Search Results - EGA European Genome-Phenome Archive

Human Heredity and Health in Africa Data Access Committee

Dac EGAC00001000648

MD Anderson Cancer Center HGSOC LRS Data Access Comittee

Oxford Nanopore long-read sequencing was performed on six paired tumor-normal samples from patients with high-grade serous ovarian carcinoma. Reads were mapped to the GRCh38 reference genome, incorporating base modification information.

Dac EGAC50000000597

B-cell precursor acute lymphoblastic leukemia acute lymphoblastic leukemia Micro-C sequencing data Data Access Committee

This dataset included 33 childhood B-cell precursor (BCP) acute lymphoblastic leukemia Micro-C samples. All samples were subjected to Illumina pair-end sequencing.

Dac EGAC50000000467

Effectiveness and Safety of Intermittent Antimicrobial Therapy for the Treatment of New Onset Pseudomonas Aeruginosa Airway Infection in Young Patients With Cystic Fibrosis (EPIC-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 investigate the efficacy and safety of 4 antipseudomonal treatments in children with cystic fibrosis (CF) with recently acquired Pseudomonas aeruginosa (PA) infection.Background: CF is an inherited disease that causes mucus to build up in the lungs and digestive tract, which can cause lung infections and digestive problems. It is the most common type of chronic lung disease in children and young adults and may result in early death. There is no cure for this disease. The primary cause of death in individuals with CF is progressive obstructive pulmonary disease associated with chronic Pseudomonas aeruginosa (PA) infection. PA infection can occur early in life and can become highly resistant to antibiotics. Once an individual has been diagnosed with chronic PA infection, it is almost impossible to manage effectively. The need exists for an effective treatment to control and eliminate PA infection. Past research has shown that if PA infection is treated early, there is a greater likelihood that it may be eliminated completely.Participants: There were 304 participants.Design: Participants were randomized to 1 of 4 antibiotic regimens for 18 months (six 12-week quarters) between December 2004 and June 2009. Participants randomized to cycled therapy received tobramycin inhalation solution (300 mg twice a day) for 28 days, with oral ciprofloxacin (15-20 mg/kg twice a day) or oral placebo for 14 days every quarter, while participants randomized to culture-based therapy received the same treatments only during quarters with positive P aeruginosa cultures. The primary end points were time to pulmonary exacerbation requiring intravenous antibiotics and proportion of PA - positive cultures.Conclusions: No difference in the rate of exacerbation or prevalence of PA positivity was detected between cycled and culture-based therapies. Adding ciprofloxacin produced no benefits (Arch Pediatr Adolesc Med 2011; 165(9):847-856).

Study phs004067

The National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN)

The NINDS Stroke Genetics Network (SiGN) is a large international collaboration designed to detect genetic variants that predispose to subtypes of ischemic stroke. The study implements a genome wide association study (GWAS) methodology with all stroke cases undergoing phenotypic and stroke-subtype classification using the same web-based Causative Classification of Stroke (CCS) system, with data entered by trained and certified adjudicators at participating Research Centers (GRC's). SiGN includes ischemic stroke cases from 24 GRC's, 13 from the US and 11 from Europe. Each GRC has access to well-characterized ischemic stroke cases in which extensive phenotype data and high-quality DNA was available. Genome-wide data was available for many cases and for those without, new genome-wide genotyping, including exome chip genotyping of rare variants, was done through the Center for Inherited Diseases Research (CIDR). To maximize power for subtype analyses, genotyping resources were allocated almost exclusively to cases. With few exceptions, controls were drawn from studies with publicly available genome-wide data.

Study phs000615

ICGC Data Access Compliance Office

To access Controlled Access ICGC data at the EGA you must first apply for access on the DACO form. Instructions on this process is available from this web site: http://docs.icgc.org/portal/access/

Dac EGAC00001000010

The EGA at the International Congress of Human Genetics

Today is the start of the International Congress of Human Genetics (ICHG). This event, hosted by the African Society of Human Genetics (AfSHG) and the Southern African Society for Human Genetics (SASHG), will reunite international experts to highlight how genomic technologies are being managed to address challenges generated by the current status of Human Health and Genomics. The European Genome-phenome Archive (EGA) will be at the Congress participating in workshops, meetings and talks where topics such as data access and discovery as well as the Federated EGA will be present. Data access and discovery In the context of the “Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. Data access and discovery In the context of the “ Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. During the last four years, CINECA has been identifying gaps in data sharing between Africa, Canada and Europe in order to build a federated solution for data access. Thomas Keane will present the project within the sessions happening the 24ᵗʰ. The Federated EGA at the ICHG A Federated EGA poster will be shown during the Poster Session 1 that will take place the 23ʳᵈ. The objective is to bring awareness of the European Genome-phenome Archive as a resource for permanent archive and secure data sharing. In this context, the network generated by the Federated EGA is key for cases where research data cannot be shared outside local jurisdictions. The Federated EGA was officially launched on 2022 with research institutes from five countries becoming the first nodes of this network. Nowadays, with more than 20 nodes preparing to join, it aims to become the largest human omics data sharing initiative towards understanding human health and disease. The H3Africa Initiative and the African research represented in the EGA 1.1% of the EGA studies include samples from African populations. Countries such as South Africa, Kenya, Uganda or Egypt, among others, are present in the 72.577 samples from African individuals archived at the EGA. 23 EGA datasets are managed by the Human Heredity and Health in Africa Initiative (H3Africa). This Initiative will celebrate its Consortium Meeting the 27ᵗʰ and 28ᵗʰ, back-to-back with the ICHG. H3ABioNet, the Pan African Bioinformatics Network for the H3Africa consortium, will also take this context to celebrate its 10-Year Symposium during the Congress. Members of the EGA team will attend both of them, as the H3ABioNet works in conjunction with H3Africa projects, to submit data to the European Genome-Phenome Archive.

Blog the-ega-at-the-international-congress-of-human-genetics

New set of services for all users unveiled at the EGA

The European Genome-phenome Archive (EGA) releases today a brand-new website as well as a set of improved services for users, comprising a revamped Submitter Portal with an improved API and data brokering functionality for submitters, as well as a new DAC Portal for Data Access Committee members to easily manage data access requests. The EGA team has been working hard over the past months on these improvements that will provide a better experience for the users. Discover them below! Visit our new EGA website and check the new functionalities and updated guides Our new website is live, with a fresh look and updated features to discover all the novelties. The homepage now includes three pathways to guide our users, depending on whether they want to deposit, download or manage data within the Archive. One of the most outstanding developments is the introduction of a streamlined process for requesting access to data: EGA Users can now directly request access to their preferred datasets through the website using their EGA accounts. Additionally, users can customise their profile, oversee active sessions, and manage the public keys, essential for our latest array of services, alongside a range of other features. Another major change is our new Help Desk contact method: a built-in website form tailored for user inquiries. This system, called "Need Help?", can be easily located on the top right-hand side of the website. It will encompass both EGA and Federated EGA node users' requests. We will detail its use soon, so stay tuned. Register your metadata to the EGA easily with our new Submitter Portal The new Submitter Portal makes the submission process quicker and more intuitive. The process is currently divided into sections that the user will know beforehand by taking the tour that the EGA team has created to guide users through the Portal before starting the first submission. Do not complete your data submissions alone! Our Submitter Portal now includes a collaboration mode so that every submission can be completed by authorised collaborators with an EGA Profile. There are a lot more features that we will be detailing from now on in incoming posts. A new platform for Data Access Committee Members The new DAC Portal brings novelties for individuals engaged in governance, legal, technical, operational roles, or those acting as data stewards. DAC members will be able to easily manage DACs, policies, and data access requests with the new Portal. Take the tour now to check them out! Help us improve the services completing the EGA Survey As part of our ongoing journey to improve your experience, we have created an EGA User Survey. This questionnaire covers a wide range of aspects such as user experience, support and data accessibility, among others. Participate now and take the opportunity to suggest your own improvements. Help us enhance your experience in this new era for the EGA. Subscribe to the EGA Mailing List and stay tuned In the next weeks we will share more information about the possibilities of the new services. You can easily join the EGA Mailing List to receive all the updates.

Blog new-set-of-services-at-EGA

Kids First: Genetics of Pediatric Germ Cell Tumors

The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the genomic and phenotypic data from this study are accessible through dbGaP. The data is also available at the Kids First Portal, where other Kids First datasets can also be accessed in the cloud for data analysis, data visualization, collaboration and interoperability, open to all researchers and developers.Pediatric malignant germ cell tumors (GCTs) represent approximately 6% of childhood cancers, including 3% of tumors in children aged 0-14 years and 15% of tumors in adolescents. GCTs are heterogeneous and grouped together due to the presumed common cell of origin, the primordial germ cell (PGC). GCTs typically occur in the testes or ovaries; however, extragonadal GCTs can occur and are likely a result of abnormal germ cell migration during development. Evidence suggests that GCTs, including those diagnosed in adults, are initiated in utero. Thus, alterations in normal embryonic development are likely to be especially relevant to GCT etiology. Germline susceptibility has not been evaluated in an agnostic fashion in pediatric GCT, mainly due to a lack of an adequate number of samples; however, emerging evidence supports a genetic etiology.In the two Kids First GCT projects, we will evaluate genetic susceptibility to intracranial and extracranial GCT by sequencing probands and their unaffected parents. The goals of the project are to: 1) evaluate the contribution of rare genetic variants in GCT through the use of aggregate burden tests, focusing on genes and established regulatory regions; 2) identify de novo SNVs and CNVs in pediatric GCT using a case-parent triad design; and 3) identify molecular signatures in GCT tumor specimens, overall and by age group and tumor characteristics. Whole Genome Sequencing (WGS) data generated through the Gabriella Miller Kids First Pediatric Research Program will provide an opportunity to investigate the genetic origins of GCT in a diverse set of samples. Given the limited knowledge of GCT etiology and biology, the results of the proposed analyses are likely to have a big impact on the field.

Study phs002322

Sequencing data (BAM files) from - A mutation in VPS15 (PIK3R4) causes a ciliopathy and affects IFT20 release from the cis-Golgi. The Data Access Committee (DAC) is responsible for sequencing data release to external requestors based on consent and/or National Research Ethics terms.

Dac EGAC00001000552

L1-Architect Project DAC

This Data Access Committee and policies are for controlling the correct use of the omics datasets generated within the L1-Architect Project, to investigate the impact of L1 transposable elements in tumours with high and ultrahigh rates of somatic retrotransposition

Dac EGAC50000000289

NHLBI TOPMed: Genomic Summary Results for the Trans-Omics for Precision Medicine Program

The NHLBI Trans-Omics for Precision Medicine (TOPMed) program aims to identify the genetic basis of variation in biomedical phenotypes, with emphasis on those related to heart, lung, blood and sleep disorders, as part of a broader Precision Medicine Initiative. The TOPMed program has provided whole genome sequencing (WGS) to over 80 different studies that had previously recruited participants and collected extensive phenotype data. Many TOPMed investigators affiliated with these studies have organized their activities into phenotype-focused Working Groups and have developed genotype-phenotype association projects. These analyses have resulted in valuable cross-study Genomic Summary Results (GSR) that include whole genome association test results of both common and rare variants. Most of the analyses include data from multiple studies, some of which are based on sensitive populations, precluding public sharing of GSR. This dbGaP accession provides a mechanism for sharing sensitive GSR, using the controlled-access mechanisms of dbGaP to provide protections for sensitive populations.

Study phs001974

HeartShare - Extant Datasets - Harmonized Clinical Trials Collection

Heart failure with preserved ejection fraction (HFpEF) prevalence is rising with an aging population and contributing comorbidities, such as obesity and diabetes. The Get With The Guidelines - Heart Failure (GWTG-HF) study showed that the proportion of hospitalized HFpEF patients rose from 2005 to 2010, and this trajectory continued to increase through 2020. HFpEF patients have a poor 5-year outcome with a 75% mortality rate. Taken together, these data suggest that HFpEF may be the dominant HF subtype in the future, affecting approximately 1 in 10 adults during their lifetime.In addition to its increasing prevalence, HFpEF is a heterogeneous syndrome with multiple pathophysiological processes and varied clinical presentations. There is an urgent need to improve understanding of different HFpEF phenotypes to match patients with interventions based on their unique subtype. Phenomapping studies have identified between two and six HFpEF clusters/phenogroups with shared features. Of these, three overlapping phenotypes repeatedly arise: an 'older, vascular aging' phenotype, 'metabolic, obese' phenotype, and 'relatively younger, natriuretic peptide (NP) deficiency' phenotype. Continued refinement of these HFpEF subtypes is needed to identify distinct characteristics and underlying biologic and molecular mechanisms towards therapeutic development and future precision trials with improved diagnostic criteria and treatment including prevention.The HeartShare extant datasets collection consists of selected completed trials on HFpEF which have been harmonized for the purpose identifying and defining subtypes. The goal is to identify HFpEF subtypes that have a common pathophysiology. Through the HeartShare extant datasets collection, users can request access to both the harmonized data and the individual trial datasets.To request access to this study collection, select phs003989 in the dbGaP when submitting a data access request. The following clinical trials and harmonized data is available through this collection:Study NameHandleAccessionConsent GroupsSurgical Treatment for Ischemic Heart FailureBioLINCC_STICHphs003493.v1.p1GRUHeart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis TherapyBioLINCC_HFN_ATHENAphs003506.v1.p1GRUHeart Failure Network - Effectiveness of Ultrafiltration in Treating People With Acute Decompensated Heart Failure and Cardiorenal SyndromeBioLINCC_HFN_CARRESSphs003510.v1.p1GRUHeart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart FailureBioLINCC_HFN_DOSEphs003524.v1.p1GRUHeart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure PatientsBioLINCC_EXACT_HFphs003533.v1.p1GRUHeart Failure Network: Functional Impact of GLP-1 for Heart Failure TreatmentBioLINCC_HFN_FIGHTphs003542.v1.p1GRUHeart Failure Network - Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection FractionBioLINCC_HFN_NEATphs003548.v1.p1GRUHeart Failure Network - Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in Diastolic Heart FailureBioLINCC_HFN_RELAXphs003565.v1.p1GRUHeart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of DyspneaBioLINCC_HFN_ROSEphs003589.v1.p1GRUHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMBHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMB-NPUGuiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart FailureBioLINCC_GUIDE_ITphs003621.v1.p1GRUSudden Cardiac Death in Heart Failure TrialBioLINCC_SCD_HeFTphs003654.v1.p1GRUTreatment of Preserved Cardiac Function Heart Failure With an Aldosterone AntagonistBioLINCC_TOPCATphs003665.v1.p1HMB-MDSHeart Failure Network - Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEFBioLINCC_HFN_INDIEphs003667.v1.p1GRUStudies of Left Ventricular DysfunctionBioLINCC_SOLVDphs003668.v1.p1GRUEvaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization EffectivenessBioLINCC_ESCAPEphs003782.v1.p1GRU

Study phs003989

UHN Genomics Data Access Committee

Dac EGAC00001000912

med-pchic-dac

The data are accessible under the terms of the following Data Access Agreement that needs to be filled in, signed (by yourself and your institutionâ€™s official contact) and returned by email to med-pchic-dac@lists.cam.ac.uk

Dac EGAC00001000523

National Sleep Research Resource (NSRR): Cleveland Family Study (CFS)

The Cleveland Family Study (CFS) is a family-based study of sleep apnea, consisting of 2,284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study began in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. National Institutes of Health (NIH) renewals provided expansion of the original cohort, including increased minority recruitment, and longitudinal follow-up, with the last exam occurring in February 2006. The CFS was designed to provide fundamental epidemiological data on risk factors for sleep disordered breathing (SDB). The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first-degree relatives, spouses and available second-degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first-degree relatives. Each exam, occurring at approximately 4-year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. Currently, data of 710 individuals are available for use through BioData Catalyst (with genotype data available through dbGaP).The National Sleep Research Resource (NSRR) is a NIH-supported sleep data repository that offers free access to large collections of de-identified physiological signals and related clinical data from a large range of cohort studies, clinical trials and other data sources from children and adults, including healthy individuals from the community and individuals with known sleep or other health disorders. The goals of NSRR are to facilitate rigorous research that requires access to large or more diverse data sets, including raw physiological signals, to promote a better understanding of risk factors for sleep and circadian disorders and/or the impact of sleep disturbances on health-related outcomes. Data from over 15 data sources and more than 40,000 individual sleep studies, many linked to dozens if not hundreds of clinical data elements, are available (as of Feb. 2022). Query tools are available to identify variables of interest, and their meta-data and provenance.

Study phs002715

How to upload GPG files

Uploading files Users that holds 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. In order to manage the available resources, we enforce a limit of 10Tb per submission account at any one time. Please do not exceed this limit. INBOX FTP The FTP is only compatible with files encrypted using the EGACryptor tool Before uploading Once your submission files have been prepared using the EGAryptor, the resulting encrypted files and associated md5sum files can be uploaded to your submission account using Aspera or FTP. The EGA is a shared, public service with limited resources. In order to manage the available resources, EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. If you are approaching this limit please contact contact EGA Helpdesk so that we can advise on how to register the associated metadata and trigger the archiving of files, so that you can continue with your submission. If we note that your submission account increases above 10Tb on a consistent base your password will be changed until metadata is associated. Aspera Download Aspera Using Aspera FTP FTP windows FTP Linux / Unix FTP client (Filezilla) FTP and TLS Troubleshooting Troubleshooting Aspera Download Aspera is a commercial file transfer protocol that may provide faster transfer speeds than ftp especially over longer distances. The Aspera ascp command line client. Please select Aspera Connect. The ascp command line client is distributed as part of the aspera connect highperformance transfer browser plugin and is free to use, without registration. The minimum required version of the IBM Aspera Cli is V4. Further instructions. Using the Aspera ascp command line program The location of the ascp program in the filesystem: Mac: on the desktop go cd /Applications/Aspera\ Connect.app/Contents/Resources/ there you'll see the command line utilities where you're going to use ascp. Windows: the downloaded files are a bit hidden. For instance, in Windows 7 the ascp.exe is located in the users home directory in: AppData\Local\Programs\Aspera\Aspera Connect\bin\ascp.exe Linux: should be in your user's home directory, cd /home/username/.aspera/connect/bin/ there you'll see the command line utilities where you're going to use ascp. Your command should look similar to this: ascp -P33001 -O33001 -QT -l300M -L- /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path If you wish to upload several files without being requested the password, please use the below command : ASPERA_SCP_PASS=ega-box-password ascp -P33001 -O33001 -QT -l300M /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path/ Explanation of parameters l300M option sets the upload speed limit to 30MB/s. You may wish to lower this value to increase the reliability of the transfer. L option is for printing logs out while transferring files to upload can be a file mask (e.g. '/homes/submitter/*.srf) or a list of files. ega-box-N is your submission account login. Add k2 switch for transfer restarts Check the command line transfer usage for more configuration details. Using FTP to upload your prepared files Use your preferred ftp client. For example, lftp is a popular choice for Linux and Mac users. Use binary mode for file transfers. Use ftp.ega.ebi.ac.uk as the target host. Login with your ega-box username and password. Upload files to your private ega-box upload area. Depending on your network setting you might wish to start FTP in passive or active mode. Using default FTP command line client in Windows Start the command line interpreter: press WinR, type cmd, hit enter Enter ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Use exit command to exit the command line interpreter. Using default FTP command line client in Linux / Unix Open a terminal and type ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Using FTP client FileZilla We recommend the use of FileZilla, a free FTP client . FileZilla is open source software distributed free of charge under the terms of the GNU General Public License. Use the following connection details (File - Site Manager) and add yoursubmission account username and password: Using FTP client FileZilla Select the files you wish to upload and then select upload: Using FTP client Filezilla Using LFTP with TLS We recommend the following to force the use of a secure connection. lftp > set ftp:ssl-force yes We also recommend setting the following for not encrypting the bulk data itself for performance reasons (theauthentication will still be encrypted): lftp > ftp:ssl-protect-data no In order to verify the certificate,the recommended way would be to use the CA certificates from your machine. To do that use this command in lftp adjusting the path to your ca-certificates location. lftp > ssl:ca-file "/etc/ssl/certs/ca-certificates.crt" If that is not possible or certificates are old and you can't update them, you can download the certificates needed from Quo Vadis Digital Repository The two certificates to download in PEM format are: QuoVadis Root CA2 G3 QuoVadis EV SSL ICA G3 Then you can concatenate them in a file one after the other and save it as lftp-certificates.pem Once this is done you have to point the ssl:ca-file variable to the path lftp > set ssl:ca-file "/path/to/lftp-certificates.pem" Also note that you can save this configuration at ~/.lftp/rc Another option is to download the certificates and add them to the ca-certificates of your machine. For example: In RHEL7 and cenots and others box the process to add the certificates globally is: Download the two certificates (in PEM or DER format, doesn't matter) and save them to "/etc/pki/ca-trust/source/anchors/" Run "update-ca-trust extract" Another less secure option is to turn off certificate verification with the following command: lftp > set ssl:verify-certificate false Troubleshooting If you are having problems with Aspera connection timeouts, it can be down to either one of the following. Transfers cannot start the connection fails instantly. Ensure that TCP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewall. The connection is made, transfers are started, but 0 bytes (0%) are uploaded for each file. Ensure that UDP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewal

Documentation submission/data/uploading-files/ftp

Exceptional Responders Initiative

The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

Study phs001145

EGA metadata schema

EGA Schemas In this page, you will find information on how the European Genome-phenome Archive (EGA) manages its metadata standards using both XML Schema Definition (XSD) and JavaScript Object Notation (JSON) formats. If you are not sure what this means, you may want to explore our brief metadata introduction. This information may be of your interest if you are planning to learn more about how the EGA is built and how to wrap around it for other processes. Nevertheless, if you are a common user (e.g. submitter or requester), you would not have to worry about these schemas nor their format, since they are implemented in user-friendly ways for you. Metadata standards are rules that define how to format and structure data of metadata objects (i.e. entities), like EGA's samples or experiments in a consistent manner. These objects are the nodes of the metadata model of the EGA (Figure 1). Figure 1. Diagram of EGA's metadata model. The model's building blocks are objects (e.g. sample), which can reference each other (e.g. an experiment referencing the used samples). Once your files are uploaded, they can also be referenced by Runs and Analyses. The submission object is an object itself that compiles many others. At EGA, we inherit our metadata schemas from the European Nucleotide Archive (ENA), and we have expanded them to include bespoke objects such as "Policy", "Dataset", and "DAC" (Data Access Committee) for our specific use-case: handling sensitive human data. See below a list of all our metadata objects and some context for each. Metadata Object EGA accession Description Examples of metadata fields Study EGAS… Information about the study Study type, study title, study abstract… Sample EGAN… Information about the used samples in the experiment or analysis Taxon ID, scientific name, biological sex, phenotype… Experiment EGAX… Information about the performed experiment Used libraries, sequencing platform, reference to the used samples… Analysis EGAZ… Contains information about the analysis Type of analysis, used assembly, reference sequence… Run EGAR… The run holds information about the files containing the raw reads generated in a run of sequencing Platform, spot descriptor, raw file references… DAC EGAC… Contains information about the Data Access Committee (DAC) DAC contacts, contact emails… Policy EGAP… Contains the Data Access Agreement (DAA) and policy which its usage complies with Policy text, data use ontologies (DUO) codes… Dataset EGAD… Contains the collection of runs/analysis to be subject to controlled access Dataset type, compilation of Run's and Analysis' IDs There are two different sets of schemas, based on their formats, in which the EGA accepts metadata: XSDs (for XML files) and JSON Schemas (for JSON files). EGA's XML Schema Definition . When programmatic submissions are pushed through the European Bioinformatics Institute (EBI) system, XML format is used. The schemas that are applied for this format are defined in XML Schema Definition (XSD) files, which can be found at ENA's GitHub repository. You can find more information on how to validate and submit your data programmatically in our programmatic submission documentation. Furthermore, see at our GitHub repository some XML examples with either made-up values (similar to what you would submit) or descriptive values for each field (just for documentation). EGA's JSON Metadata Schemas . When programmatic submissions are pushed through the Centre for Genomic Regulation (CRG) system, JSON format specifications are used instead. See the full JSON specifications for further details. In conclusion, the EGA metadata schemas are crucial for maintaining the quality and consistency of submitted data. By understanding and following the rules outlined in these schemas, you can ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource. Sample checklists Besides the standards in our schemas, we have another layer called Sample checklists. These are another system that the EGA inherits from ENA, and specifies what attributes are required or allowed for a sample object. The EGA uses these checklists to enforce that, for example, a sample object has the three mandatory attributes: subject ID, sex and phenotype of the individual the sample was taken from. When you submit to EGA, our checklist is automatically selected by default.

Documentation submission/metadata/ega-schema

The Cancer Dependency Map (DepMap)

The Cancer Dependency Map (DepMap) aims to accelerate precision cancer medicine by creating a comprehensive map of tumor vulnerabilities. The DepMap project genomically profiles a wide range of cancer models and characterizes them for their sensitivity to genetic and compound perturbations. The data is computationally analyzed to create a systematic overview of the genetic dependencies and compound sensitivities of cancer types and the predictive biomarkers that point to patient populations most likely to benefit from targeting of these vulnerabilities. The DepMap public portal has become a comprehensive resource to identify cancer vulnerabilities by providing datasets at scale, cutting-edge computational tools, and sophisticated visualization tools that together have accelerated the discovery of novel targets and biomarkers. Please visit Depmap.org to access the public portal.

Study phs003444

Single-cell proteo-genomic reference maps of the human hematopoietic system

We have generated high content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all major hematopoietic cell types in healthy aging and leukemia. Please note raw and integrated gene expression data, cell type annotation, metadata and dimensionality reduction are available as Seurat v3 objects through figshare. Access links are https://figshare.com/s/0fda29b169c719223ee3 (97 surface marker, 9 individuals dataset), https://figshare.com/s/313b5739ff469dac8c01 (197 surface marker, bone marrow and blood dataset), https://figshare.com/s/901bcddb9ee18e226031 (97 surface markers and whole transcriptome dataset) and https://figshare.com/s/24e10bf129fae1918316 (97 surface marker, 15 AML datasets).

Study EGAS00001005593

Genentech Data Access Committee

Dac EGAC00001000055

Center for Technology Licensing at Cornell University for data associated with Nature Medicine 2024 paper

For data access to plasma/tumor/normal samples from the manuscript "Ultrasensitive plasma-based monitoring of tumor burden using machine learning-guided signal enrichment" from Widman et al. Nature Medicine 2024

Dac EGAC50000000207

Atherosclerosis Risk in Communities Study (ARIC-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. At present, the ARIC sIRB has determined that ARIC data cannot be shared with for-profit entities.Related Studies Other ARIC data available include: Imaging studies (ARIC-Imaging), Genetics and genomics (ARIC, phs000280.v8.p2), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): ARIC (phs002988.v1.p1), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637.v1.p1). Available Data Data available for request include ARIC v1-v8 examination cycles, collated annual follow-up communication data for contact years 2-32, and follow-up for mortality, heart disease, and stroke events through 2019. Also included are data from ancillary studies. Objectives The objectives of ARIC are to: 1) investigate associations of factors, including those not previously measured in cohort studies, with prevalence of atherosclerosis and incidence of CHD, clinical stroke and other cardiovascular diseases; and 2) measure cardiovascular disease occurrence and trends and relate these to community levels of, and changes in, risk factors, medical care and atherosclerosis. Background At the time of project initiation, the NHLBI had long recognized the need for longitudinal studies to identify the biochemical and physiological markers and specific environmental factors which place individuals at high risk for the major atherosclerosis diseases. The development of reliable ultrasound examination of peripheral arteries enhanced the expected benefit of such studies. Community surveillance planning began for ARIC in response to recommendations of the 1978 NHLBI Workshop on the Decline in CHD Mortality and has been extended in its purpose to evaluate the large geographic differences in U.S. mortality. Participants Black and white men and women, age 45-64 at entry; sample size: 15,792. Design ARIC is a large-scale, long-term prospective study that measures associations of established and suspected coronary heart disease risk factors with both atherosclerosis and new CHD events in men and women from four geographically diverse communities. The project has two components: community surveillance of morbidity and mortality; and repeated examinations of a representative cohort of men and women in each community. The community surveillance involves abstracting hospital records and death certificates and investigating out-of-hospital deaths. The representative cohorts include approximately 4,000 persons from each community. Community surveillance data includes detailed hospital record abstraction, ECG tracings, and event adjudication. Data from out-of-hospital events in the community include physician, informant, and coroner questionnaires as well as death certificate data and event adjudication. Community surveillance ended in 2014.Cohort participants were examined four times at three year intervals between 1987 and 1998, and have been continuously contacted annually to update their medical histories. Atherosclerosis was measured by carotid ultrasonography. Risk factors studied include: blood lipids, lipoprotein cholesterols, and apolipoproteins; plasma hemostatic factors; blood chemistries and hematology; sitting, supine and standing blood pressures; anthropometry; fasting blood glucose and insulin levels; ECG findings; cigarette and alcohol use; physical activity levels; dietary aspects; and family history. Clinic visits were restarted in 2011 with ARIC visit 5.

Study phs003738

Epigenetic Changes in Immune Response and Oncogenesis Related Genes Caused by Heavy Metal Long-Term Exposure

Our study investigated methylation changes in CpG islands located in immune response and oncogenesis related genes in humans induced by long-term environmental heavy metal exposure. We assessed the methylation levels of 654 CpG sites located on NFKB1, CDKN2A, ESR1, APOA5 and IGF2/H19 genes by targeted bisulfite sequencing (target enrichment by 48.48 Access Array Integrated Fluidic Circuit (Fluidigm, USA) in a cohort of 40 subjects living near a metal mining area (the Kapan mining region, Armenia) and 40 unexposed subjects. We performed linear regression on our data to find differentially methylated positions with adjustment for gender, age, BMI class, smoking, and plasma concentrations of 21 essential and non-essential metals detected by ICP-MS. Our study showed hypomethylation of five CpG sites in the NFKB1 promoter region in the exposed group. According to our findings, the methylation changes of CpG sites in NFKB1, CDKN2A, IGF2 and ESR1 genes are associated with multiple and specific metal exposures. Targeted bisulfite sequencing data obtained for 80 subjects who participated in this study are available through dbGaP. The tables contain information about age, sex, BMI, smoking and exposure status, as well as race and ethnicity of the study participants.

Study phs003392

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