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• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult DNA (2025-10-16)

  Human Cell Atlas - WGS Adult Heart . This dataset contains all the data available for this study on 2025-10-16.

  Dataset EGAD00001015751

• Inserm U1231 GAD TEAM

  This Data Access Committee reviews requests for access to the data submitted by the Inserm U1231 – Team GAD research team.

  Dac EGAC50000000707

• Lam-ESC&Lam-Recombination data

  This dataset includes all data produced in the study describing "Lam-ESC&Lam-Recombination", a method for sequencing of signal joints and coding joints generated from human light chain antigen receptor loci during V(D)J recombination in B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) patients. This dataset includes: - Amplicon Lam-ESC for a total of 86 BCP-ALL patients - fastq files - Amplicon Lam-Recombination for a total of 43 BCP-ALL patients - fastq files

  Dataset EGAD50000000597

• Validation for human early embryonic substitutions (2017-05-11)

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003332

• Immune Profiles Study

  This study assesses glioma patient blood methylation longitudinally beginning pre-surgery through other clinically important timepoints. Progression and survival are studied in relation to methylation derived immunologic profiles and other characteristics. For this study, patients scheduled for surgery at University of California San Francisco (UCSF) for a possible newly diagnosed glioma (grades 2-4) or recurrent grade 2/3 glioma were consented and enrolled. Patients had blood collected pre-surgery and, if the pathology results confirm a glioma, every few weeks or months during their treatment (up to 30 total timepoints). Blood immunomethylomic profiles were measured at these timepoints to assess associations with glioma patient outcomes, clinical measures, other known prognostic markers, and imaging characteristics.

  Study phs002998

• Whole genome sequencing of adult glioblastoma nuclei

  Nuclei were extracted from three primary adult glioblastoma samples and processed for scATAC-seq, and residual nuclei left over from these same samples were used to extract DNA and processed and sequenced for WGS. This WGS data was then used to cross-validate assessment of large-scale copy number alterations with scATAC-seq using the Copy-scAT tool.

  Study EGAS00001005256

• Multi-omics integration reveals only minor long-term molecular and functional sequelae in immune cells of individuals recovered from COVID-19

  The majority of COVID-19 patients experience mild to moderate disease course and recover within a few weeks. An increasing number of studies characterized the long-term changes in the specific anti-SARS-CoV-2 immune responses, but how COVID-19 shapes the innate and heterologous adaptive immune system after recovery is less well known. To comprehensively investigate the post-SARS-CoV-2 infection sequelae on the immune system, we performed a multi-omics study by integrating single-cell RNA-sequencing, single-cell ATAC-sequencing, genome-wide DNA methylation profiling, and functional validation experiments in convalescent COVID-19 and healthy individuals. We showed that immune responses generally recover without major sequelae after COVID-19. However, subtle differences persist at the transcriptomic level in monocytes, with downregulation of the interferon pathway, while DNA methylation also displays moderate changes in convalescent COVID-19 individuals. However, these differences did not affect the cytokine production capacity of PBMCs upon different bacterial, viral, and fungal stimuli, although baseline release of IL-1RA and IFN?? was higher in convalescent individuals. In conclusion, despite minor differences in epigenetic and transcriptional programs, the immune system of convalescent COVID-19 patients largely recovers to the homeostatic level of healthy individuals.

  Study EGAS00001005529

• Immunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays

  IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) is a prospective longitudinal cohort study (NCT04378777) launched in May 2020 in response to the worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institute of Health (NIH). Patient enrollment and sample analysis involved 20 hospitals associated with 15 U.S. biomedical research centers and 11 centralized Core immunoassay laboratories.The study aimed to enable the identification of potential biomarkers and inform future therapeutic interventions using a longitudinal approach encompassing the whole disease course for a comprehensive understanding of the contributions of the pathogen and host immune response in modulating the manifestations, severity, and post-acute sequelae of the infection. IMPACC enrolled close to 1200 adult symptomatic, molecularly confirmed hospitalized COVID-19 patients in the study within 48 hours of their hospital admission. Clinical data and biological samples (blood, mid-turbinate nasal swabs, and esophageal aspirant) were collected according to minimal risk guidelines at enrollment and on days 4, 7, 14, 21, and 28. Biological samples were collected at 3-month intervals up to 12 months after hospital discharge to assess functional and immunologic recovery measures. Sample collection, processing, and storage procedures were standardized across sites, and samples were transported to centralized assay-specific core laboratories (Core Labs) in batches for testing and analysis. The description of outcome severity was not limited to survival versus death but encompassed a clinical trajectory approach using 5 groups leveraging longitudinal data based on time in the hospital, disease severity by ordinal scale based on the degree of respiratory illness, and presence or absence of limitations at discharge. Disease severity was assessed based on the degree of respiratory illness using a 7-point ordinal scale adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. DNA for genetic analyses was collected from whole blood at a single time point. To identify any genomic determinants of severe COVID-19 disease, single-nucleotide polymorphism (SNP) genotyping and exome sequencing were conducted to assess genetic variants associated with individual susceptibility to severe disease. In addition, IMPACC included bulk transcriptomic analysis of upper airway (nasal swaps) samples, lower airway (esophageal aspirant) samples, and peripheral blood mononuclear cells (PBMCs) to evaluate dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome. Additional information for the IMPACC study has been submitted to The Immunology Database and Analysis Portal (ImmPort) under study accession SDY1760. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Steven Kleinstein (steven.kleinstein@yale.edu).

  Study phs002686

• Genome Diversity in Africa Project: Uganda (2021-02-17)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics . This dataset contains all the data available for this study on 2021-02-17.

  Dataset EGAD00001006976

• Complete DNA/RNA sequencing dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07

  Complete WGS and RNA-Seq dataset for Australian ICGC ovarian cancer sequencing project 2014-07-07, representing 93 donors. Sequencing was performed on Illumina HiSeq. Alignment of the lane-level fastq data was performed with bwa (WGS data) and RSEM (transcriptome data). For this dataset lane-level .bam files have been merged and de-duplicated to create a single bam file for each sample type (tumour/normal) for each donor. This dataset supersedes all previous datasets for this study. 2016-08-08 updated with 14 outstanding RNA-seq samples & corresponding RSEM bams 2016-12-07 updated with 7 outstanding RNA-seq controls and corresponding RSEM bams

  Dataset EGAD00001000877