controls

  A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patient agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. For the initial eMERGE Geisinger eGenomic Medicine (GeM) genotyping project, a subset of 1,232 unique samples were genotyped using Illumina HumanOmniExpress-12 v1.0 arrays, and used as population controls for other Geisinger Clinic case cohorts, including abdominal aortic aneurysm and gastric bypass surgery cases. These samples were selected from a larger subset of approximately 6,000 MyCode DNA samples using a partial matching algorithm that included age, sex, and body mass index as variables.

  Study phs000381

• A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

  In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

  Study EGAS50000001529

• Targeted sequencing of cell free DNA samples from oligometastatic colorectal cancer patients

  In order to discover specific mutations that correlate with prognosis, target sequencing was performed using cell-free DNA samples from oligometastatic colorectal cancer patients.

  Study JGAS000196

• The Natural History of Mucolipidosis Type IV

  Mucolipidosis type IV (MLIV) is an autosomal recessive disorder typically characterized by severe psychomotor delay evident by the end of the first year of life and slowly progressive visual impairment during the first decade as a result of a combination of corneal clouding and retinal degeneration. The purpose of this research study is to look at the brain and eye in patients with mucolipidosis type IV (MLIV). MLIV is a lysosomal storage disease that primarily affects the brain and the eyes. The disease is caused by a defect in a gene called MCLON1 that makes a protein called mucolipin-1. Patients with MLIV do not make enough normal mucolipin. The disease begins early in life and the neurological problems seem to stabilize later in life. On the other hand, the eye abnormalities usually progresses over time. The exact course of the disease has not been determined, and until now, no study has addressed this question carefully. The research objectives are: To learn about the natural history of cognitive function for individuals with mucolipidosis type IV. To measure brain volume over time in individuals with mucolipidosis type IV This is an observational study of individuals with MLIV disorder. Those participating in this study will be evaluated annually for five years following a baseline visit.

  Study phs001329

• shallow WGS of cell free DNA

  12.5 ng of cfDNA was used as input for shallow whole-genome sequencing (sWGS), aiming for a coverage of x0.2-0.4-fold. Library preparation was performed using the TruSeq Nano DNA High Throughput Library Prep Kit (Illumina, San Diego, CA, USA) on an automated Hamilton STAR liquid handling system (Hamilton, Germany GmbH, Robotics, Gräfeling, Germany) with dual indexing, and sequencing was performed on the NextSeq500/550 platform (Illumina). The fraction of tumor-derived DNA in cell-free DNA was estimated using the R package ichorCNA.

  Dataset EGAD00001009796

• Sleep Abnormalities in Rare Genetic Disorders: Angelman Syndrome, Rett Syndrome, and Prader-Willi Syndrome

  This research study will investigate sleep behavior in the rare neurological disorders Angelman Syndrome (AS), Rett Syndrome (RTT), Prader-Willi Syndrome (PWS) and Early-onset Morbid Obesity (EMO). Sleep is very important to proper health and plays a critical role in learning, memory, brain development and brain function. Sleep disturbances can have negative effects on health and the quality of life of children and their families. Sleep disorders are common in individuals with AS, RTT, PWS and EMO. As a result, individuals with AS, RTT, PWS and EMO are at risk for sleep-related health problems that can worsen existing daytime behaviors and lead to additional problems with learning and memory. The principal objectives of the study are to: Characterize sleep behavior in individuals with Angelman Syndrome, Rett Syndrome, Prader-Willi Syndrome and Early-onset Morbid Obesity. Compare sleep behavior in these individuals with sleep behavior in normal controls Assess the natural history of sleep behavior in individuals with Angelman Syndrome, Rett Syndrome, Prader-Willi Syndrome and Early-onset Morbid Obesity About this Study This is a questionnaire study that will evaluate the sleep behavior of individuals with AS, RTT or PWS (participants), or unaffected siblings of individuals with AS, RTT or PWS (controls). Those participating in the study will already be registered with the Rare Disease Clinical Research Network (RDCRN) and have a confirmed diagnosis of AS, RTT or PWS or be an unaffected sibling. We will look at the medical records on file with the RDCRN to confirm diagnosis of AS, RTT or PWS. Study participants will participate in the study at their regularly scheduled RDCRN clinic visits. Participants will be asked to complete questionnaires at the study visits that will document their sleep behaviors. The questionnaires are not difficult and participants should be able to complete them in approximately 15-30 minutes. Parents and legal guardians are allowed to assist participants or answer on their behalf. Questionnaires will be administered at the initial study visit and at a 12 month follow-up visit to document any changes in sleep behavior. We hope to enroll approximately 1400 individuals with either AS, RTT or PWS or their unaffected siblings.

  Study phs001292

• VIKING Health Study - Shetland

  The Viking Health Study – Shetland, together with ORCADES collectively termed VIKING, aims to identify genes influencing risk factors for common diseases such as heart disease, diabetes, glaucoma and stroke. The genetic research cohort study in Shetland was established to identify genetic variants, both common and rare, increasing risk of disease. This isolated population has a number of characteristics, the most important being the very large number of distant relatives, which are favourable for the identification of rare variants influencing disease risk. This study describes PCR-free paired end whole genome sequencing (TruSeq DNA PCR-Free, Illumina) run on a HiSeqX platform at 30X coverage on 500 individuals from VIKING. Unrelated individuals from the largest families were selected first, followed by those from smaller families, until eventually related individuals were selected to best represent the variation in the full cohort.

  Study EGAS00001003872

• De novo mutations in cell-free foetal DNA (cffDNA)

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000596

• Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA

  This dataset contains a total of 10 families and 51 samples presented in 'Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA' study, in which 9 of them are cfDNA samples and the rest of samples are gDNA samples. All the samples are targeted sequencing data with a custom 45Mb capture library . Raw pair-end fastq files for each sample is available.

  Dataset EGAD00001004989

• Whole-genome sequencing of cell-free DNA from pancreatic and breast cancer cohorts for fragmentomic and tumor fraction analysis

  This project provides whole-genome sequencing data from cell-free DNA collected from patients with pancreatic ductal adenocarcinoma and breast cancer, alongside healthy and benign controls. The study aims to identify novel liquid biopsy biomarkers by exploring the relationship between per-base quality scores and fragmentomic signals like end-motifs and fragment length. Furthermore, the data supports the development of Bayesian deep learning frameworks for the uncertainty-aware estimation of tumor fraction and ploidy in low-concentration clinical samples.

  Study EGAS50000001620