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• Whole Genome Sequencing of Neuroblastoma

  Neuroblastoma is a childhood tumour of the peripheral sympathetic nervous system. The pathogenesis has for a long time been quite enigmatic, as only very few gene defects were identified in this often lethal tumour1. Frequently detected gene alterations are limited to MYCN amplification (20%) and ALK activations (7%)2-5. Here we present a whole genome sequence analysis of 87 neuroblastoma of all stages. Only few recurrent amino-acid changing mutations were found. In contrast, analysis of structural defects identified in 18% of high stage neuroblastoma a local shredding of chromosomes, known as chromothripsis6. These tumours are associated with a poor outcome. Structural alterations recurrently affected ODZ3, PTPRD and CSMD1, which are involved in neuronal growth cone stabilization7-9. In addition, ATRX, TIAM1 and a series of regulators of the Rac Rho pathway were mutated, further implicating defects in neuritogenesis in neuroblastoma. Most tumors with defects in these genes were aggressive high stage neuroblastoma, but did not carry MYCN amplifications. The genomic landscape of neuroblastoma therefore reveals two novel molecular defects, chromotripsis and neuritogenesis gene alterations, which frequently occur in high risk tumors.

  Study EGAS00001000222

• Whole Genome Sequencing of Asian Lung Cancers: Second Hand Smoke is Not Responsible for Higher Incidence of Lung Cancer Among Asian Never-Smokers

  Background Asian nonsmoking populations have a higher incidence of lung cancer compared to their European counterparts. There is a long-standing hypothesis that the increase of lung cancer in Asian never-smokers is due to environmental factors such as second-hand smoke. Results We analyzed whole-genome sequencing of 30 Asian lung cancers. Unsupervised clustering of mutational signatures separated the patients into two categories: i) all of the never-smokers, and ii) only smokers or ex-smokers. Half of the ex-smokers / smokers were in the never-smoker-like cluster. The overall somatic variant profiles of Asian lung cancers were similar to that of European origin with G.C>T.A being predominant in smokers. We found EGFR and TP53 are the most frequently mutated genes with mutations in 50% and 27% of individuals, respectively. Among these Asian never-smokers, 71% had an EGFR mutation compared to 20% of the smokers in the smoking cluster. Other frequently mutated genes include RYR2, SATB2, C1orf88, FERMT1 and CTNNB1. Somatic alterations occurred in WNT signaling pathway genes, suggesting this pathway plays a role in both Western and Asian lung cancers. Conclusions Asian never-smokers have lung cancer signatures distinct from the smoker signature and their mutation profiles are similar to that of European never-smokers. The profiles of Asian and European smokers are also similar. This suggests that the same mutational mechanisms underlie the etiology for both ethnic groups, and the high incidence of lung cancer in Asian never-smokers might not be due to second hand smoke or other carcinogens that cause oxidative DNA damage. Half of the ex-smokers/smokers have a molecular phenotype similar to never-smokers; of which, 50% had EGFR mutations. This suggests that routine EGFR testing is warranted in the Asian population, regardless of smoking status.

  Study EGAS00001000621

• Pediatric Preclinical Testing Consortium (PPTC)

  The Pediatric Preclinical Testing Consortium (PPTC) is addressing the unmet need of streamlining the development of new therapies for childhood cancers. The PPTC seeks to develop robust biomarkers of anticancer drug activity, and the majority of these are predicted to be genetic mutations that can be detected in tumor DNA and/or RNA. In order to design the most impactful experiments that can be rapidly translated to the clinic, PPTC investigators require a complete genomic characterization of the patient-derived xenograft tumor models that are utilized across the consortium. This will not only allow for the most robust experimental design, but also will increase the engagement of industry partners who seek collaborators poised to provide the proof-of-concept necessary for drugs in their development pipelines. All data and models will be made available to academically qualified investigators.

  Study phs001437

• FHIR Test Study BETA

  FHIR Test Study BETA. This study was created with 3 consent groups to simulate an actual study for FHIR API testing project. The data herein is simulated and are intended for development of FHIR representation of dbGaP phenotype data.

  Study phs002410

• A panel of reference haplotypes for imputing complement component 4 (C4) gene structural variation

  Neuropsychiatric and autoimmune disorders have substantial epidemiological correlations (Benros et al., JAMA Psychiatry 2013, PMID: 23760347) and broad, genome-wide patterns of shared genetic risk (Pouget et al., Hum Mol Genet, PMID: 31211845; Tylee et al., Am J Med Genet B Neuropsychiatr Genet 2018, PMID: 30325587). Some cases of psychosis involve autoantibodies against the NMDA receptor, AMPA receptor, or other synaptic proteins (reviewed in Dalmau et al, Lancet Neurol 2011, PMID: 21163445). The related autoimmune conditions lupus and Sjogren's Syndrome also involve the development of autoantibodies. The possibility that neuropsychiatric disorders can have molecular mechanisms in common with autoimmune disorders - for example, that psychosis involves an inflammatory or autoimmune component in some patients, or that immune molecules are re-used in the brain to underlie other important biological activities (Stevens et al., Cell 2007, PMID: 18083105) - could open novel therapeutic possibilities for neuropsychiatric disorders. At a genetic level, the strongest genetic associations of schizophrenia, lupus, and Sjogren's Syndrome to common genetic variation involve associations to genetic markers in the Major Histocompatibility Complex (MHC) locus. Bipolar disorder in some studies also associates with variation in or near the MHC locus, though less strongly than schizophrenia does. Intriguingly, the same specific SNPs appear to associate strongly with schizophrenia, lupus, and Sjogren's; these strongly associating SNPs span a genomic segment that includes the HLA class II genes (which have an important role in antibody production) and the complement component 4 (C4) genes. The specific genes and alleles responsible for these associations need to be completely defined, and the extent to which they represent shared or distinct genetic influences in neuropsychiatric and autoimmune illnesses needs to be clarified. The complement component 4 (C4A and C4B) genes are present in the MHC locus, between the class I and class II HLA genes. C4A and C4B commonly vary in genomic copy number and encode complement proteins with distinct affinities for molecular targets. The complex genetic variation at C4 - arising from many alleles with different numbers of C4A and C4B genes - has been challenging to analyze in large cohorts. We recently developed an approach to this problem based on imputation: people share long haplotypes with the same combinations of SNP and C4 alleles, such that C4A and C4B gene copy numbers can be imputed from SNP data (Sekar et al., Nature 2016, PMID: 26814963). In the current work, to analyze C4 in large cohorts, we developed a way to identify C4 alleles from whole-genome sequence (WGS) data, then analyzed WGS data from 1,234 individuals to create a large multi-ancestry panel of 2,530 reference haplotypes of MHC SNPs and C4 alleles that can then be imputed into still-larger cohorts for which SNP data are available. With this dbGaP submission, we make this reference panel available for other studies. Protocols and software for imputing C4 alleles into genome-wide SNP data, and for performing molecular analyses on the C4 genes (such as direct measurement of copy number from genomic DNA), can be found on the McCarroll Lab web site (http://mccarrolllab.org/resources). We are also working to create additional reference panels for imputation of C4 alleles that will be based on still-larger and more diverse population samples; links to these will also be available on the McCarroll Lab web site as we create and validate them.

  Study phs001992

• Submitter Portal

  Submitter Portal The Submitter Portal does not support array submissions! Please refer to the array documentationAny new objects registered in the Submitter Portal will not be available for use in an array submission For further information please check our Submission FAQs, submission quickguide as well as submission terms! The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. Submitter Portal Index Previous steps Access to Submitter Portal Start a Submission Take The Tour Tutorial Previous steps Create your EGA account To submit data, you first need to create your EGA user. Then, once your account has been verified by the Help Desk team, you will be able to request a submitter role and send the EGA Data Processing Agreement (DPA). In the case you already have an EGA account, or an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role and added your public key to your profile, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find relevant information in the DAC Portal Guide. Access to Submitter Portal 1. Request Submitter Role Once you have created your EGA user, request a Submitter Role and complete relevant information such as submission type and size. 2. Signature of the Data Processing Agreement The Data Processing Agreement (DPA) signed by CRG and EMBL-EBI (Joint Data Processors for the EGA) can be downloaded to the submitter for its signature. Further information related to the DPA can be in the Privacy Notice section. The DPA should be signed by a legal representative of the submitter with power of attorney/appointment duly authorised to sign contracts on behalf of the institution. The submitter will return a fully-executed copy of the DPA to us. Please note that due to the high volume of submissions to EGA the DPA is non-negotiable. Once you have completed all the information and attached the DPA signed, send your Submitter request and the EGA Helpdesk Team will validate it and send a confirmation to start submitting your metadata. Start a Submission The steps below will show you how to start a submission and are accompanied with a tutorial and the Take the tour of Submitter Portal. 1. Login Go to the Submitter Portal interface and log in using your EGA account credentials. 2. Create a submission The Submitter Portal interface will show you any already existing open submission. To start a new submission click on “Create a Submission”.In this phase you have the option to add any collaborator(s) as well as their permissions (“Read only” or “Read & Write”). If you want to invite all the collaborators from a previous submission, you can add them by selecting said submission.In the event that the submission has been closed, you will need to reopen it. To do this, you will need to modify one of the objects in the submission, for example, copy and paste the title. Once the submission is open, you can add a collaborator. Further information can be found in the Submission Tour 3. Create Study Click on add Study and complete the form with the relevant information. The fields with an asterisk (*) are mandatory. Further information can be found in the Submission Tour4. Create Sample Sample registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with information about the sequencing samples. Upload the samples.csv and the sample will be created.Add single sample: complete the mandatory fields with the metadata information of your sample.  Further information can be found in the Submission Tour5. Create Experiment Register an experiment with ​information about the sequencing methods, protocols and machines. Experiments generate the connection between samples and study. Further information can be found in the Submission Tour6. Create Run Samples, experiments and files are linked through runs. To register a run, you will be asked to select the appropriate experiment and the file format. Run registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with the sample - file linkage. Upload the run.csv and the runs will register.As the INBOX is a directory, bear in mind to include the file path (/). Example: /filename.c4gh. Add single run: select the file format, sample and experiment from the drop box. For re-using submitted samples, please use the EGA accession ID (EGANXXX). Please note that files must be uploaded in your inbox before linking your files and samples. Further information can be found in the Submission Tour7. Create Analysis Analysis should be only used for BAM/BAI or CRAM/CRAI pair, VCF and phenotype linkage to samples. The analysis is an EGA specific metadata object that links samples to files. This object also stores some metadata about your experiments, such as the experiment type, genome reference, or the platform used. **If only BAM or CRAM alignment files are submitted but not the original unaligned FASTQ files, then please make sure that the BAM or CRAM files also contain the unaligned reads. This is critical to enable primary re-analysis and re-alignment of the dataset using new tools or future genome assemblies.** Start by selecting the samples to be linked to the file, and then populate the required attribute fields. Please be aware of the existence of mandatory fields that must be populated.When populating the chromosome field (mandatory), please select the chromosomes from the checkbox. Please take in consideration that EGA allows for the re-use of any registered metadata. Therefore, a previously registered study or samples can be referenced for the analysis in the current data submission.Further information can be found in the Submission Tour 8. Create Dataset Dataset contains the collection of runs/analysis data files subjected to controlled access by being associated with a Policy. Complete the mandatory fields such as title, description, type and policy. Please, take in consideration that DAC and Policy must be registered in advance in the DAC Portal. Similar to other metadata objects, you can re-use previous runs or analyses, using their EGA accessions IDs (runs - EGAR, analyses - EGAZ). Further information can be found in the Submission Tour 9. Finalise submission Once the files are ingested please delete them from your SFTP INBOX before finalising your submission. This will prevent the files from reappearing in your Submitter Portal Inbox. Once you have completed your submission, click on the Finalise button, and schedule an estimated release date. Afterwards, your submission will be sent to Helpdesk for approval. Please note that once the Helpdesk has approved your submission, you will receive the identifiers for your data. See the Frequently Asked Questions (FAQ) for more information. 10. Update closed submission If you want to append more file to a closed submission, you will need to re-open the submission where the dataset was registered. Find the Submission: go to the Submitter Portal Menu -> Datasets section and find the submission id (EGA0XXX).  Reopen the submission where the dataset is located: to reopen a submission, you must edit any object within the submission. For example, you can copy and paste the title. Take The Tour The Submitter Portal Take The Tour is a visual guidance of all the steps described previously about how to start a submission. Tutorial In this tutorial we will show you how to use the Submitter Portal to register your metadata. Please note the video focuses on the run-based submission (for raw files - fastq - and aligned data - BAM/CRAM) and analysis-based submission (for your BAM/BAI pairs, variation -VCF - and phenotype files).

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal

• The National Heart, Lung, and Blood Institute (NHLBI)-funded Next Generation Genetic Association Studies (NextGen) Consortium: Phenotyping Lipid traits in iPS derived hepatocytes Study (PhLiPS Study)

  The goal of the PhLiPS study is to create a library of induced pluripotent stem cell (iPSC) lines and iPSC-derived hepatocytes of diverse genotypes for use in metabolic profiling and interrogating lipid phenotypes. These cell lines were created as a part of the Next Generation Genetic Association Studies (Next Gen) Program, which was a five-year, $80 million program to investigate functional genetic variation in humans by assessing cellular profiles that are surrogates for disease phenotypes. To achieve this, researchers from multiple institutions across the U.S. were awarded grants to derive iPSC lines from more than 1,500 individuals representing various conditions as well as healthy controls for use in functional genomic ("disease in a dish") research. This extensive panel includes a diverse set of age, gender, and ethnic backgrounds, and therefore will be an invaluable tool for evaluations across demographics. Further enhancing the utility of these cell lines are data sets such as phenotyping, GWAS, genome sequencing, gene expression and -omics analyses (e.g., lipidomic, proteomic, methylomic) that can be matched to the cell lines. The PhLiPS Study focuses on individuals free of cardiovascular disease or with lipoprotein metabolism disorders in the community served by the Hospital of the University of Pennsylvania.

  Study phs001341

• HNF1B induced three-dimentional genome analysis of patient-derived pancreas neoplasm organoids

  Three-dimensional (3D) genome structures are organized in a hierarchy of various module layers, including chromosome compartment, topologically associating domain, and enhancer-promoter loop. These modules are important in regulating cell type specific gene expression. Here, we aimed to elucidate how 3D genome organization is related to regulating subtype specific genes in pancreatic neoplasms.

  Study JGAS000514

• Methylation_changes_in_OA_patients_with_chronic_exposure_to_cobalt_and_chromium

  We have whole blood from a population of 70 patients, half exposed chronically to an excessof metals cobalt and chromium. The 2 groups are age, sex, and OA diagnosis matched. The2 groups have systemic differences in bone mass and turnover, and other systemicdifferences.We will type the cohort of 70 individuals on the Illumina 450k methylation array and willcompare between the two groups.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001180

• PRE-DETERMINE: Biologic Markers and MRI SCD Cohort Study

  The PRE-DETERMINE Study is a prospective, multi-center study of 5,764 patients with a history of coronary artery disease (CAD) and documentation of either a prior myocardial infarction (MI) or mild to moderate left ventricular dysfunction (LVD) with left ventricular ejection fraction (LVEF) 35-50%. Patients were enrolled at 136 sites where information on baseline demographics, clinical characteristics, pertinent past medical history, lifestyle habits, cardiac test results, and medications were collected via electronic data capture. Electrocardiograms (ECG) along with a blood sample was also collected at baseline, sent to central laboratories, and stored for future analyses. Contrast-enhanced magnetic resonance imaging (CE-MRI) scans were collected on a subset of patients and analyzed. Enrollment closed in November 2013 and patients are now being followed centrally by the Clinical Coordinating Center via mail/phone to document interim non-fatal arrhythmic events and cause-specific mortality. Questionnaires that inquire about intervening implantable cardiac defibrillator (ICD) implantations, ICD therapies, cardiac arrest, and other pertinent cardiovascular endpoints are mailed to participants every six months, and follow-up telephone calls are made to non-responders. Study endpoints are being confirmed through review of medical records, interviews with next-of-kin, and autopsy reports, if available.The primary objective of PRE-DETERMINE is to determine whether biologic markers and ECGs can be utilized to advance sudden cardiac death (SCD) risk prediction in patients with coronary heart disease (CHD) and LVEF >30-35%. The overarching goal of the study is to identify a series of markers that alone or in combination specifically predict risk of arrhythmic death as compared to other causes of mortality among this at risk population of CHD patients with preserved LVEF> 30-35%. If biologic or ECG markers are identified that can specifically predict risk of ventricular arrhythmias, then these markers may serve as relatively inexpensive methods to identify those at risk. The public health impact of identifying markers could be quite substantial, leading to more efficient utilization of ICDs and advances in our understanding of mechanisms underlying SCD.Among the 95% of participants that provided a blood sample at baseline, genome wide genotyping using the Illumina Global Screening Array (GSA) has been performed. A total of 4,335 participants with European ancestry gave consent that allows genetic research and deposition of data into dbGaP.

  Study phs002940