14382 results for ""Pennsylvania+German"+ACS+study+'Socius'+open+access"

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• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• DETECT-A NGS Data Batch 3

  This batch is a subset of the full DETECT-A dataset, containing 29294 fastq files generated from 3653 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001008597

• DETECT-A NGS Data Batch 2

  This batch is a subset of the full DETECT-A dataset, containing 498 fastq files generated from 71 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001008591

• DETECT-A NGS Data Batch 5

  This batch is a subset of the full DETECT-A dataset, containing 12740 fastq files generated from 3211 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001015426

• DETECT-A NGS Data Batch 1

  This batch is a subset of the full DETECT-A dataset, containing 43963 fastq files generated from 3024 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001008415

• DETECT-A NGS Data Batch 4

  This batch is a subset of the full DETECT-A dataset, containing 25210 fastq files generated from 3040 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001015360

• DETECT-A NGS Data Batch 6

  This batch is a subset of the full DETECT-A dataset, containing 9 fastq files generated from 8 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

  Dataset EGAD00001015458

• The data access committee for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  Dac EGAC00001003253

• The Nordic Centre of Excellence Programme in Molecular Medicine Data Access Committee

  Dac EGAC00000000006

• Data access agreement for ATRT

  Dac EGAC00001000306

• Data Access Commitee for Schulte-Schrepping et al., 2020: Severe COVID-19 is marked by a dysregulated myeloid cell compartment

  Dac EGAC00001001684

• DupiAERD DAC

  DAC to regulate access to RNA sequencing data of NERD patients with dupilumab treatment before and after aspirin provocation.

  Dac EGAC50000000273

• Linnarsson lab general data access committe

  Committee that handles the majority of policies for the Linnarsson Lab at Karolinska Institutet

  Dac EGAC50000000835

• Quick Guide for data submission

  Quick Guide This is a quick guide to submit data to the EGA. Please select data type to display the right detailed instructions. Sequence data Array-based data Get your submission account You first need to create your EGA user. Then, once your account has been verified by the Help Desk team, request your submission account and provide details of the data type and platform(s) in your submission. Register Study/DAC Use Submitter Portal to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the and upload it to your inbox using SFTP. Register experiments and runs Associate each data file to a registered sample and study by Linking files to samples. Details of the experimental procedure you followed must be provided. Finalise your submission Group your runs/analysis into datasets and link them to your new or existing DAC and policy using DAC Portal. Data request are done at a dataset level, thus files within a datasets must share release conditions. Release and admin When finalising the submission, set a released date to instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released. Get your submission account Fill the submission form and provide details of the data type and platform(s) in your submission. Register Study/DAC Use EGA Programmatic submission to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the EgaCryptor and upload it using default FTP clients or Aspera. Complete the Array-Format (AF) spreadsheet Download the AF spreadsheet and complete all four sections. Return the spreadsheet to the EGA helpdesk. Release and admin Instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released.

  Documentation submission/quickguide

• PLCO - Limited Use Pilot Test Data

  This is a sample of Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial data for limited use in a pilot test for remote data access. The PLCO is a randomized, controlled trial of screening tests for prostate, lung, colorectal and ovarian cancers. Approximately 155,000 participants were enrolled between November 1993 and July 2001. Participants were individually randomized to the control arm or intervention arm in equal proportions. Participants assigned to the control arm received usual care, whereas participants assigned to the intervention arm were invited to receive screening exams for prostate, lung, colorectal and ovarian cancers as outlined in the study protocol. The goal of the study was to assess whether these screening exams reduce mortality from prostate, lung, colorectal and ovarian cancers. Data were collected on cancer diagnoses and deaths from all causes that occurred through December 31, 2009. Median follow-up time was 12.4 years.

  Study phs002011

• Genomic Answers for Kids (GA4K)

  Identification of complex genetic variants including defects in gene regulatory circuits and uncharacterized genes present challenges for rare disease diagnosis. In Genomic Answers for Kids program we apply the joint interpretation of patient genome sequence with genomic endophenotypes to expand the clinically actionable genome among pediatric cases of suspected genetic disease. Our objective is to examine the role of novel and under-interpreted sequence variation by combining complete DNA sequences, personal epigenetic variations and massively parallel functional screens. To achieve this we perform augmented whole genome sequence (WGS) interpretation including reanalysis of clinical exomes as well as generating WGS for patients with negative exome results all be subject to family-based semi-automated recall pipeline to discover missed diagnostic variation. We use linked-read and long-read sequencing technologies to focus on putative structural variants missed in short-read genome and exome analysis by the optimized integration of linked and long read technologies that also improve identification of transmission patterns of all variants, as well as resolving genomic regions resistant to standard alignment. We also include tissue DNA sequencing to investigate somatic mosaicism. To further assist with WGS interpretation for uncommon variation we capture snapshots of patient transcriptomes and epigenomes in individual cells using single-cell RNA (scRNA) and sc open chromatin (scATAC) as well as bulk whole genome bisulphite genome sequencing for methylome interpretation. Alternative splicing is functionally assessed in available patient tissues using RNA-seq, including full length cDNA sequences by IsoSeq (PacBio) methodology. Our overarching goal is an increase rate of diagnostic genomic findings up to two-fold among rare disease, resulting in the majority (>50%) of patient cases resolved by the integrated system developed in our program.

  Study phs002206

• Genetic immune escape landscape in primary and metastatic cancer

  Immune surveillance escape is a hallmark of tumorigenesis1. Multiple studies have characterized the immune escape landscape across several untreated early-stage primary cancer types2–4. However, whether late-stage treated metastatic tumors present differences in genetic immune escape (GIE) prevalence and dynamics remains unclear. Here, we performed a pan-cancer characterization of GIE prevalence across six immune escape pathways in 6,457 uniformly processed Whole Genome Sequencing (WGS) tumor samples including 58 cancer types from 1,943 primary untreated patients and 4,514 metastatic patients. To effectively address the complexity of the Human Leukocyte Antigen (HLA-I) locus and to characterize its tumor status, we developed LILAC, an open-source integrative framework. We demonstrate that one in four tumors harbor GIE alterations, with high mechanistic and frequency variability across cancer types. GIE prevalence is highly consistent between primary and metastatic tumors for most cancer types with few exceptions such as prostate and thyroid carcinomas that have increased immune evasion frequencies in metastatic tumors. Positive selection analysis revealed that GIE alterations are frequently selected for in tumor evolution and that focal LOH of HLA-I, unlike non-focal LOH of HLA-I, tends to lose the HLA allele that presents the largest neoepitope repertoire. We also unraveled tumor genomic features contributing to immune escape incidence, including DNA repair deficiency, APOBEC activity, tobacco associated mutation load and viral DNA integration. Finally, there is a strong tendency for mid and high tumor mutation burden (TMB) tumors to preferentially select LOH of HLA-I for GIE whereas hypermutated samples favor global immune evasion strategies. Our results indicate that genetic immune escape is generally a pre-metastatic event during tumor evolution and that tumors adapt different strategies depending on their neoepitope burden.

  Study EGAS00001006123

• MethylationEPIC BeadChip samples of pre- and post-5ZA-treated head and neck cancer patients refractory to anto-PD-1 therapy

  Background Immune checkpoint blockade (ICB) is an effective treatment in a subset of patients diagnosed with head and neck squamous cell carcinoma (HNSCC); however, most patients are refractory. Methods In a non-randomized, open-label phase 1b clinical trial, participants with recurrent and/or metastatic (R/M) HNSCC were treated with low-dose 5’azacytidine (5’aza) daily for either 5- or 10-days in combination with fixed doses of durvalumab and tremelimumab after progression on ICB therapy. The primary objective was to assess the biologically effective dose of 5’aza as determined by molecular changes in paired baseline and on-treatment tumor biopsies; the secondary objective was safety. Results Thirty-eight percent (3/8) of participants with evaluable paired tissue samples had a greater than 2-fold increase from baseline in interferon-gamma (IFN-ɣ) signature and CD274 (programmed cell death protein 1 ligand, PD-L1) expression within the tumor microenvironment (TME), which was associated with increased CD8+ T cell infiltration and decreased infiltration of CD4+ T regulatory cells. The mean neutrophil-to-lymphocyte ratio (NLR) decreased by greater than 50%, from 14.2 (SD 22.6) to 6.9 (SD 5.2). Median overall survival (OS) was 16.3 months (95% CI 1.9, NA) and 2-year OS rate was 24.7% (95% CI: 4.5%, 53.2%) with 58% (7/12) of treated participants demonstrated prolonged OS of greater than 12 months. Conclusion Our findings suggest that low-dose 5’aza can reprogram systemic host immune responses and the local TME to increase IFN-ɣ and PD-L1 expression. The increased expression of these established biomarkers correlated with prolonged OS upon re-challenge with ICB.

  Study EGAS00001007998

• Prevention and Early Treatment of Acute Lung Injury (PETAL) Acetaminophen in Sepsis: Targeted Therapy to Enhance Recovery (ASTER) (PETAL ASTER-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. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL ASTER include plasma, urine and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: To determine whether acetaminophen increases days alive and free of organ dysfunction in sepsis participants compared with placebo.Background: Acetaminophen (paracetamol) has many effects that can be beneficial in sepsis treatment, including analgesia, antipyresis, cyclooxygenase-2 inhibition, as well as a potent and specific hemoprotein reduction that can block hemoglobin-induced oxidation of lipids and other substrates. The majority of sepsis participants experience elevated circulating cell-free hemoglobin levels, which is associated with development of organ dysfunction including acute respiratory distress syndrome (ARDS) and death.Acetaminophen has been found in observational studies to be associated with improved survival in critically ill sepsis participants with elevated plasma cell-free hemoglobin, and small clinical trials have had positive sepsis participant outcomes such as reduced plasma biomarkers of lipid peroxidation and improved kidney function. However, a large, randomized trial of acetaminophen administration for treatment of fever in participants with suspected infection did not show a mortality benefit. The NHLBI PETAL Network initiated ASTER as a larger phase trial to examine the utility of plasma cell-free hemoglobin level as a biomarker for future sepsis trials and whether acetaminophen would increase the number of days alive and free of organ support for participants with sepsis and respiratory or circulatory organ dysfunction. Participants: A total of 447 participants were enrolled and randomized, 227 to the acetaminophen arm and 220 to the placebo arm. Data from 40 participants who were randomized to the Vitamin C arm, which was stopped early (see Design section below), is also included.Design: ASTER was a phase 2b multicenter, randomized, double-blind trial. The study originally had a 3-arm platform trial in which participants were randomized 1:1:1 to treatment with intravenous acetaminophen, vitamin C, or a common placebo. The vitamin C arm of the trial was stopped after enrolling 79 participants due to external clinical trial data for vitamin C.Participants randomized to the acetaminophen arm received acetaminophen at the dose of 1 g in 100 mL diluent (or 15 mg/kg if actual body weight was Conclusions: Intravenous acetaminophen was considered to be safe but did not significantly improve days alive and free of organ support in critically ill sepsis participants. There was no significant interaction between cell-free hemoglobin levels and acetaminophen.

  Study phs003900

• University of Helsinki and Turku University Hospital Data Access Committee

  Dac EGAC00001001760

• This DAC is the list of persons that, on behalf of the UKBEC consortium, manage the access to the UKBEC data.

  Dac EGAC00001000314

• This agreement governs the terms on which access will be granted to the data generated by the United Kingdom Brain Expression Consortium.

  Dac EGAC00001001408

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001001884

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001002335

• Institute of Neuropathology - University of Freiburg Medical Center

  The Data Access Committee of the Institute of Neuropathology Freiburg.

  Dac EGAC50000000033