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• HELIUS DAC The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Dac EGAC00001000895

• SDH_deficient_renal_tumours___WGS_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004102

• National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

  NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

  Study phs004180

• Whole-exome/genome sequencing of childhood acute leukemia in Iraq

  This dataset contains 26 whole-genome sequencing (13 paired tumor and normal), 106 whole-exome sequencing (53 paired tumor and normal), and 43 targeted sequencing data. Sequencing was performed using an Illumina platform. The data are BAM files aligned to the hg19 reference genome.

  Dataset EGAD00001007873

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 26 patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Study EGAS50000000146

• Family Investigation of Nephropathy and Diabetes (FIND) Study

  The Family Investigation of Nephropathy and Diabetes (FIND) is a multicenter study designed to identify genetic determinants of diabetic kidney disease. Study subjects were recruited from eleven centers and in many ethnic groups throughout the United States. A genome-wide association study (GWAS) was conducted with the Affymetrix 6.0 chip. Subjects (index cases) with diabetes and kidney disease were initially recruited, and their parents and siblings were invited to participate. Genetic material from these participants was used to genotype markers throughout the genome. For association-based testing, a case-control design was implemented with study subjects selected primarily from the index cases of the families. Unrelated controls were selected from families where a case was not already selected. Several study sites also contributed non-FIND subjects, both cases and controls (consent forms for the release of FIND and non-FIND subjects/samples are included in this dbGaP release). Cases were selected if they met study criteria for diabetic nephropathy or met inclusion criteria based on elevated serum creatinine levels and abnormal urine protein excretion. Similarly, controls were long-term diabetics with otherwise normal kidney function. See inclusion/exclusion criteria section for a detailed description for the FIND study as a whole and this GWAS. The goal of the FIND study is to identify genes that influence susceptibility to diabetic kidney disease, leading to a better understanding of how kidney disease develops. In the long run, this may lead to improved treatment and prevention of diabetic kidney disease.

  Study phs000333

• Understanding Self- Organising Capacity of Stem Cells during Implantation and Early Post-implantation Development in vitro and in vivo: Implications for Human Development (2020-04-20)

  The aim of this project is to differentiate human embryonic stem cells to an extra-embryonic fate, specifically the hypoblast. This is of uttermost importance given the current lack of human hypoblast stem cells. We hypothesized that the pluripotent characteristics of the starting human embryonic stem cell population may dictate the competency for extra-embryonic cell fate specification. Based on this hypothesis and using human embryonic stem cells maintained in different naïve-like culture regimes, we have now developed conditions that allow the differentiation of human embryonic stem cells to a stable GATA6+ SOX2- population. This suggests that these cells may be putative human hypoblast stem cells. To validate this finding here we propose to perform RNA sequencing experiments of the differentiated human embryonic stem cells. By comparing their RNA expression profile to the single cell sequencing data of the human embryo that we are currently generating, we will be able to determine the identity of our GATA6+ SOX2- cells, and establish whether they represent the in vivo human hypoblast. This dataset contains all the data available for this study on 2020-04-20.

  Dataset EGAD00001006056

• Genetic Components of Knee Osteoarthritis (GeCKO) Study: The Osteoarthritis Initiative

  The Osteoarthritis Initiative (OAI) is a publicly and privately funded prospective longitudinal cohort with a primary objective of identifying risk factors for incidence and progression of tibiofemoral knee OA. The OAI utilized a focused population-based recruitment to enroll 4,674 men and women between the ages of 45-79 years who either had radiographic symptomatic knee OA or who were without radiographic symptomatic OA in both knees but were considered high risk for OA because they had two or more known risk factors for knee OA. Subjects were recruited into the baseline phase of the OAI at multiple sites throughout the US between 2004 and 2006. All subjects were invited back for follow-up examinations to assess incidence or progression of OA annually, for up to 5 years. Phenotype data from the baseline and follow-up examinations are available for public access from the Osteoarthritis Initiative (OAI) database at http://www.oai.ucsf.edu/. The Genetic Components of Knee Osteoarthritis (GeCKO) Study was initiated in 2009 as a genetic ancillary study to perform a genome-wide association study to identify genetic variants associated with radiographic osteoarthritis. This study included 4,482 individuals participating in the parent OAI study. Following sample cleaning (e.g., removal of duplicates, sex mismatches, poor sample quality, etc.), the final sample set included 4,129 individuals.

  Study phs000955

• bulk RNAseq analysis of tumor from 3 non-muscle-invasive bladder cancer patients

  We performed screenings of patient-specific neo-epitopes by tumor-infiltrating CD8+ T lymphocytes of 4 non-muscle invasive bladder cancer patients. After the tumor resection, these patients went on to receive BCG treatment as they had high-risk disease. In order to select the neo-epitopes, we performed bulk RNAseq of the bladder tumor to select the mutated genes that were expressed in the tumor (TPM >1). For patient UC2, 3 different tumors were resected at the same time and RNA from these 3 tumors were sent separately for RNAseq. For patient UC4, no RNA was available, so this patient is not included in this study.

  Study EGAS50000001383

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001513