14305 results for ""Pennsylvania+German"+ACS+study+'Socius'+open+access"

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• Relation between transcriptome, karyotype and age in cases of sex chromosome aneuploidies.

  Why women live longer than men is still an open question in human biology. Sex chromosomes have been proposed to play a role in the observed sex gap in longevity, and the Y male chromosome has been suspected of having a potential toxic genomic impact on male longevity. It has been hypothesized that transposable element (TE) repression declines with age, potentially leading to detrimental effects such as somatic mutations and disrupted gene expression, which may accelerate the aging process. Given that the Y chromosome is rich in repeats, age-related increases in TE expression could be more pronounced in males, likely contributing to their reduced longevity compared to females. In this work, we first studied whether TE expression is associated with the number of sex chromosomes in humans. We analyzed blood transcriptomic data obtained from individuals of different karyotype compositions: 46,XX females (normal female karyotype), 46,XY males (normal male karyotype), as well as males with abnormal karyotypes, such as 47,XXY, and 47,XYY.

  Study EGAS00001007462

• Mechanisms of patient response to Dabrafenib in Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)*NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]*CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Dataset EGAD00001001375

• 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

• Synthetic - GDI synthetic data

  Synthetic - The Genomic Data Infrastructure (GDI) project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure the GDI project (funding: EC H2020 under grant agreement number 101081813) is acknowledged.

  Study EGAS50000000678

• Data Access Committee for study Genetics of Preeclampsia at High Altitudes

  Dac EGAC00001002097

• Hepatocellular Carcinoma Spatial transcriptomics Data Access Committee

  This is the DAC for study ST HCC

  Dac EGAC50000000635

• Institut Curie Data Access Committee

  Data Access Committee to access U932 Transim NGS data

  Dac EGAC50000000205

• The University of Hong Kong Colon Cancer Organoids Genomics Study Data Access Committee

  Dac EGAC00001001405

• Swedish schizophrenia study (S3) data access

  Dac EGAC00001003466

• LIONESS DAC

  This DAC will govern access to WES data associated with the LIONESS study.

  Dac EGAC50000000613

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• DAC Johns Hopkins University - AML scRNAseq study

  This is the Data Access Committee (DAC) from Johns Hopkins University for the study scRNAseq of acute myeloid leukemia

  Dac EGAC50000000242

• About

  About What's the EGA? The European Genome-phenome Archive (EGA) is a global network for permanent archiving and sharing of personally identifiable genetic, phenotypic, and clinical data generated for the purposes of biomedical research projects or in the context of research-focused healthcare systems. Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, we aim to advance biomedical research and promote personalised medicine worldwide by enabling discovery of and access to human genomic and health research data. The EGA contains data collected from individuals whose consent agreements authorise data release for specific research use to bona fide researchers. We ensure strict security measures to control access to the data and maintain patient confidentiality. With expertise in data management and technical infrastructure, we promote FAIR data reuse and enable researchers to share their data securely. By leveraging public funding and our strategic partnerships, the EGA provides a free service for permanent data storage, data discovery, and secure data access. In addition, we foster a federated network to provide transnational access to human research data in compliance with legal frameworks. For additional information about the EGA, please contact: Helen Parkinson and Mallory Freeberg EMBL European Bioinformatics Institute Arcadi Navarro, Roderic Guigó, and Jordi Rambla Center for Genomic Regulation History The European Genome-phenome Archive was launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. With the signing of a memorandum of understanding in 2013 and a formal agreement in 2016, the EGA became a joint project of EMBL-EBI and the Centre for Genomic Regulation (CRG). The two institutes work together to support the EGA services, including supporting submissions, website, strategic leadership, and data infrastructure developments. In 2022, the Federated EGA was officially launched with the signature of the first five countries: Finland, Germany, Norway, Spain, and Sweden. With more than 20 additional nodes worldwide preparing to join, the Federated EGA aims to become the largest human omics data sharing initiative towards understanding human health and disease. EGA overview If you're a researcher you may need to deposit, manage, or access genomic data in a secure and regulated way. The European Genome-phenome Archive (EGA) is a platform that facilitates these processes, ensuring that sensitive data is stored and shared in accordance with legal and ethical regulations. Submission process To start a submission, you need to become an EGA submitter. For that, you’ll need to sign a Data Processing Agreement (DPA) with us, that defines the terms and conditions under which your data will be processed and shared within the EGA system. The access to each study is controlled by its Data Access Committee (DAC). The DAC is responsible for managing data access requests and ensuring that the release of data is in accordance with the General Data Protection Regulation (GDPR). Please, note that once your data is released, all public metadata related to your study and dataset(s) will be searchable on the EGA website. However, the files are only accessible under controlled access, which means that a DAC has to agree to a previous data access request. Request process It is possible to submit an access request to data stored at the EGA. The DAC assigned to the study will assess the request and, if approved, grant access to the data. Requesters must provide sufficient justification for your request and comply with the intended data usage in order to get access to it. Each dataset is covered by a Data Access Agreement (DAA) that defines the terms and conditions of use for the specified dataset/s. The DAA is created and provided by the DAC, and must be signed by the individual requesting access to the given dataset/s. Download process Once the request for access is approved, the data and metadata can be downloaded. The EGA offers various download options to fit the needs: it is possible to preview files without downloading them, download specific files of interest, or even download terabytes of data. Overall, the EGA provides a secure and regulated environment for depositing, managing, and accessing human data. Regardless of the role - submitter, DAC member, or requester - the EGA provides assistance for each while ensuring that sensitive data is managed in an ethical and responsible manner. More information on how EGA handles data is available in the EGA dataflow.

  Documentation about/ega

• Transcriptomic profiles of chronic lymphocytic leukemia before and after frontline therapy: 5-year results from the randomized CLL14 study

  CLL14 (NCT02242942) is a multinational, open-label Phase III study designed to compare venetoclax-obinutuzumab (Ven-Obi) versus chlorambucil-obinutuzumab (Clb-Obi) in previously untreated patients with CLL and co-existing conditions. Between Aug 7, 2015, and Aug 4, 2016, 432 patients were enrolled and randomly assigned to receive either venetoclax plus obinutuzumab (Ven-Obi, n=216) or chlorambucil plus obinutuzumab (Clb-Obi, n=216). In both study arms, patients received fixed-duration treatment of overall 12 cycles, each cycle 28 days long, and entered subsequent post-treatment surveillance. Peripheral blood samples were collected before the start of therapy, as well as every 3-6 months during and after therapy, including at the time of disease progression. The primary endpoint of the study was progression-free survival, secondary endpoints included overall response rate, minimal residual disease response, and overall survival. The primary read-out was conducted after a median follow-up of 28.1 months, when the primary endpoint was met with 30 primary end-point events (disease progression or death) in the Ven-Obi arm and 77 in the Clb-Obi arm (hazard ratio, 0.35; 95% confidence interval [CI], 0.23 to 0.53;P<0.001). Follow-up is ongoing until 9 years after the last patient enrollment. In an exploratory analysis, bulk RNAseq was conducted with CD19-enriched blood from patients before start of therapy (418 patients) and at first relapse (44 patients).

  Study EGAS00001006596

• TFTAK Data Access Committee

  The TFTAK Data Access Committee (TFTAK DAC) oversees access to data generated by TFTAK research projects.

  Dac EGAC50000000885

• DAC to control the access to the RRBS raw data of the glioblastom progression study (GBMatch).

  Dac EGAC00001000689

• Data Access Committee for the study "Somatic chronology of treatment-resistant prostate cancer via deep whole-genome ctDNA sequencing"

  Dac EGAC00001002479

• OXEL WES DAC

  This DAC controls access to the whole exome sequencing (WES) data from the OXEL pilot study.

  Dac EGAC50000000163

• Cancer Research UK Manchester Institute/ Cancer Research UK National Biomarker Centre Data Access Committee

  Cancer Research UK Manchester Institute/Cancer Research UK National Biomarker Centre Data Access Committee is created to • Review and approve data access requests. • Ensure data security and compliance with institutional and legal obligations. • Maintain accurate records of access decisions For questions or further information, please contact: Chair of the Data Access Committee: Caroline Wilkinson Email: dac@cruk.manchester.ac.uk

  Dac EGAC50000000795

• Whole exome sequencing of Parkinson's disease patients from the United Kingdom

  As part of the International Parkinson's Disease Genomics Consortium, exomes of Parkinson's disease (PD) patients and healthy controls were sequenced to study the genetic etiology of PD. This UK cohort consists of 70 PD patients. Researchers can apply for access to fastq, vcf and binary plink files for this cohort.

  Study EGAS00001002156

• Data Access Commitee for study Fine-Scale Genomic Analyses Of Admixed Individuals Reveal Unrecognized Genetic Ancestry Components In Argentina

  Dac EGAC00001001634

• Access to aligned sequencing data for study "Loss of SNAI2 in prostate cancer correlates with clinical response to androgen deprivation therapy".

  Dac EGAC00001001809

• NCI's Datasets for General Research Use

  This collection contains all of NCIs authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level GRU datasets that become available. Renewal of this study is required annually.

  Study phs003014

• SpainUDP Data Access Committee

  Data access committee handling data access requests for RNAseq data related to the Spanish Undiagnosed Rare Diseases Program SpainUDP cohort.

  Dac EGAC50000000932

• Data access committee for study - The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program "CASCADE".

  Dac EGAC00001000574

• Small Intestine Adenocarcinoma Subtyping Data Access Committee

  DAC created for the Molecular classification of small intestinal adenocarcinomas Study in Amsterdam UMC.

  Dac EGAC50000000663

• GenomeEUtwin Data Access Committee

  Access to data generated by the GenomeEUtwin is available by emailing application to the data access committee and will be granted to qualified investigators for appropriate use.

  Dac EGAC00000000007

• Compilation of Aggregate Genomic Data for General Research Use

  This study contains all authorized aggregate genomic data from datasets currently in dbGaP that are approved for general research use (GRU) and have no further limitations beyond those outlined in model Data Use Certification Agreement. Access to this study will be granted for one year and any additional authorized aggregate GRU datasets that become available during this one-year period. This study does not include individual-level data.

  Study phs000501

• ITER-FIISC Data Access Committee

  DAC for whole-genome variant calling data of individuals from the study of allergic diseases in the Canary Islands.

  Dac EGAC50000000180

• dbGaP Collection: Compilation of Individual-Level Genomic Data for General Research Use

  This dbGaP Collection contains all authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level GRU datasets that become available. Renewal of this study is required annually. Data Included in this Study Individual-level genomic data designated for general research use with no further use limitations or restrictions, that is, Data use does not require approval by an Institutional Review Board for secondary analyses Data have no publication embargo Data have no other use limitations (e.g., requirement for collaboration or publication; restricted for use by academic or not-for-profit organizations; restricted to health, medical, and/or biomedical research) In response to requests from the scientific community, the NIH implemented a change in the procedures for accessing individual-level GRU genomic data. Under the modified procedures, interested investigators can request GRU individual-level genomic datasets with a single application. However, please note that these data have not been harmonized. Additionally, to help expedite the processing of requests for individual-level GRU genomic datasets, the requests will be reviewed by a single, central Data Access Committee. The process for requesting these datasets is identical to the request process for non-GRU individual-level, controlled-access data, such as the expectation that investigators will abide by the NIH Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies and Data Use Certification Agreement. Effective April 24, 2018, the Data Use Limitations (DUL) for the Genes and Blood Clotting Study (GABC) (phs000304) was updated to Health/Medical/Biomedical, Not-for-profit Use Only (HMB-NPU). Additionally, the submitting institutions have requested the removal of the National Heart, Lung, and Blood Institute (NHLBI) "Grand Opportunity" Exome Sequencing Project (GO-ESP) Lung Cohorts Exome Sequencing Project: Genetic modifiers of Pseudomonas aeruginosa (Pa) lung infection acquisition in cystic fibrosis (phs000254) from the dbGaP Compilation of Individual-Level Genomic Data for General Research Use (dbGaP Compilation) (phs000688). As such, data from studies phs000304 and phs000254 are no longer available as part of the dbGaP Compilation (phs000688). Investigators must submit separate Data Access Requests (DARs) for the two studies and be approved by the NHLBI Data Access Committee.

  Study phs000688

• Million Veteran Program (MVP) Summary Results from Non-Sensitive Omics Studies

  MVP is an ongoing prospective cohort study and mega‐biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans. This is the accession to hold publicly available results. Results from sensitive phenotypes or MVP population subsets can be found at accession phs001672 and will require an application for access.

  Study phs002453

• Summarized somatic variant calls from CMMRD-associated high-grade gliomas

  This dataset contains summarized somatic variant call data derived from paired tumor–blood whole-exome sequencing of human samples. Access to the dataset is controlled and granted only upon submission and approval of a formal data access request. Requests are reviewed by the Data Access Committee led by the Principal Investigator to ensure compliance with applicable legal, ethical, and data protection requirements. Users must not attempt to re-identify study participants and must comply with all relevant confidentiality and data protection regulations. In accordance with local legal and ethical requirements, individual-level raw sequencing data are not shared.

  Dataset EGAD50000002180

• Data Access Committee for the DNA sequencing data included in the study "A generalizable machine learning framework for classifying DNA repair defects using ctDNA exomes”

  Dac EGAC00001003111

• Tumor Profiler DAC

  The Tumor Profiler DAC is responsible for the access to data generated in the Tumor Profiler Study.

  Dac EGAC50000000199

• ITER-FIISC Data Access Committee (FPF)

  DAC for Whole-exome variant calling of individuals from the study of familial pulmonary fibrosis in the Canary Islands.

  Dac EGAC50000000473

• Nivolumab and Tumor Infiltrating Lymphocytes (TIL) in Advanced Non-Small Cell Lung Cancer

  We performed a trial of adoptive cell therapy using tumor infiltrating lymphocytes (TIL) in metastatic non-small cell lung cancer (NSCLC). We conducted a single-arm open- label phase 1 trial (NCT03215810) of TIL administered with nivolumab in 20 patients with advanced NSCLC. Patients had tumor metastases resected for TIL, and the sequencing data from these tumors is included herein. The primary endpoint was safety, and secondary endpoints included objective response rate, duration of response, and T-cell persistence. Autologous TIL was expanded ex vivo from minced tumors cultured with IL-2. Patients received initial nivolumab for 4 cycles. If they had subsequent evidence of progression, then they proceeded to receive cyclophosphamide and fludarabine lymphodepletion, TIL infusion, and interleukin-2, followed by maintenance nivolumab. The endpoint of safety was met according to pre-specified criteria. Of 13 evaluable patients, 3 had confirmed responses and 11 had reduction in tumor burden, with a median best change of 35%. Two patients achieved complete responses ongoing 1.5 years later. In exploratory analyses, we found T cells recognizing multiple types of cancer mutations were detected after TIL treatment, and were enriched in responding patients.

  Study phs002486

• Onco-exaptation of an Endogenous Retroviral LTR Drives IRF5 Expression in Hodgkin Lymphoma

  The transcription factor interferon regulatory factor 5 (IRF5) is upregulated in Hodgkin lymphoma (HL) and a key regulator of the aberrant transcriptome characteristic of this disease. Here we show that IRF5 upregulation in HL is driven by transcriptional activation of a normally dormant endogenous retroviral LOR1a long terminal repeat (LTR) upstream of IRF5. Specifically, through screening of RNA-seq libraries, we detected LTR-IRF5 chimeric transcripts in multiple HL cell lines but not in normal B-cell controls. In HL, the LTR was in an open and hypomethylated epigenetic state and we further show the LTR is the site of transcriptional initiation. Among HL cell lines, usage of the LTR promoter strongly correlates with overall levels of IRF5 mRNA and protein, indicating that LTR transcriptional awakening is a major contributor to IRF5 upregulation in HL. Taken together, oncogenic IRF5 overexpression in HL is the result of a specific LTR transcriptional activation. We propose that such LTR derepression is a distinct mechanism of oncogene activation (“onco-exaptation”) and that such a mechanism warrants further investigation in molecular and cancer research.

  Study EGAS00001001205

• Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome

  Mutation in the germline is the ultimate source of genetic variation, but little is known about the influence of germline chromatin structure on mutational processes. Using ATAC-seq, we profile the open chromatin landscape of human spermatogonia, the most proliferative cell-type of the germline, identifying transcription factor binding sites (TFBSs) and PRDM9-binding sites, a subset of which will initiate meiotic recombination. We observe an increase in rare structural variant (SV) breakpoints at PRDM9-bound sites, implicating meiotic recombination in the generation of structural variation. Many germline TFBSs, such as NRF, are also associated with increased rates of SV breakpoints, apparently independent of recombination. Singleton short insertions (>=5 bp) are highly enriched at TFBSs, particularly at sites bound by testis active TFs, and their rates correlate with those of structural variant breakpoints. Short insertions often duplicate the TFBS motif, leading to clustering of motif sites near regulatory regions in this male-driven evolutionary process. Increased mutation loads at germline TFBSs disproportionately affect neural enhancers with activity in spermatogonia, potentially altering neurodevelopmental regulatory architecture. Local chromatin structure in spermatogonia is thus pervasive in shaping both evolution and disease.

  Study EGAS00001005366

• Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing

  Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.

  Study EGAS00001003190

• NCI's Collection of Datasets for Health, Medical, and Biomedical Research Purposes

  This collection provides access to NCI's collections of datasets for the purpose of performing health, medical, or biomedical (HMB) research. This collection would not support ancestry lineage research not related to a specific medical or health conditions.

  Study phs003044

• Rapid Early Action for Coronary Treatment (REACT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: This multicenter controlled community study developed and evaluated the impact of a community educational intervention program on participant delay time from onset of symptoms of an acute myocardial infarction (AMI) to arrival at a hospital emergency department.Background: Although early reperfusion or thrombolytic therapy can reduce morbidity and mortality following an AMI, delayed access to medical care in participants is relatively common. Mean delay times from symptom onset to hospital arrival range from more than 4 hours to 24 hours, and the largest component of prolonged delay is participant recognition and action.Participants: A total of 20 communities from 5 field centers in the U.S. were pair-matched (10 pairs) according to geographic proximity and demographic characteristics. After initiation of a 4 month baseline surveillance period, one community in each pair was randomly selected to receive the intervention. The baseline surveillance period was followed by an 18 month community intervention and surveillance period. The community surveillance captured a total of 59,944 adults aged 30 years or older presenting to hospital emergency departments with chest pain, of whom 20,364 met study criteria for suspected acute coronary heart disease (CHD) at admission and discharged with a CHD diagnosis.Conclusions: Delay times were decreased in the intervention and reference communities. The results showed that the multicomponent community intervention program did not differentially reduce delay time from onset of AMI symptoms to arrival at a hospital, but did significantly increase the use of Emergency Medical Services by these participants in the intervention communities. (PMID:10872014).

  Study phs003885

• Data Access Committee for Maurice Lab - UMC Utrecht

  The Data Access Committee of the Maurice lab at the Center for Molecular Medicine, University Medical Center Utrecht, is responsible for reviewing and approving requests for access to controlled human transcriptomics and genomics data generated by the lab. The DAC ensures that data access requests are consistent with informed consent, ethical approvals, and applicable legal and institutional regulations, including GDPR.

  Dac EGAC50000000876

• International Verapamil SR/Trandolapril [INVEST] Genes Study

  INternational VErapamil SR-Trandolapril STudy (INVEST) was a prospective, multicenter, randomized, open-label, parallel-clinical trial that evaluated blood pressure response and adverse outcomes in patients randomized to either an atenolol-based or a verapamil SR-based hypertension treatment strategy in 22,576 patients with documented coronary artery disease and hypertension (PMID: 9809930,14657064). Hydrochlorothiazide and trandolapril were added as needed to achieve BP control or end organ protection in a protocol-defined manner. Briefly, the protocol required patients to be followed up at bassline, 6, 12, 18 and 24 weeks and then every 6 months thereafter until 2 years after the last patient was enrolled. At each visit, patients had BP and heart rate measured, clinical assessment performed, and additional antihypertensive medications added as needed to meet JNC VI blood pressure goals. The primary outcome was the first occurrence of all-cause death, nonfatal myocardial infarction (MI), or nonfatal stroke (clinicaltrials.gov identifier: NCT00133692). The genetic substudy of INVEST, INVEST-GENES, collected genomic DNA samples from 5,979 INVEST study participants. INVEST-GENES samples were genotyped on the Illumina OmniExpressExome GWAS chip. This data release includes 1529 samples that passed quality control including 657 whites, 537 Hispanics and 155 blacks. Two case-control subsets were created: one for the primary outcome of all-cause death, nonfatal MI or nonfatal stroke; the other one is for new-onset diabetes. Resistant hypertension was also evaluated in 1349 participants based on the medication use and blood pressure measurements at the visit prior to experiencing study outcomes or censoring (PMID:30237584).

  Study phs002319

• ITER-FIISC Data Access Committee (Sepsis)

  DAC for Whole-exome variant calling of individuals from the study of sepsis and acute distress respiratory syndrome in Spain.

  Dac EGAC50000000641

• Data Access Committee for Translational analyses from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  This DAC is responsible for request review and handling related to the study above.

  Dac EGAC50000000697

• Helse Bergen HF Data Access Committee for the MetBreCS trial dataset submitted to Federated EGA Norway

  This Data Access Committee is appointed by Helse Bergen HF to administer access requests for the MetBreCS trial dataset submitted to Federated EGA Norway.

  Dac EGAC50000000523

• GEOCODE data access policy

  The GEOCODE Data Access Policy ensures the responsible use, security, and compliance of GEOCODE data. Access to GEOCODE data is restricted to authorized users based on role-based permissions, ensuring compliance with data protection regulations.

  Dac EGAC50000000574

• WEHI AML Multiome Committee

  This committee oversees access to data generated as part of AML research study at WEHI, ensuring compliance with privacy regulations and ethical standards.

  Dac EGAC50000000912

• Wellcome Trust Sanger Institute

  Access to individual-level genotype data is available by application to the MalariaGEN Independent Data Access Committee. Access to data will be granted to qualified investigators for appropriate use. For further information information on data release policy and data access application form, please follow the link below.

  Dac EGAC00000000002

• PDAC Phenotype and Germline Genotype Data Access Committee

  This Data Access Committee (DAC) is responsible for reviewing and approving requests for access to controlled phenotype metadata and derived germline FUT2/FUT3 genotype data from patients with pancreatic ductal adenocarcinoma (PDAC). Access is granted to bona fide researchers for non-commercial research purposes only, subject to approval by the DAC and in accordance with the original informed consent and applicable ethical regulations.

  Dac EGAC50000000893