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• Visium CytAssist Spatial Gene Expression analysis for glioblastoma

  The glioblastoma spatial transcriptomics dataset was generated from 4 FFPE fixed adult glioblastoma samples, using the 10x Genomics Visium platform, producing raw FASTQ files, spatial feature matrices (.h5, .mtx, .tsv), and paired histology images (.tif). Spot-level transcript counts were aligned to tissue architecture and processed in Seurat, with results stored as .rds objects. Data visualization was performed using SpatialFeaturePlot, and quantitative analyses were supported by custom Matlab scripts. The dataset provides both raw and processed files, offering reproducible spatially resolved transcriptomic profiles of glioblastoma tissue sections

  Dataset EGAD50000001767

• Addictions: Genotypes, Polymorphisms, and Function/Human Genetic Correlates of Addictive Diseases

  Drug addiction continues to be a major medical and social problem. It is estimated that one million or more persons in the United States are currently addicted to heroin or prescription opioids, with millions more worldwide. Cocaine addiction and alcohol dependence are frequent comorbid conditions in persons with heroin/opioid dependence in addition to being major primary addictions. Many studies over the past thirty years have shown that these drugs disrupt physiologic systems, and that these disruptions may contribute to drug addiction and alcohol dependence and to relapse to drug or alcohol abuse following withdrawal and abstinence. Clinical observations suggest that individuals differ in their response to heroin, cocaine, and alcohol; however, little is known about specific underlying hereditary genetic factors which might influence individual susceptibility to the addictive properties of these substances. Studies also suggest that both common and distinct heritable factors account for the genetic variance in the susceptibility to the separate addictive diseases. We hypothesize that there is a heritable as well as environmental basis for the acquisition and persistence of, and relapse to, specific addictive diseases. Using samples from individuals without and with opioid and other specific drug dependence diagnoses and psychiatric comorbidities, genetic analyses will be used to determine association and linkage. All study subjects will be extensively characterized with respect to the addictive diseases, medical history, family medical addictive disease history; psychiatric comorbidity, and psychological profile, as well as ethnic/cultural background. A better understanding of the consequences of genetic contributions with respect to protection from, or susceptibility to, heroin/opioid addiction and related codependencies and comorbid conditions, could have enormous importance in both prevention and treatment of this problem.

  Study phs001109

• The CHOP Pediatric Genetic Sequencing (PediSeq) Project : Applying Genomic Sequencing in Pediatrics

  The purpose of this research study is to learn more about newer types of genetic testing called whole exome sequencing and whole genome sequencing. Current genetic testing usually examines one gene or a few genes at a time. Exome and genome sequencing allow us to test most of a person's genes at one time with a single test. This testing might identify the reason for a person's unexplained condition or diagnosis. We hope this study will help us identify the best methods for: Educating patients and families about exome and genome sequencing Analyzing exome and genome sequencing data to identify results relevant to patients Giving results to families in a clear, appropriate, and informative manner The current data only includes WES for 159 samples. The WGS samples for 20 samples will be uploaded in the near future.

  Study phs000935

• Development and Validation of a Disability Severity Index for Charcot-Marie-Tooth Disease (CMT)

  In Charcot-Marie-Tooth Disease (CMT) or inherited neuropathy research studies, it is the researcher who has selected what they believe to be important markers of impairment in function in patients. For example, it has been inferred that the wearing of ankle-foot-orthosis (AFOs), the use of walking aids such as canes, or the use of wheelchairs, are appropriate markers for “mild”, “moderate” or “severe” disability, respectively. Whether patients agree with this classification is unknown. By understanding what patients classify as mild, moderate and severe disability in CMT, we will know what our treatments need to target, to have a meaningful impact on the patients' functional status. Primary objective: The purpose of this study is to compare patient and healthcare provider impressions of what constitutes mild, moderate and severe disability in CMT. Target population: 200 patients who have self-registered at the Inherited Neuropathy Consortium Contact Registry, a web-based contact registry developed and supported by the Data Management and Coordinating Center (DMCC) for the Rare Diseases Clinical Research Consortium (RDCRN), located at the University of South Florida, and 200 health care professionals attending conferences about CMT, such as the 4th International CMT Consortium to be held in Potomac, Maryland, June 29-July 1, 2011 and the MDA Clinic Directors meeting in Las Vegas, NV March 4-7, 2012. Methods: A brief, anonymous, 20-item survey, in which we measure what the physician and the patient think are important indicators of disability in CMT, will be distributed by paper to 200 health care professionals, and via an online link to 200 patients self-registered with the RDCRN contact registry. Out of the 200 patients, approximately 25 patients will be requested to take the survey twice in a 2 to 4 week period. Analysis: We will measure the agreement between items in the physician and patient groups, and use items with high agreement in a Disability Severity Index.

  Study phs001295

• Yale Center for Mendelian Genomics (YCMG)

  From 2012-2021, Yale University was home to one of four national centers created by the National Institutes of Health (NIH) to study the genetics of rare inherited diseases. Researchers at Yale University, University of Washington, the Broad Institute and a center operated jointly by Baylor University and Johns Hopkins University analyzed the genomes of thousands of patients who suffer from more than 6,000 rare Mendelian disorders affecting more than 25 million individuals in United States. The Centers for Mendelian Genomics (CMG) applied next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian disorders. The discovery of new genes that cause Mendelian conditions expanded our understanding about their biology to facilitate their diagnosis, and potentially indicate new treatments. The CMG provided free exome sequencing and analysis to collaborating investigators for qualified phenotypes.

  Study phs000744

• Bulk RNAseq FASTQ files of WNT7B reporter PDAC organoids (P28 and P40) sorted by mNeonGreen high and low

  This dataset contains raw FASTQ files from bulk RNA sequencing of two patient-derived PDAC organoid lines (P28 and P40) carrying a WNT7B reporter knock-in. Organoids were sorted into mNeonGreen high (WNT-high) and low (WNT-low) populations, with three biological replicates per sorted population. RNA was extracted using the Qiagen QiaSymphony SP system, and libraries were prepared with the Illumina Truseq stranded polyA kit. Sequencing was performed on an Illumina NextSeq2000 platform using single-end 50bp reads. Quality control was conducted with FastQC, and reads were trimmed with TrimGalore as appropriate. Data are controlled-access and intended for transcriptomic analysis of WNT7B expression-dependent transcriptional programs in PDAC organoids.

  Dataset EGAD50000002218

• Epigenome-wide association study of asthma remission in whole blood and nasal epithelium

  Clinical remission (ClinR) was defined as the absence of asthma symptoms and medication for at least 12 months, and complete remission (ComR) was defined as ClinR with normal lung function and absence of airway hyperresponsiveness. We analyzed differential DNA methylation of ClinR and ComR comparing to persistent asthma (PersA) in whole blood samples (n=72) and nasal brushing samples (n=97) in a longitudinal cohort of well characterized asthma patients.

  Dataset EGAD00010002026

• PEACE melanoma 14

  Understanding the evolutionary pathways to metastasis and resistance to immune checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here we present the most comprehensive intra-patient metastatic melanoma dataset assembled to date as part of the PEACE research autopsy programme, including exome, panel-sequenced, RNA-seq, and single-cell whole-genome sequencing samples from 14 ICI-treated patients. The main goals of the project are to decipher the evolutionary dynamics of melanoma metastases and to elucidate mechnisms of resistance to therapies.

  Study EGAS00001007081

• EGA synthetic data

  Synthetic Data One of the limitations in genomics research is that human genomics data is not openly available; access must be controlled according to participant consent agreements and data protection regulations such as GDPR. Obtaining authorization to access such data can sometimes take a long time, resulting in delays to important research work. In this context, synthetic genomic and phenotype data can be useful resources for researchers to avoid these delays. Synthetic data are artificially generated datasets, often created with algorithms, which can be used without the need for authorization to test new products and tools, build technical demonstrators, validate data models, and train AI models. The EGA provides access to synthetic cohort datasets augmented with rich synthetic metadata that overcomes these real data usage restrictions. Whilst synthetic datasets are not included in the general EGA mandate and services, we can consider such submissions and evaluate their acceptance on the basis of their unique use cases not already covered by existing synthetic datasets. Access to synthetic data studies is managed by the EGA Helpdesk Data Access Committee. Study ID Title Located in EGAS00001002472 CINECA synthetic cohort EUROPE UK1 referencing fake samples Central EGA EGAS00001005591 Synthetic data - Genome in a Bottle Central EGA EGAS00001005042 Test Study for EGA using data from 1000 Genomes Project - Phase 3 Central EGA EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Central EGA EGAS50000000190 EOSC4Cancer Synthetic Colorectal Cancer Genomic data Central EGA EGAS50000000086 Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023 Federated EGA Sweden EGAS50000000678 Synthetic - GDI synthetic data Federated EGA Spain

  Documentation synthetic-data

• Comprehensive molecular characterization of brainstem glioma

  Brainstem gliomas are the most devastating and lethal tumors. Survival rates are among the lowest in all cancers and options for intervention are likewise low. Due to anatomical delicacy of these areas, resection of tumors is particularly difficult and attempted resections have high perioperative mortality rates. Genomic and epigenetic studies often provide a gateway to functional studies of specific classifications of tumors that can lead to major breakthroughs in diagnosis and treatment options.

  Study EGAS00001004341