14659 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• CRITICS trial Whole Exome Sequencing (WES)

  Chemotherapy versus chemoradiotherapy after surgery and preoperative chemotherapy for resectable gastric cancer (CRITICS): an international, open-label, randomised phase 3 trial. Molecular characterisation of N=36 resectable gastric adenocarcinomas from CRITICS trial, describing mutations obtained by matched (Tumor-Normal) whole exome sequencing (WES). Samples are annotated for TCGA’s molecular classification (MSI, GS and CIN).

  Dataset EGAD50000001145

• The Genetics of Type 2 Diabetes Consortium (GoT2D): Low-Pass Sequencing and High-Density SNP Genotyping for Type 2 Diabetes

  The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome (Fuchsberger et al, 2016), and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in dbGaP will include all the Swedish, Finnish, and UK samples, but the German data will be deposited in the European Genome-phenome Archive (EGA), by virtue of the project specific funding requirements.

  Study phs000840

• Nouscom Data Access Committee

  The Data Access Committee reviews and approves data access requests for "WES Analysis of precancerous lesions in Lynch Syndrome" study, ensuring compliance with participants’ consent and institutional ethical regulations.

  Dac EGAC50000000784

• Single cell multi-omic study of H3-K27M mutant diffuse midline glioma across age and location

  Histone 3 lysine27-to-methionine (H3-K27M) mutations most frequently occur in childhood diffuse midline gliomas (DMGs) of the pons, but are also increasingly recognized in adult DMGs. Their potential heterogeneity at different ages and midline locations are vastly understudied. Here, through dissecting the single-cell transcriptomic, epigenomic and spatial architectures of a comprehensive cohort of patient H3-K27M DMGs, we delineate how age and anatomical location shape glioma cell-intrinsic and -extrinsic features in light of the shared driver mutation. We conducted multi-omic profiling of 50 H3-K27M mutant patient tumors. We performed deep full-length Smart-seq2 fresh single-cell (n=18) or frozen single-nucleus (n=25) RNA-sequencing (sc/snRNA-seq) of 43 tumors). We additionally analyzed the open chromatin profiles of 8 tumors utilizing the single-cell/nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq)

  Study EGAS00001006994

• A Platform Study of Combination Immunotherapy for the Neoadjuvant and Adjuvant Treatment of Patients with Surgically Resectable Adenocarcinoma of the Pancreas

  This is a single-institutional, randomized, open label platform clinical trial testing various immunotherapy combinations. Patients with newly diagnosed and surgically resectable pancreatic ductal adenocarcinoma (PDA) and scheduled to undergo the Whipple procedure at Johns Hopkins Hospital were eligible to participate in this study. Criteria for determining resectability strictly followed National Comprehensive Cancer Network (NCCN) guidelines. The study consisted of 6 parts: parts 1-5 constituted the Prime Phase (see below), and part 6 was the Extended Treatment Phase. Part 1: Participants received one cycle of immunotherapy two weeks prior to undergoing the Whipple procedure. Part 2: Subjects underwent the Whipple procedure. Part 3: Subjects received a second cycle of immunotherapy 4-10 weeks following the Whipple procedure (2-4 weeks prior to adjuvant chemoradiation). Part 4: Subjects underwent chemoradiation. Part 5: Subjects received 4 additional 28-day cycles of immunotherapy beginning 1-2 months after completing chemoradiation for a total of six cycles (two before chemoradiation and 4 following chemoradiation). Eligible subjects were randomized to Arms A and B in a 1:1 ratio, stratified up-front by age (≤65, >65). Arm A participants received Cy/GVAX. Arm B participants received the combination of Cy/GVAX and nivolumab. GVAX Vaccine consists of equal numbers (2.5 x 108 each) of Panc 6.03 pcDNA1GM-CSF and Panc 10.05 pcDNA1GM-CSF combined into a single vaccination. Each vaccination consisted of six total intradermal injections. A single intravenous (IV) dose of 200 mg/m2 Cy (CytoxanR) was given one day prior to GVAX. Anti-PD-1 Therapeutic Antibody Nivolumab 480 mg every 4 weeks was administered as an intravenous infusion. The primary objective for Arms A and B was to compare IL17 expression (Th17) in vaccine-induced lymphoid aggregates between resected PDAs from patients treated with the combination of Cy/GVAX and anti-PD-1 blockade antibody vs. the treatment of Cy/GVAX alone. Secondary objectives were to assess the safety, overall survival (OS), and disease free survival (DFS) of patients treated with each of the study drug combinations, and to assess the effects of each of the immunotherapy study drug combinations on PD-L1/PD-1 associated pathways, vaccine-induced immune regulatory signatures, and peripheral and intratumoral antigen specific T cell responses. The exploratory objective was to explore the effects of therapy on tumor and peripheral blood and tumor infiltrating immune cells, and to explore potential molecular determinants of response, progression and disease stability. To these ends, tumor infiltrating immune cells (TIICs) were obtained from surgically resected tumors following the neoadjuvant treatment of the study immunotherapy. TIICs were sorted into CD3+CD4+ T cells, CD3+CD8+ T cells, CD3-CD19+ B cells, and CD3-CD19-CD11b+ myeloid cells by flow cytometry. The sorted immune cell subtype pellets were sent to the commercial vendor (Eurofins) for RNA extraction and sequencing. SMART-seq v4 Ultra Low Input mRNA Sample Prep Kit was used for library preparation with 100bp paired end reads. FASTQ files, that were returned from the vendor, are deposited here.

  Study phs003002

• Center for Craniofacial and Dental Genetics: Exome Sequencing of Orofacial Cleft Families

  Orofacial Clefts (OFCs) are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans. Affect about 1 in 800 newborns, OFCs are also one of the most common structural birth defects worldwide. OFCs can impose a substantial personal cost resulting from the associated emotional and financial burden. On average a child undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Individuals born with an OFC have higher infant mortality (especially in developing countries with limited access to care), higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genetic studies have focused on the contribution of common genetic variants through genome-wide linkage and association studies. These studies have revealed a significant etiologic heterogeneity. One promising approach to dissect the etiology of OFCs into focus on subclinical phenotypic features present in the non-cleft family members of affected individuals. These subclinical features are subtle phenotypic features that may represent mild manifestations of the same risk genes; thus, their inclusion in family-based studies may clarify the inheritance patterns in OFC families. In this project, we conducted whole exome sequencing in multiplex families with both overt OFCs and subclinical phenotypes to identify high-impact genes causing OFCs.

  Study phs001675

• AmsterdamUMC Data Access Committee for the study "Multi-omic analysis of thyroid dysfunction in Down Syndrome"

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired as part of the "Multi-omic analysis of thyroid dysfunction in Down Syndrome" study as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000186

• Whole_Genome_Sequencing_of_hiPS_cells

  Human induced pluripotent stem (hiPS) cells hold great promise for regenerative medicine. Safety issues of use of hiPS cells however remain to be addressed. One of such issues is mutations derived from somatic donor cells and introduced during genome manipulation. We sequence whole genomes of hiPS cells and analyzed mutations. Our study brings hiPS cell technology one step closer to application to regenerative medicine.

  Study EGAS00001000008

• The genomic landscape of acute lymphoblastic leukemia with intrachromosomal amplification of chromosome 21

  Use single cell whole genome sequencing data from one iAMP21 patient SJBALL021901 to study the clonal evolution of iAMP21.

  Study EGAS00001006796

• Asan Medical Center Data Access Committee

  Asan Medical Center Data Access Committee for BRISK study.

  Dac EGAC50000000733

• Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment. From April 2017 to April 2021, 302 samples of 253 patients were included. Comprehensive molecular profiling utilizing lcWGS, WES, RNAseq, Affymetrix, and/or 850k methylation profiling was performed for 226 samples. Germline pathogenic variants were identified in 16% of patients. At least one somatic alteration was detected in 204 (90.3%), and 185 (81.9%) were considered druggable, with priority levels very high (6.1%), high (21.3%), moderate (26.0%), intermediate (36.1%), and borderline (10.5%). Diagnosis was revised or refined in 8 patients (3.5%). Spatial and temporal heterogeneity was observed in paired samples of 15 patients, indicating the value of sequential analysis. Of 137 patients with follow-up beyond 12 months, 21 molecularly matched treatments were applied in 19 patients (13.9%) with modest response. Most relevant barriers to not applying targeted therapies included poor performance status, as well as limited access to drugs within clinical trial. iTHER demonstrates feasibility of comprehensive molecular profiling across all ages, tumor types and stages in pediatric cancers, informing of diagnostic, prognostic, and targetable alterations as well as reportable germline variants within a clinically relevant timeframe. Therefore, WES and RNAseq is implemented into standard clinical care at the Princess Máxima Center for all children. Improved access to targeted treatments within biology-driven combination trials is required to eventually improve survival.

  Study EGAS00001007099

• BLUE CORAL: Biology and Longitudinal Epidemiology of PETAL COVID-19 Observational Study

  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.Available Data: Long Term Follow-up data has been added with version 2. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL BLUE CORAL include: Bronchial Lavage, Plasma, Tracheal Aspirate, Urine, Whole Blood Buffy Coat, DNA, Plasma, Serum, Urine, and Whole Blood. Please note that use of biospecimens is tiered for both non-genetic and genetic research.Objectives: To measure the incidence and changes over time in symptoms, disability, and financial status after COVID-19–related hospitalization.Background: For many individuals, the effects of COVID-19 persist after the acute phase and result in prolonged symptoms and disability. This has led to widespread efforts to characterize the epidemiologic characteristics of such post-COVID-19 sequelae. However, accurate data were limited, hindering the ability to counsel patients, caregivers, and policy makers and to plan relevant recovery-focused clinical research. Thus, the BLUE CORAL study was intended to address the knowledge gaps and provide critical data to help guide clinical care, public health, and scientific efforts.Participants: A total of 1376 COVID-19 patents were enrolled, with 825 (444 male, and 379 female) that completed at least one follow-up survey.A subset of the BLUE CORAL adult participants were enrolled in the extension study, FIRE CORAL. FIRE CORAL was a multicenter prospective cohort study of participants recovering from COVID-19 disease after discharge from the hospital. Design: BLUE CORAL was a prospective cohort study. Participants were enrolled between August 24, 2020, and July 20, 2021, with follow-up occurring through March 30, 2022. Posthospital surveys were administered by trained interviewers in English or Spanish to patients or their proxies at 1, 3, and 6 months after enrollment. Cardiopulmonary symptoms were assessed using the Airways Questionnaire 20, the Kansas City Cardiomyopathy Questionnaire, and the Seattle Angina Questionnaire. Fatigue was assessed using the Patient Health Questionnaire-9. Disability was assessed by self-report of limitations in activities of daily living (ADLs) or instrumental activities of daily living (IADLs). Financial problems were assessed using the World Health Organization Disability Assessment Schedule 2.0 question and questions regarding job changes, time off work, and insurance coverage developed with the Mi-COVID-19 study using qualitative interviews. Quality of life was measured using the European Quality of Life 5-dimension 5-level instrument.The primary outcomes were new or worsened cardiopulmonary symptoms, financial problems, functional impairments, perceived return to baseline health, and quality of life. Symptoms that were not present before hospitalization or specifically reported as increased in severity were counted as new or worsened. Conclusions: The findings of this cohort study of people discharged after COVID-19 hospitalization suggest that recovery in symptoms, functional status, and fatigue was limited at 6 months, and some participants reported new problems 6 months after hospital discharge.

  Study phs003419

• Genomic Data Access Committee for Early and Late Onset Colorectal Cancer Study

  This Data Access Committee (DAC) manages access to genomic data generated from the study "A Clinically and Genomically Annotated Early Onset Colorectal Cancer and Late Onset Colorectal Cancer." The study focuses on identifying the distinct genomic profiles of early-onset colorectal cancer (EOCRC) compared to late-onset colorectal cancer (LOCRC) through whole-genome sequencing (WGS) of both tissue and blood samples. The DAC is responsible for reviewing and approving access requests from researchers who wish to utilize this data for non-commercial, academic purposes related to colorectal cancer research. The committee ensures that all data access is granted in compliance with ethical standards and that the data is used solely for the approved research objectives. Researchers requesting access to this data must provide a detailed research proposal, institutional review board (IRB) approval, and demonstrate relevant expertise in genomic research. All data will be stored in secure, encrypted environments, and any further sharing or use of the data requires additional DAC approval.

  Dac EGAC50000000359

• Accelerating Medicines Partnership-Systemic Lupus Erythematosus (AMP-RA/SLE)

  This project is analyzing tissue and blood samples from people with rheumatoid arthritis (RA) and lupus to pinpoint genes, proteins, chemical pathways, and networks involved at a single cell level. This type of modular, molecular analysis will allow comparisons across the diseases and will provide insights into key aspects of the disease process. The project will identify differences between those RA patients who respond to therapies and those who do not, as well as provide a better systems level understanding of disease mechanisms in both RA and lupus. This knowledge is essential for the development of targeted therapies and for the application of existing and future therapies to appropriate patient populations. Additional datasets can be accessed through ImmPort (http://www.immport.org/immport-open/public/home/studySearch), accession: SDY997

  Study phs001459

• Accelerating Medicines Partnership-Rheumatoid Arthritis (AMP-RA/SLE)

  This project is analyzing tissue and blood samples from people with RA and lupus to pinpoint genes, proteins, chemical pathways, and networks involved at a single cell level. This type of modular, molecular analysis will allow comparisons across the diseases and will provide insights into key aspects of the disease process. The project will identify differences between those RA patients who respond to therapies and those who do not, as well as provide a better systems level understanding of disease mechanisms in both RA and lupus. This knowledge is essential for the development of targeted therapies and for the application of existing and future therapies to appropriate patient populations. Additional datasets can be accessed through ImmPort (http://www.immport.org/immport-open/public/home/studySearch), accession: SDY998, SDY999.

  Study phs001457

• Whole_genome_sequence_of__third_generation_family_member__SFHS_

  Previously we performed deep WGS on 6 parents and 13 children from 3 large families from the Scottish Family Health Study to identify de novo mutations. This prelim is cover the additional sequencing of one grandchild from one of these three families. The inclusion of a third generation individual will provide additional experimental validation for the de novo mutations found in the initial trio. As in the previous study, the DNA will be WGS to a depth of approximately 25X to achieve this purpose.

  Study EGAS00001000429

• AmsterdamUMC Data Access Committee for the EPIC-CD study

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired as part of the EPIC-CD project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000097

• Single molecule molecular inversion probe capture developed using the CIViC database

  This study evaluated the use of the Clinical Interpretations of Variants in Cancer database (CIViC) to develop an Open-sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP is a resource that allows users to develop a clinical capture panel that can be linked back to clinical summaries within the CIViC database. This method for capture panel development and variant annotation was tested using 27 cancer samples from 5 tumor subtypes with original exome or genome sequencing. Specifically, using OpenCAP, 111 variants were identified as relevant for the capture panel and 2,027 smMIPs were designed to target these variants. The smMIPs panel design was employed on all samples to validate the capture panel design. When compared to original sequencing, the CIViC smMIPs capture panel demonstrated a 95% sensitivity for variant detection (n = 61 variants). Additionally, the CIViC smMIPs capture panel identified 182 additional clinically relevant variants that had been missed on original sequencing.

  Study phs001890

• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Single cell atlas of human glioma

  We profiled 87 primary-recurrentpatient-matched paired GBM specimens with single-nucleus RNA and bulk-DNA sequencing and single-cell open-chromatin and spatial transcriptomics/proteomics assays. We found that recurrent GBMs are characterized by a shift to a mesenchymal phenotype in response to therapy

  Dataset EGAD00001008811

• A Pilot Study of Neoadjuvant Nivolumab, Ipilimumab and Intralesional Oncolytic Virotherapy for HER2-Negative Breast Cancer

  This study was a single arm phase 1 trial that assessed the regimen safety and feasibility as well as tumor response in patients with localized HER2-negative breast cancer treated with talimogene laherparepvec (T-VEC) in combination with nivolumab and ipilimumab. The primary objective was to evaluate the safety and adverse event profile of this treatment combination. Six patients were enrolled, four having relapses after prior neoadjuvant chemotherapy, and two who were previously untreated. One patient had a pathological complete response, three patients had pathological partial responses, one showed no significant response, and one had disease progression. Biopsies demonstrated increased immune cell infiltration in samples from patients who responded to therapy. In this study, the checkpoint blockade immunotherapy combined with T-VEC provided responses in patients with advanced or relapsed HER2-negative breast cancer at the expense of long-term toxicities.

  Study phs003316

• AmsterdamUMC Data Access Committee for the MAPS study

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired from the MAping the Peritoneal immune System (MAPS) project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000096

• 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)

  Study EGAS00001000946

• Experimental PfSPZ Vaccine in Adults Without Malaria

  The study was performed to evaluate whole-blood transcriptomic profiles via RNA-seq before, during, and after immunization with the PfSPZ Vaccine in malaria-naïve, healthy adults enrolled in VRC 312 (NCT01441167). VRC 312 was the second study of the PfSPZ Vaccine and the first study to evaluate intravenous (IV) administration of this vaccine. The study was an open-label evaluation of the safety, tolerability, immunogenicity, and protective efficacy of the vaccine at successively higher administered by the IV route. The highest dosages were evaluated for protection against a malaria challenge after 4 to 6 vaccinations. The primary objectives of the study were related to the safety and tolerability of the vaccine at the 4 different dosage levels when administered IV; the secondary objectives were related to PfSPZ vaccine-mediated protection against Plasmodium falciparum (Pf) challenge at the 3 higher dosage levels, and the exploratory objectives were related to the immunogenicity of the PfSPZ Vaccine and defining an immune correlate of protection. To further determine potential molecular correlates of immunogenicity and/or protection, RNA-seq was performed on whole blood collected from subjects in all dose groups at time points before, during, and after immunization.

  Study phs002422

• Losartan Effects on Emphysema Progression (LEEP-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 To evaluate the efficacy of losartan, an angiotensin receptor blocker, to reduce emphysema progression in patients with COPD and mild to moderate emphysema. Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease comprising chronic bronchitis and emphysema. COPD is a major cause of morbidity and mortality. Smoking cessation slows the progression of the disease, and bronchodilators can provide sustained improvement in lung function, but there are no pharmacologic agents that clearly modify emphysema progression. Angiotensin receptor blockers (ARBs) have been suggested as potential drugs to slow the progression of COPD. A few trials have shown that patients treated with ARBs had slower progression of radiographic emphysema. The LEEP study was initiated to test the hypothesis that the ARB losartan would reduce the progression of emphysema in patients with COPD with mild to moderate emphysema.ParticipantsA total of 220 participants were enrolled. 108 participants were randomized to receive losartan, and 112 participants were randomized to receive the placebo.Design LEEP was a randomized, placebo-controlled multicenter trial. Participants were randomly assigned (1:1) to receive losartan or placebo. The dose was 50 mg losartan or placebo given as one capsule daily for 2 weeks, and, if well tolerated and the systolic blood pressure was >90 mm Hg, it was increased to two capsules. Participants and site investigators were masked to treatment assignment. Participant responses to the St George's Respiratory Questionnaire, the modified Medical Research Council dyspnea scale, the COPD Assessment Test, and the Physical Function–Short Form 20a were collected. The number and severity of COPD exacerbations were recorded. COPD exacerbations were defined as two or more new or worse symptoms for ≥3 days and classified by treatment as mild (neither antibiotics nor oral steroids), moderate (an antibiotic or oral steroid), or severe (hospitalization). The primary outcome measure was the change in quantitative whole-lung emphysema score after 48 weeks measured by the percentage of lung voxels less than -950 Hounsfield units (PCT950) on full inspiratory HRCT. Conclusions Losartan does not prevent progression of emphysema in patients with COPD who have mild to moderate pulmonary emphysema.

  Study phs004313

• Genomic characterization of 9p- syndrome

  We characterized the precise genomic breakpoints of the complex structural variant associated with 9p- syndrome in one individual.

  Study phs002054

• Cholesterol and Pharmacogenetics (CAP) Study

  The Cholesterol and Pharmacogenetics Study was a 6-week open label, non-randomized study of 40mg/day simvastatin treatment in 335 black and 609 white (944 total) men and women. Plasma lipids and lipoproteins were measured on two occasions prior to treatment and at 4 and 6 weeks of treatment. The study was designed to test for genetic associations with baseline measurements and changes in response to simvastatin treatment. Whole genome genotyping was performed on 592 white CAP study participants in two stages. In Stage 1, 304 were genotyped for 314,621 SNPs to tag for common genomic variation. In Stage 2, 290 participants were genotyped, including 280 who were genotyped for 620,901 SNPs. Two samples were excluded due to gender discrepancies. More recently, CAP self-reported black participants were genotyped on Illumina Omni2.5Exome chips. PolyA-selected strand-specific RNA-seq libraries were generated in several batches from lymphoblastoid cell lines (LCLs) derived from 268 white and 165 black CAP participants. The LCLs were exposed to sham buffer (control) or 2 uM activated simvastatin for 24 hours, producing a total of 866 100/101 bp paired end RNA-seq libraries sequenced on Illumina HiSeq 2000 machines.

  Study phs000481

• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• Intellectual Disability cases with parents (trios) or affected sibs (sibpairs)

  Samples from ID cases negative for CNV through array-CGH were submitted to exome sequencing. Families with one affected individual underwent trio exome sequencing for identification of de novo variants. Families with more than one affected child underwent sibpair sequencing for identificatio of shared recessive or x-linked variants.

  Study EGAS00001003968

• Smart-seq3 scRNA-seq of cells from primary (OV2295) and metastatic (OV2295R2) high-grade serous ovarian cancer cell-line

  In this project, single cells extracted from two high-grade serous ovarian cancer cell-lines, one primary (OV2295) and one metastatic (OV2295R2), where split into two 384 well plates and libraries were prepared using Smart-seq3 single cell RNA sequencing (Hagemann-Jensen et al, 2020).

  Study EGAS00001006868

• An Atlas of Cells in the Human Tonsil

  Palatine tonsils are secondary lymphoid organs representing the first line of immunological defense against inhaled or ingested pathogens. Here, we provide a comprehensive census of cell types forming the human tonsil by applying single cell transcriptome, epigenome, proteome and adaptive immune repertoire as well as spatial transcriptomics, resulting in an atlas of >350,000 cells. We provide a glossary of over one hundred annotated cell types and states, and disentangle gene regulatory mechanisms that drive cells through specialized lineage trajectories. Exemplarily, we stratify multiple tonsil-resident myeloid slancyte subtypes, establish a distant BCL6 superenhancer as locally active in both follicle-associated T and B cells, and describe SIX5 as a potentially novel transcriptional regulator of plasma cell maturation. Further, our atlas is a reference map to understand alterations observed in disease, here we discover immune-phenotype plasticity in tumoral cells and microenvironment shifts of mantle cell lymphomas (MCL). To facilitate such reference-based analysis, we develop HCATonsilData and SLOcatoR, a computational framework that provides programmatic and modular access to our dataset; and allows the straightforward annotation of future single-cell profiles from secondary lymphoid organs.

  Study EGAS00001006375

• Whole-genome sequencing data for inflammatory breast cancer patients

  This study reports the whole-genome sequencing data for 20 inflammatory breast cancer patients, each of whom has one normal blood sample and one breast tumor sample. Overall, there are 40 files included in this study, in the format of BAM.

  Dataset EGAD00001005749

• Evolutionary Analysis of Chronic Lymphocytic Leukemia Cells During Relapse After Allogeneic Hematopoietic Stem Cell Transplant

  We investigated the molecular dynamics driving relapse of chronic lymphocytic leukemia (CLL) following allogeneic hematopoietic stem cell transplant (allo-HSCT) through an integrated analysis of whole exome, bulk transcriptome, bulk methylome and single cell transcriptional data from paired leukemic samples representing 19 patients. We found that their clinical kinetics corresponded to distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are distinct from those imposed by chemotherapy.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out ribosome profiling (Ribo-seq) and RNA-sequencing on CLL samples and isolated primary B cells from healthy donors. We discovered novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001998

• The EGA Helpdesk team: 2025 in review and what we are building next

  Behind every dataset submitted, every access request processed, and every technical question answered, there is a team working quietly to keep things moving: the Helpdesk (HD). With the onset of 2026, this feels like the right moment to look back on what 2025 has been like for the HD team: the challenges we faced, how we adapted, and where we're heading next. Why the Helpdesk matters to EGA The EGA Helpdesk is more than a support channel. It plays a key role in maintaining trust in the EGA ecosystem. By supporting data submitters, researchers, Data Access Committees (DACs), and institutional partners, the HD helps ensure that data can flow securely, efficiently, and reliably. When issues arise, the Helpdesk is often the first place where their impact is felt and addressed. In that sense, the HD sits at the intersection of technology, policy, and people. One Helpdesk, two locations, one shared mission The EGA Helpdesk is a joint, distributed team working closely across two locations: CRG (Barcelona, Spain) and EMBL-EBI (Cambridge, UK). Although we are based in different institutions, we operate as a single Helpdesk, with shared workflows, priorities, and responsibility towards users. At CRG, the HD team is formed by: Andrea Max Àlex and me At EMBL-EBI, we work closely with: Silvia Coline Aravind What defines us as a team is simple: we work user-first, even under pressure. In a highly technical environment, clarity, empathy, and consistency matter just as much as tools and processes. A close collaboration across sites is essential to making that happen. What does the EGA Helpdesk do? The HD supports users across the full lifecycle of data in EGA. This includes: Data submissions, uploads, and encryption workflows. Data access requests and permissions. Questions around policies, consent, and data usage. Technical and system-related issues. Coordination between users, internal teams, and external partners. 2025: growth, change, and recalibration 2025 was a year of growth, but not always a predictable one. Early in the year, several technical and system-related challenges required us to adjust our original plans. Priorities shifted, timelines changed, and some improvements had to be rethought. For the HD team, this is often the hardest part of the job: we see delays through the eyes of users and understand the real impact they can have on ongoing research. One of the key lessons from 2025 was that stability is not only a technical challenge, but also an organisational one. Teamwork proved to be essential: anticipating peak periods, sharing context early, and coordinating closely across teams made a tangible difference. When things became complex, working together across roles and locations was what allowed us to keep moving forward. In 2025, the Helpdesk received 5.313 tickets and resolved 5.511 requests, reflecting both increased adoption of EGA and the team’s ability to absorb higher demand. At the same time, demand continued to grow. Compared to 2024, ticket creation increased by over 6%, while resolution capacity grew by more than 11%. The team not only kept up with incoming requests but also resolved part of the accumulated backlog, finishing the year having solved more tickets than were created. The real challenge of 2025 was not overall performance, but how the workload was concentrated during peak months. Seasonality and demand spikes placed pressure on the system, even while overall efficiency remained strong. On a team level, 2025 was also a year of transition. I joined the HD leadership role in January 2025, stepping into a period of change and rapid learning. Later in the year, in October, we said goodbye to Raül, and in January 2026, we welcomed Àlex, strengthening the team for the next phase. What users needed most in 2025 While requests vary widely, some themes stood out throughout the year: Support with data submissions and uploads Data access requests and permissions Technical and system-related issues As EGA matures, day-to-day operations have become more complex. Many long-running tickets are not delayed due to a lack of follow-up, but because they depend on external approvals, cross-institutional coordination, or multi-step processes. Understanding these patterns helps us focus not just on resolving tickets, but on improving how work flows through the system. Looking ahead to 2026 With a reinforced team and clearer insights from 2025, our focus for 2026 shifts from throughput to flow. Key priorities include: Strengthening our web content and documentation Reducing structural backlog Improving cross-team and cross-system coordination Anticipating peak demand earlier and planning capacity accordingly Challenges will continue to arise in 2026, as they always do. However, 2025 reinforced something important: a stable, empathetic, and well-aligned Helpdesk team is essential to supporting EGA's mission at scale. Supporting users well means supporting research, and that remains at the core of what we do.

  Blog ega-helpdesk-team-2025-in-review-and-upcoming-improvements

• DCCT/EDIC Epigenetics (DNA Methylation) Study

  Metabolic memory (persistent benefits of early glycemic control on preventing/delaying diabetic complications development) was observed in the Diabetes Control and Complications Trial (DCCT) and follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study, dbGaP phs000086.v3.p1, but mechanisms are unclear. We investigated the involvement of epigenetic DNA methylation (DNAme) by examining its associations with preceding glycemic history, and subsequent complications development over 18 years in blood DNAs of 499 randomly-selected DCCT/EDIC participants with type 1 diabetes. We found associations between DNAme near DCCT-closeout and mean-DCCT-HbA1c at 186 CpGs (FDR<15%, including 43 at FDR<5%), many located in complications-related genes. These CpGs are enriched in C/EBP motifs, enhancer/transcription regions in blood cells/progenitors, and open chromatin-states in myeloid cells. Remarkably, several CpGs in combination explain 68-97% of the mean-DCCT-HbA1c risk of complications development during EDIC. DNAme at key CpGs appears to mediate the association between hyperglycemia and complications in metabolic memory, through modifying myeloid cell enhancer activity.

  Study phs002024

• A Phase III Randomized Study of Nivolumab Plus Ipilimumab Versus Nivolumab in Stage IV Squamous Cell Lung Cancer

  Lung-MAP (S1400, NCT02785952) was a multicenter, open-label, phase III randomized clinical trial. The Lung-MAP-I substudy (S1400I) was conducted from December 2015 to April 2018, through the National Clinical Trials Network and led by the SWOG Cancer Research Network. The trial compared nivolumab plus ipilimumab (nivo+ipi) with nivolumab monotherapy (nivo) in patients with chemotherapy-pretreated, immunotherapy-naïve, advanced squamous non-small cell lung carcinoma (sqNSCLC). Two hundred fifty-two patients were randomly assigned to receive nivo+ipi (n = 125) or nivo (n = 127). The clinical efficacy endpoints were overall survival, progression free survival, duration of response, and best objective response by RECIST 1.1. Multi-omic translational analysis was performed in collaboration with the the CIMAC–Cancer Immunologic Data Commons (CIDC) Network using available tumor tissue samples and blood samples (n = 160) submitted for Lung-MAP screening and provided by the SWOG tissue bank.

  Study phs003412

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• The Dutch Microbiome Project: Defining the (un)healthy gut microbiome

  The Dutch Microbiome Project (DMP) data includes raw data generated by shotgun metagenomic sequencing of faecal samples of 8,208 Dutch individuals, processed microbiome data analysed using Biobakery2 tools (including taxonomy, pathway, virulence factors and antibiotic resistance gene profiles), and basic phenotypes (age and sex, BMI). Data is made available in two randomly assigned batches to facilitate the data access and maintenance. Access to this dataset requires a minimal access procedure (data access form at https://forms.gle/eHeBdXJMXbVvCJRc8 or email request to the data access committee (DAC) of this study, listed at DAC EGAC00001001996, https://ega-archive.org/dacs/EGAC00001001996). This access procedure is to ensure that the data is being requested for research/scientific purposes only and thus complies with the informed consent signed by Lifelines participants, which specifies that the collected data will not be used for commercial purposes. Submitted data access forms will be evaluated by the DAC and Lifelines, and a response to requests will be given within two weeks. For requests from verified academic parties, access will be given without further delay. For requests from commercial parties, Lifelines will perform a pre-DPIA (Data Privacy Impact Assessment) to assess the risks of the proposed processing of personal data (e.g. purpose, storage, access, archiving, etc.) with respect to the GDPR (EU privacy laws) subject rights. Based on the outcome of the pre-DPIA, Lifelines will decide whether sharing data with the commercial entity is allowed and/or whether additional measures have to be taken.

  Study EGAS00001005027

• Data for Paper: Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  mRNA, total RNA, small noncoding RNA, NOMe-Seq and DNase-Seq data from following samples (not every Sequencing Type for every sample): 01_HepG2_LiHG_Ct1 41_Hf01_LiHe_Ct 41_Hf02_LiHe_Ct 41_Hf03_LiHe_Ct 51_Hf03_BlCM_Ct 51_Hf04_BlCM_Ct 51_Hf03_BlEM_Ct 51_Hf04_BlEM_Ct 51_Hf03_BlTN_Ct 51_Hf04_BlTN_Ct Metadata available at deep.dkfz.de

  Dataset EGAD00001002735

• NEC

  This multi-centre, non-randomized, open-label, phase II trial (NCT03016338), assessed niraparib monotherapy (cohort 1, C1), or niraparib and dostarlimab (cohort 2, C2) in patients with recurrent serous or endometrioid endometrial carcinoma. The primary endpoint was clinical benefit rate (CBR). Secondary outcomes were safety and objective response rate (ORR). Translational research was an exploratory outcome. Potential biomarkers were evaluated in archival tissue by immunohistochemistry and next generation sequencing panel. Feasibility of liquid biopsy by ctDNA was assessed.

  Dataset EGAD00001010056

• FHS-Net Social Networks

  Note: Data Use Restrictions: The data must only be used for genetic research projects solely in the area of health-related social-network research. This study compiles detailed information on family and social ties linked to participants in the offspring cohort of the Framingham Heart Study. The investigators took computerized information from self-report data used by the FHS for over 30 years to facilitate health exam scheduling. These tracking sheets asked participants to identify people close to them, which were assumed by the investigators to indicate a social tie. Individuals are listed as "egos" (if the ties are from their perspective) and/or "alters" (if they are linked as a friend or family members to one of the other participants). All egos were FHS offspring participants while alters could be FHS participants in any cohort or non-participants. This information was combined with internal FHS pedigree data on family ties to list family member alters (as well as the nature of their relationship). The resultant dataset therefore includes each ego-alter tie, the nature of their relationship and the start and end dates for their ties for each of seven waves for the offspring study. Due to privacy concerns, all exam dates for individuals are listed relative to the initial FHS exam date. The study investigators chose a random, confidential date, to which all initial exam dates are linked (by number of months from random date to initial exam date). With this information, researchers can have access to the temporal relationships among participants' exam dates while remaining unaware of the actual exam dates for individual participants. During each clinic exam cycle, the participants undergo a detailed examination including physical examination, medical history, laboratory testing, and electrocardiogram. Over the years, other tests (that may not be performed at every exam cycle) have included pulmonary function, lifestyle, physical function, cognitive function questionnaires, and various noninvasive cardiovascular tests including echocardiograms. This study involves phenotypic data from these exams including (when available) basic body measurements (height, weight, blood pressure), laboratory values (blood sugar levels, LDL levels), information on smoking and alcohol use, and tests of depression and cognitive functioning. Important links to apply for individual-level data Data Use Certification Requirements (DUC) Instructions to Request Authorized Access Apply here for controlled access to individual level data Participant Protection Policy FAQ In 1948, researchers recruited men and women from the town of Framingham, Massachusetts, beginning the first round of extensive physical examinations and lifestyle interviews that would later be analyzed for common patterns related to CVD development. Initially, the Framingham Heart Study enrolled 5,209 men and women from the Framingham area who were between the ages of 28 and 62 years. Beginning in 1971, the Framingham Heart Study enrolled 5,124 men and women, who were either offspring of the original cohort or spouses of those offspring. In 2002, 4,095 third generation participants (men and women) were enrolled.

  Study phs000153

• Pilot study of adoptive cell therapy using cultured tumor infiltrating lymphocytes for Japanese melanoma patients refractory to immune-checkpoint inhibitors

  To evaluate feasibility of the adoptive cell therapy (ACT) using tumor infiltrating lymphocytes (TIL) in Japanese melanoma patients who failed the immune checkpoint inhibitors (ICIs) and investigate the immune components and immunologic milieu within the pretreatment tumor and expanded TILs from there.?Three patients whose clinical subtype were mucosal, superficial spreading, and acral melanoma were treated and the all completed the TIL-ACT. Clinical response were one short-partial response, one relatively long-stable disease, and one progression disease. Whole-exome and transcriptional analysis of pretreatment tumor revealed the various?immunophenotypes including tumor mutation burden with immunogenic neoantigens and upregulation of immunosuppressive gene signatures.

  Study JGAS000249

• The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

  In this study, we characterized 24 rheumatoid arthritis (RA) synovial tissue chromatin classes (i.e., cell states defined by chromatin accessibility) across 5 cell types (T, B/plasma, myeloid, stromal, and endothelial). We also investigated the transcription factors that may regulate these chromatin classes, their connections to transcriptional cell states in a proposed superstate model, and their interplay with RA pathology through associations with histological parameters and risk variants.As part of the Accelerating Medicines Partnership (AMP) network, we obtained 18 synovial tissue samples from 14 RA and 4 osteoarthritis (OA) patients for this study. Samples were collected from 7 clinical sites. We performed a 10x single cell ATAC-seq experiment on each sample.We further collected synovial tissue samples from 11 RA patients and 1 OA patient from 2 clinical sites; each sample was used for a 10x single cell multimodal ATAC and Gene Expression experiment.For additional support of the proposed superstate model, we also collected peripheral blood mononuclear cells (PBMCs) from 4 RA patients, sorted for 4 populations (CD4+CD127-CD25hi Tregs, CD4+CD127-CD25int Tregs, CD4+CD25-PD1+CXCR5- TPH, CD4+CD25-PD1+CXCR5+ TFH), tagged each population with a hashing antibody, and pooled populations for one multimodal sequencing run.The FASTQ files are available for controlled access via dbGaP. Additional data can be found on Synapse.The presence of pooled subjects inflates the automatically-generated subject count; the actual consented subject count for this data is 34.

  Study phs003417

• How to upload Crypt4GH files

  Uploading files Users who hold an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files, please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention, such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. To manage the available resources, we enforce a limit of 10TB per submission account at any one time. If you exceed this limit, a “permission denied” message will be displayed. This will prevent you from uploading more files, but connecting to your inbox.For submissions larger than 10TB, please perform uploads in 10TB batches: register all the metadata and then finalise the submission. Upload the next batch of files and repeat the same metadata registration and finalisation process until you have completed the file upload. Further information can be found in the SP documentation. INBOX FTP The INBOX is only compatible with files encrypted using the Crypt4gh tool Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated, you will be able to request a submitter role. [Optional] Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g., ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. To upload files to your account, you can use the graphical user interface (GUI) or the command line. Graphical User Interface (GUI)We recommend using FileZilla, a free, open-source FTP client. However, you can use any other GUI that allows connecting over the SFTP protocol. For FileZilla as your GUI, follow these steps to upload files: Create a new connection in Site Manager (File > Site Manager) and select the following options (Figure 1): Protocol: SFTP - SSH File Transfer ProtocolHost: __EGA_INBOX_DOMAIN__Logon Type: Key fileUser: your EGA usernameKey file: Path/to/your/private_keyFigure 1: Process of establishing a new connection to __EGA_INBOX_DOMAIN__ using a key file as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers.Click Connect, and you will log in remotely to your home directory. You can think of this folder as a storage "in the EGA cloud" in which you will add your files for the EGA. The uploading area has three folders:To-encrypt: Files uploaded in this folder will be encrypted automatically on the fly.Encrypted: Files uploaded in this folder must already be encrypted with Crypt4gh. Upload your files here if your connection is unstable or you have problems completing the upload into-encrypt.Etc: This folder contains two files that allow the server to show you your username and group instead of some internal numbers. Please do not upload files here; otherwise, you will obtain a permission denied error. Find the files you want to upload by browsing your local storage (left side of your screen in FileZilla). Select all the files you want to upload, then right-click on them and select Upload (Figure 2). Figure 2: Step-by-step process of manually uploading files to __EGA_INBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can transfer data from their local storage to the "EGA cloud" by following the depicted steps Please note that regardless of which folder you upload your files in, both folders (to-encrypt, encrypted) will point to the same path (/) (Figure 3). Therefore, you will see your files in both folders. Figure 3: Both folders, to-encrypt and encrypted, point to the same path (/)" If your connection is unstable, please encrypt your files first using Crypt4gh. Then upload them to the ‘encrypted’ folder. The example above shows how to connect to __EGA_INBOX_DOMAIN__ using the private key. However, if you prefer to log in using your credentials, you can do so. Please go to the Frequently Asked Questions (FAQs)  for more information. SFTP command line To upload files securely to your private area of the EGA, you can use SFTP(Secure File Transfer Protocol) with your favorite FTP client. Here's what you need to know to get started: Connect to the target host __EGA_INBOX_DOMAIN__. This is the new hostname for the EGA SFTP service. Log in with your EGA username and key files (or password). Upload files to your private EGA inbox to ensure that only you can access the files. By following these steps, you can securely upload your files to the EGA for safe storage and sharing. Using the SFTP command line client in Linux/Unix Open a terminal and type sftp username@hostnameEnter your EGA passwordTo see a list of available SFTP commands, type helpsftp> put – Upload filesftp> get – Download filesftp> cd path – Change remote directory to ‘path’sftp> pwd – Display remote working directorysftp> lcd path – Change the local directory to ‘path’sftp> lpwd – Display local working directorysftp> ls – Display the contents of the remote working directorysftp> lls – Display the contents of the local working directoryType the "put" command to upload files. For example: put *.bamUse the bye command to close the connection (SFTP session). After uploading- Once you have uploaded files to the inbox, please bear in mind that the checksum needs to be calculated, which can take up to two days. You will only be able to link your files to a run/analysis once the encrypted checksum has been calculated.- When linking your files to the 'Run' or 'Analysis', ensure that the file name matches the file path '/name' in the INBOX folder.- Please delete the files from your SFTP INBOX after all the runs/analyses have been registered and files are ingested (SP > Files > Files ingested). This will clear your inbox space an allow you to upload more files. This will also prevent the files from reappearing in your Submitter Portal inbox. Frequently Asked Questions Specific to the inbox What username should I use to log in to my inbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username.  If you have forgotten your registered username, please contact our Helpdesk team for assistance. How are checksums calculated in your inbox? If you encrypt the file beforehand and upload it to the "encrypted" folder, the unencrypted checksum will not be calculated until the file is ingested (i.e., until it is used in a run/analysis). If the file is uploaded to the "to-encrypt" folder, then both checksums are calculated.Please bear in mind that after files have been uploaded to the inbox, the checksum must be calculated, which can take from a few hours to two days.  Specific to using keys to authenticate Can I access one EGA account from different devices? Yes, you can access your account from different devices by linking several public keys to your EGA account. Each device can generate a unique public-private key pair, and the corresponding public keys can be linked to the same account. This way, you can use different public keys on different devices and still have access to the same account and data. I have several keys and I don't remember which one is which When generating SSH keys, it's a good practice to add a comment using the -C flag. This will allow you to add a descriptive tag to your key, making it easier to identify later on. Here's an example command that generates an SSH key with a comment: ssh-keygen -t ed25519 -C work-pass In this example, we're generating an ed25519 SSH key with the comment work-pass. Once you have multiple keys with different comments, you can use the comments to easily identify each key. To view the comments for your existing SSH keys, you can use the following command: ssh-keygen -l -f /path/to/key This will display the key fingerprint and the associated comment. By checking the comments, you should be able to identify which key is which. What if I can't find my SSH keys for uploading files with a key file, and how can I use new keys? If you can't find your SSH keys, don't worry - you can make new ones. To do this, open your terminal or command prompt and type a command to make a new SSH key. You can pick a name for the key, and choose a password to keep it safe. After making the key, you can add the new key to your account or server where you want to upload files using the key file. This usually involves copying and pasting the key's "public" (e.g. file.pub) part to the right place. If you lose track of the key again, just make a new one and add it again. Keep in mind that SSH keys belong to you and your computer, so if you switch computers or accounts, you'll need to make new keys. I don't want to type the passphrase every time I use the key. What can I do? You can use an ssh-agent to avoid typing the passphrase every time you use the key. An ssh-agent is a program that stores your private keys in memory and provides them to ssh when needed. You can add your key to the ssh-agent using the command ssh-add followed by the path to your key file.Here's an example of the steps to follow: Open a terminal window.Start the ssh-agent by typing the command eval $(ssh-agent).Add your key to the ssh-agent by typing the command ssh-add [key filepath]. For instance, if your key file is located in the home directory with the name mykey, the command will look like this: ssh-add ~/mykey After adding your, key to the ssh-agent, you should be able to use ssh without having to enter your passphrase every time. Can I use my password for authentication (without my private key)? If you prefer to use your username and password for authentication instead of your private key, you can still do so. When using a Graphical User Interface (GUI) such as FileZilla, you can select Ask for password as your Logon Type (Figure 3). This option will prompt you to enter your password when you click Connect, instead of using your private key. Figure 3: This option will prompt you to enter your password when you click "Connect", instead of using your private key. Figure 3: Process of establishing a new connection to __EGA_INBOX_DOMAIN__ using your password as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers. It's worth noting that using a password for authentication can be less secure than using an SSH key, as passwords can be more easily compromised through various means. However, if you choose to use your password for authentication, selecting "Ask for password" as your Logon Type is a good way to do so securely via a GUI. Why is it better to use my key and not my password? SSH keys for authentication is generally considered to be more secure and convenient than using passwords. SSH keys are more difficult to crack than passwords, and they can be restricted to specific users and machines, giving you more control over access. Once you set up your SSH keys, you can use them to authenticate quickly and easily, without having to enter a password every time. This makes automation of tasks, such as uploading encrypted files, much simpler. Additionally, SSH keys provide better logging, allowing you to keep track of who is accessing your systems and when. All in all, using SSH keys is a good practice for improving security and convenience in your authentication process.

  Documentation submission/data/uploading-files/inbox

• NHLBI's Collection of Datasets for General Research Use (Public Posting of Genomic Summary Results: Allowed)

  This collection contains all of NHLBI's 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. Genomic Summary Results (GSR) sharing is allowed (unrestricted) or not applicable. To request access to this study collection, select phs003132 in the dbGaP Authorized Access System.

  Study phs003132

• Characterization of High-Grade Serous Ovarian Cancer Subtypes via Single-Cell and Spatial-Transcriptomics Profiling

  We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors. The initial dataset (added October, 2020) contains 3 samples (3 individuals). The next dataset (added November, 2022) contains 34 samples from 8 individuals. The samples in the second dataset were sequenced in five different ways: 1) rRNA depletion and bulk RNA sequencing of tumor chunks, 2) rRNA depletion and bulk RNA sequencing of dissociated cells, 3) poly-A capture and bulk RNA sequencing of dissociated cells, 4) poly-A capture and scRNA sequencing of dissociated cells, 5) barcoding and pooling cells and scRNA sequencing (2 pools of 4 samples each). The third dataset (added June, 2024) contains data from one spatially resolved transcriptomics experiment (4 samples, one per Visium capture area, describing one tumor from one individual) and scRNA sequencing on 5 samples (5 individuals).

  Study phs002262

• The neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy

  Identification of immunogenic cancer neoantigens as targets for therapy is challenging. Here, we integrate whole genome and long-read transcript sequencing of cancers to identify the collection of neo-open reading frame peptides (NOPs) expressed in tumors. We termed this collection of NOPs the tumor framome. NOPs represent tumor-specific peptides that are different from wild-type proteins and may be strongly immunogenic. We describe a class of hidden NOPs that derive from structural genomic variants involving an upstream protein coding gene driving expression and translation of non-coding regions of the genome downstream of a rearrangement breakpoint, i.e. where no gene annotation or evidence for transcription exists. The entire collection of NOPs represents a vast number of possible neoantigens particularly in tumors with many structural genomic variants and a low number of missense mutations. We show that NOPs are immunogenic and epitopes derived from NOPs can bind to MHC class I molecules. Finally, we provide evidence for the presence of memory T cells specific for hidden NOPs in peripheral blood from a patient with lung cancer. This work highlights NOPs as a major source of possible neoantigens for personalized cancer immunotherapy and provides a rationale for analyzing the complete cancer genome and transcriptome as a basis for detection of NOPs.

  Study EGAS00001006021

• Precision Medicine for Dilated Cardiomyopathy in European and African Ancestry

  The DCM Precision Medicine Study is a multi-site consortium-based cross-sectional study of families with an embedded open-label randomized controlled trial. The aims of the study are to test the hypothesis that dilated cardiomyopathy (DCM) has a substantial genetic basis and to evaluate the effectiveness of a family communication intervention in improving the uptake of preventive screening and surveillance in at-risk first-degree relatives. The Study goal was to recruit 1,300 individuals (600 non-Hispanic African ancestry, 600 non-Hispanic European ancestry, and 100 Hispanic; 50% female) meeting rigorous diagnostic criteria for idiopathic DCM (probands) and 2,600 of their relatives. The probands were inpatients or outpatients identified by heart failure and cardiac transplant cardiovascular physicians and clinical research personnel in heart failure/heart transplant programs at sites in the DCM Consortium. The DCM phenotype was selected for this study because of its prevalence and its prior inclusion in the development of virtually all pharmacotherapy for non-ischemic heart failure from reduced ejection fraction. Study procedures included obtaining family history, cardiac history, medical record review, surveys, and blood sample collection. Exome data from 1219 idiopathic DCM probands and 127 idiopathic DCM relatives are included in dbGaP.

  Study phs002641

• Epigenetic Landscape of Human Parathyroids

  The goal of this study is to produce a comprehensive map of the chromatin landscape of human parathyroids. Data from 20 subjects with parathyroid adenoma causing primary hyperparathyroidism were used. For the sequencing platform, Illumina HiSeq 2000 with V3 high-output kits were used. For the data processing pipeline, reads were aligned to hg19 using Bowtie or BWA. For RNA-seq data, transcript levels were estimated per gene to RPKM using Cufflink. For ChIP-seq and ATAC-seq data, enrichment peaks were estimated compared to inputs or background using MACS2 after merging reads from replicates. For DNase-seq, significant peaks compared to background distribution were computed using Hotspot. For Hi-C data, significant interactions were detected using Juicer HiCCUPS and 5 kb resolution for the merged data from replicates. Chromatin states for parathyroids were computed using ChromHMM based on ChIP-seq profiles in parathyroids of H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K27me3 and H3K9me3 and the emission matrix from 18 states pre-trained in the Roadmap Epigenomics. Gene expression, binding positions of transcription factor, open chromatin regions, 3D-chromatin interaction, and chromatin states are submitted.

  Study phs003302

• The Primary Open-Angle Glaucoma Genes and Environment (GLAUGEN) Study

  Background Information: Primary open-angle glaucoma (POAG) is an age-related, intraocular pressure (IOP)-dependent progressive optic neuropathy that ultimately leads to irreversible blindness. Vision loss from POAG is a condition of public health significance. Current evidence suggests that POAG is a polygenetic disease modified by environmental influences. Despite the fact that a positive family history of disease is an important risk factor for POAG, conventional linkage and candidate gene approaches have revealed less than 5% of the genetic component of the disease. Furthermore, there is no consensus on environment risk factors for POAG. Elevated IOP is the only modifiable risk factor for POAG; yet, lowering IOP slows, but does not halt the disease process. Study Objectives: The overall goal of our research is to elucidate the pathogenesis of POAG so that cost-effective disease detection and primary prevention strategies can be implemented. The primary aim of the Glaucoma Gene Environment Initiative (GLAUGEN), funded by the Human Genome Research Institute (NHGRI), is to discover genetic loci associated with POAG. The secondary aim of GLAUGEN, funded by NHGRI and the National Eye Institute, is to discover gene environment interactions in POAG. Methods and study populations: For this study, we have assembled cases and controls from three studies: the Nurses&#39; Health Study (NHS), the Health Professionals Follow-up Study (HPFS) and the Genetic Etiologies of POAG (GEP) project based at Massachusetts Eye and Ear Infirmary (MEEI). This case-control group includes 1057 unrelated cases and 1272 controls. Members of the NHS and HPFS also have repeated environmental exposure data collected prior to a diagnosis of POAG. NHS - The Nurses Health Study started in 1976 under the direction of Dr. Frank E. Speizer. With funding from the NIH, registered nurses from 11 US states were invited to complete a detailed questionnaire regarding lifestyle and health biennially. Initially, 121,000 women responded to the baseline questionnaire. Currently, Dr. Susan Hankinson serves as the program director for the NHS. HPFS - The Health Professionals Follow-up Study began in 1986 under the direction of Drs. Walter Willett and Meir Stampfer. Under the auspices of the NIH, they enlisted 51,529 male health professionals from throughout the US to complete similarly designed biennial questionnaires. Beginning in 1990, questions regarding ocular health were added to biennial questionaires completed by health professionals participating in the NHS and HPFS. This allowed us to formulate (PI: S. Hankinson; NEI) and maintain (PI: L. Pasquale; NEI) a cohort at risk for POAG derived from the respective general cohorts who were under ophthalmic care. We then developed a definition of POAG that allowed us to identify cases from a population that was geographically dispersed. The centerpiece of this definition is the presence of reproducible visual field loss consistent with nerve fiber layer (NFL) dropout (the NFL contains the axons that comprise the optic nerve) on reliable tests. Reproducible visual field loss occurred in the context of anterior segment findings that did not suggest a secondary cause of elevated IOP and posterior segment findings that did not suggest a secondary cause of visual field loss. We selected controls from the cohort at risk for POAG on the basis of age, gender and time period when cases were identified. GEP - The Genetic Etiologies of POAG was initiated in 1996 with funding from the National Eye Institute under the direction of Dr. Janey Wiggs. The purpose of this work was to discover novel genetic loci associated with POAG. In the GEP, cases were derived predominantly from the Glaucoma Service at MEEI. The majority of cases had an examination by a glaucoma specialist and met the definition for POAG used in NHS and HPFS. Cases with only one reliable visual field consistent with NFL dropout were included if there was a cup-disc ratio of 0.7 or more. The majority of controls were patients who presented to the MEEI comprehensive ophthalmology service for routine eye examination or from spouses of MEEI patients with secondary forms of glaucoma. Other controls were identified from regional glaucoma screenings held throughout Massachusetts. Members of GEP have detailed ocular phenotype data but limited information on environmental exposures. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to primary open-angle glaucoma through large-scale genome-wide association studies of three well-characterized cohorts of cases and controls, some in matched pairs. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000308