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• Genome and transcriptome sequence data from a chordoma patient

  Genome and transcriptome sequence data from a chordoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003040

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002891

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005878

• Genome and transcriptome sequence data from a chondrosarcoma patient

  Genome and transcriptome sequence data from a chondrosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005848

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005838

• Genome and transcriptome sequence data from a chordoma patient

  Genome and transcriptome sequence data from a chordoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005871

• Single Cell DNA amplicon sequencing of 12 B-ALL patients (at diagnosis and during treatment)

  This dataset contains single cell DNA amplicon sequencing of 12 B-ALL patients. For all patients a diagnosis sample was processed, while 4 patients were also followed up during treatment, summing up to a total of 23 samples. Mutations were called in the predefined set of amplicons.

  Dataset EGAD00001006955

• Genome and transcriptome sequence data from a meningioma patient

  Genome and transcriptome sequence data from a meningioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004920

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002019

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008943

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008941

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010943

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011000

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002570

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005890

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010965

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011022

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002541

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003060

• Genome and transcriptome sequence data from a angiosarcoma patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004690

• DNA methylation-based classification of sinonasal tumors [DNA sequencing]

  This dataset contains raw exome sequencing data from nine sinonasal undifferentiated carcinoma FFPE samples and matched normal tissue that were assigned to a shared epigenetic class using DNA methylation-based classification. They were analyzed using the Twist Human Core Exome Plus Kit (Twist Bioscience) on a NovaSeq 6000 sequencer.

  Dataset EGAD00001009668

• Genome and transcriptome sequence data from a osteosarcoma patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004628

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004629

• RNAseq data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - MUMC

  The dataset includes fastq files from 4 NEN tumors or metastases and matched PDTOs. The sequencing was done with either a Nextseq 2000 or a NovaSeq 6000 instrument.

  Dataset EGAD00001009991

• Genome and transcriptome sequence data from a paraganglioma patient

  Genome and transcriptome sequence data from a paraganglioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008935

• RNAseq in ASD patients and controls

  RNA sequences of a total of 24 samples, including 13 unrelated ASD patients (13 males) and 11 adult individuals of Spanish origin as controls (4 males, 7 females). The RNAseq study was conducted on a HiSeq 4000 (Illumina) and paired-end sequences were obtained (fastq files).

  Dataset EGAD00001008160

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004649

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002593

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002046

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010957

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011032

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002991

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002996

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003024

• Genome and transcriptome sequence data from a mesothelioma patient

  Genome and transcriptome sequence data from a mesothelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003618

• Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Dataset EGAD00001004018

• Whole exome sequencing for HELIC

  The HELIC study has been whole genome sequencing individuals from 2 Greek isolatedpopulations at 1x depth. The genotype calling process crucially involves a VQSR stepfollowed by imputation-based refinement. We have been investigating optimal ways toincrease calling accuracy. To aid us in setting appropriate parameters for VQSR and otherQC steps, we have carried out whole exome sequencing of a small number ofHELIC samples.

  Dataset EGAD00001001638

• Congenital anosmia 2

  Congenital anosmias can be complete (the lack of a sense of smell) or specific (the inability to detect specific smells). Here we obtained genomic DNA from families with multiple individuals with anosmia, suggesting they are congenital. These include those inherited in a manner consistent with dominant and recessive alleles. We have sequenced the exomes of both affected and unaffected family members on the Illumina platform.

  Dataset EGAD00001002228

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002623

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004922

• Genome and transcriptome sequence data from a hemangioma patient

  Genome and transcriptome sequence data from a hemangioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005900

• Genome sequence data from a metastatic rectal carcinoma patient

  Genome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010972

• Genome and transcriptome sequence data from a myoepithelioma patient

  Genome and transcriptome sequence data from a myoepithelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010938

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010939

• Genome sequence data from a metastatic paraganglioma patient

  Genome sequence data from a metastatic paraganglioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010985

• Genome and transcriptome sequence data from a thymoma patient

  Genome and transcriptome sequence data from a thymoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011039

• Metastases of a cancer of unknown primary (CUP)

  Dac EGAC00001001484

• A Study to Assess the Cardiovascular, Cognitive, and Subjective Effects of Atomoxetine in Combination with Intravenous Methamphetamine

  The Study to Assess the Cardiovascular, Cognitive, and Subjective Effects of Atomoxetine in Combination with Intravenous Methamphetamine started in 2007 and ended in 2011. It was a small pilot study that included methamphetamine abusing individuals and healthy control participants aged 18-50 years. Participants who qualified over the telephone were scheduled to visit the London Laboratory at the UCLA Semel Institute for Neuroscience and Human Behavior for the In-Person Screening Phase. The screening procedures, usually scheduled over two visits, determined if participants were eligible to complete the subsequent study visits. Both groups completed identical screening procedures, including a SCID diagnostic interview to rule out any major psychiatric disorders. Methamphetamine users also answered questionnaires specific to their drug use. Urine toxicology for marijuana, opiates, cocaine, methamphetamine, and benzodiazepines were monitored at the beginning and throughout the study. Additionally, participants had blood samples to test for Rapid Plasma Reagin (exposure to syphilis), purified protein derivative (PPD), HIV and Hepatitis-C (HCV). Positive test results were relayed by a study physician and resulted in termination from continuing in the study. The inpatient portion of the study lasted a total of 24 days. To confirm compliance with abstinence from illicit and prescription drug use for the duration of the study, urine and breath alcohol testing was performed for both inpatient (methamphetamine users) and outpatient (healthy control) groups. Each subject was randomized to receive either atomoxetine (80 mg daily) or placebo. During inpatient days of the study, a study physician oversaw research subjects daily and experimental procedures were conducted in the General Clinical Research Center (GCRC). During drug administration sessions, heart rate and blood pressure were assessed at frequent intervals. Experimental sessions lasted around three hours and were conducted at approximately the same time of day for a given participant. Lunch was provided to participants at 11:30am with the prohibition of caffeine on study days involving methamphetamine administration. Participants were provided with smoke breaks as needed to assure that acute nicotine withdrawal did not negatively impact performance on cognitive testing. The following outlines the day to day procedures for a methamphetamine inpatient: Phase I Inpatient Study (15 days total) Days 1-3: On the day of admission, participants received blood tests and an EKG in order to determine that they had no occult medical conditions which would make their participation in the study medically contraindicated. A three day washout period was provided at the beginning of the study to establish an appropriate methamphetamine-free baseline for testing. Days 4-6: Participants completed cognitive test batteries to assess inhibitory control including self-report measures and cognitive testing, as well as up to three MRI scanning sessions. Day 7: On day 7, at 9AM and 1PM, participants received methamphetamine in a single-blinded condition. It was administered as two IV infusions of 15mg separated by a 60min break. The total dose of IV methamphetamine was 30mg. Participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in the absence of study medication. Day 8: On day 8 we evaluated the safety and residual effects of the methamphetamine administered on the previous day. Days 9-10: After demonstrating medical and psychiatric stability of the initial methamphetamine infusion, participants were then randomized to receive placebo or atomoxetine (0 or 40mg) under double-blind conditions, which would be given at 8AM on both study days. Days 11-12: On days 11 and 12, participants remained in the GCRC and took two doses of test compound atomoxetine (0 or 40mg) at 8AM and 8PM. On the morning of day 12, participants completed a series of cognitive testing. Day 13: On day 13, participants remained in the GCRC, and took two doses of the test compound atomoxetine (0 or 40mg) at 8AM and 8PM. At 9AM and noon, they received methamphetamine under double-blind conditions administered non-contingently as two infusions of 0 or 15mg by IV (intravenously), with each infusion separated by 60min. The total dose of IV methamphetamine that each participant received was 30mg. As before, participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in those participants receiving study medication. Day 14: On day 14 at 8AM, participants received their final dosing of the first test compound (atomoxetine 0 or 40mg). At 9AM and 1PM, participants selected between methamphetamine infusion or money using double-blind conditions in a multiple-choice self-administration paradigm. Participants were able to take up to two infusions of 0 or 15mg of methamphetamine, separated by 60min. The total dose of IV methamphetamine that each participant received on day 14 was 30mg. Participants were clinically evaluated by continuous cardiac telemetry, serial EKG and measurement of vital signs, during and after infusions, in order to determine the medical safety of methamphetamine infusion in those participants receiving study medication. At 5pm on day 14 discharge laboratory studies were drawn. Day 15: On day 15, a final EKG was performed as well as a review of discharge laboratory studies, including review of the EKG and continued medical and psychiatric stability. Upon clearance from a physician, participants were discharged on day 15. Participants spent at least 2 weeks (14 days) out of the hospital prior to returning to the UCLA GCRC for inpatient Phase II. Phase II Inpatient Study (9 days total) Day 1-2: On the day of re-admission, participants received blood tests and an EKG. A two day washout period was provided at the beginning of the study to establish an appropriate methamphetamine free condition for safe administration of the second test compound condition. Days 3-4: On days 3 and 4, given medical stability, participants were then switched to the opposite test compound (atomoxetine 0 or 40mg) under double-blind conditions, in the same manner as in Days 9-10 in Phase I. Days 5-6: Same procedure as in Days 11-12 in Phase I but with opposite medication condition. Day 7: Same procedure as in Day13 in Phase I but with opposite medication condition. Day 8: Same procedure as in Day14 in Phase I but with opposite medication condition. Day 9: Same procedure as in Day14 in Phase I but with opposite medication condition. For healthy control participants, the study consisted of 30 days or fewer of out-patient testing. Healthy control participants had an extensive screening, including a history and physical exam performed by a study physician, an EKG, and laboratory studies performed to assess for medical or psychiatric conditions. Control participants meeting criteria were invited back to UCLA to undergo cognitive testing, and some participants received fMRI scans. Participants were required to refrain from illicit and prescription drug use for the duration of the study, which was confirmed with urine toxicology and breath alcohol level testing on examination days. Caffeine was restricted on study days for least 2 hours prior to cognitive testing and MRI scans. Participants were permitted to drink their normal daily intake of caffeine, given the caveat above. On study days, cigarette smoking was permitted to match conditions used with methamphetamine users. The incorporation of smoke breaks during the test day assured that acute nicotine withdrawal did not negatively impact performance on cognitive tests or neuroimaging. The following outlines procedures for healthy control participants: For normal controls, participation involved one day of outpatient screening, and one day of baseline cognitive testing and possible MRI scans. After these procedures were completed, participants were randomized to the first test compound (atomoxetine 40mg or placebo), to be taken once daily in the morning for 2 days. It was then increased to twice daily for the next 3 days, followed by a final dose (40mg or placebo) on the sixth day of study medication. Participants were also asked to bring their pill packages to assess compliance with the study medication. Additionally, control participants completed a series of repeated-measures cognitive testing (on placebo or atomoxetine, respectively) and possibly two fMRI sessions (separated by a short break). After at least a four-day washout period, control participants were instructed to start the opposite test compound (atomoxetine 40mg or placebo), again to be taken once daily in the morning for two days, then twice daily for 3 days, reaching the final dose (40mg or placebo) of the second test compound in the morning. Participants were again asked to bring their pill packages to assess compliance and had blood drawn to assess atomoxetine levels. Control participants then completed another series of cognitive testing and fMRI testing sessions. They were subsequently discharged from the study. Normal control participants returned two weeks after completion of both study phases in order to complete assessments to their physical and psychological status following treatment.

  Study phs001195

• NIH RECOVER: A Multi-Site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults

  The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal, observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients with and without known SARS-CoV-2 infection will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows: Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection. Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection.Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs:1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults (this study)The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. A summary of information available by request in the RECOVER Adult Cohort (this study) can be reviewed via the "Adult Cohort Dataset Release Notes" and the "REDCap Codebook for the Adult Cohort" documents.2) The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study: A Multi-Center Observational Study (data not yet released)The RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization.3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection (data not yet released)The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003463

• Implementation of the GDPR

  Data Protection 1 About the EGA The European Genome-phenome Archive (EGA) was formally launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. In late 2012, with the signing of a memorandum of understanding (and subsequent formal agreement in 2016) between EMBL-EBI and the Centre for Genomic Regulation (CRG), the EGA formally became a joint project of the two institutes. The two institutes work together to support the EGA services, including supporting submissions, web site, strategic leadership, and data infrastructure developments. 2 EMBL-EBI & GDPR The EGA is co-managed by EMBL-EBI and CRG. EMBL-EBI is an international organisation established by treaty and has certain privileges and immunities (e.g. exemptions from the application of national law) and also may self-regulate its activities (e.g. establish its own institutional legal framework) within the framework of its founding act of 1973. The General Data Protection Regulation (GDPR) is a European Union (EU) regulation that legislates how organisations can share and process personal data of EU citizens. EMBL places great value in maintaining collaboration with researchers who are subject to GDPR. For that reason, it is of utmost importance for EMBL to handle data received from those collaborators in a secure and responsible manner. Mindful of its public mandate and the sensitivity of the data it handles, EMBL has always ensured a high level of data protection in its activities. Since the introduction of GDPR in May 2018, EMBL has established its internal policy on General Data Protection (IP68), exercising its right to self-regulate its operations,., IP 68 establishes a robust personal data protection framework that provides for data protection principles, enforceable data subject rights and oversight and redress mechanisms offering a level of protection comparable with GDPR. 3 CRG & GDPR The Centre for Genomic Regulation (CRG) is an international biomedical research institute of excellence, created in July 2000 and mainly participated by the Catalan Government. It is a non-profit foundation and its mission is to discover and advance knowledge for the benefit of society, public health and economic prosperity. The CRG is a CERCA center. CERCA is the collective organisation for all research centres of excellence in Catalonia. CERCA ensures these centres develop successfully by promoting synergies and strategic cooperation improving their visibility and the impact of their research and promoting the dialogue amongst both public and private stakeholders. As a legal entity based in Spain and operating within the EU, the CRG ensures the compliance with the GDPR and the legal regulations on personal data protection applicable at the national level, as well as any other legislation that may replace, modify or supplement the above-mentioned in terms of personal data protection. 4 EGA & GDPR EGA GDPR Schema 4.1 Genetic and phenotypic data Within GDPR, there are two main actors: data controllers and data processors. Data controllers are persons or entities which determine the purposes and means that the personal data may be processed, e.g. companies, researchers, or universities. For EGA, the data controller is ultimately the data producer and the submitter(s) who submit the data to EGA. The data controller also creates a Data Access Committee (DAC) who will decide on data access permissions at EGA. Data processors are the persons or entities which process the data on behalf of a data controller. With regard to GDPR, EGA is a data processor as it processes data as instructed by the data controller. GDPR applies to any organisation which accesses personal data from an individual within the EU. Under GDPR, personal data is defined as any data that is identifiable, including names and email addresses as well as health-related and genetic data. EGA does not accept personally identifiable data except genetic and phenotypic data, so all other data submitted to EGA, such as names and addresses, must be pseudonymised. GDPR requires that data controllers implement data protection principles, such as data minimisation, to minimise the risk of data leakage, and protect the rights of the data subjects. As a data processor, EGA has a set of security policies that are followed to minimise the risk of unauthorised data access or data loss. In its role as a data processor, EGA requires all submitters to sign a Data Processing Agreement (DPA) when the submission account is first created. This agreement is only required to be signed once per submitter, and will remain valid for future submissions to EGA. 4.2 Other personal data The EGA also collects personal data as part of our interactions with submitters, data access committees, and researchers accessing data distributed by EGA. The below privacy notices explain what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Privacy Notices for EGA Title Version Last Updated EGA Data Access Committee Account Privacy Notice for EGA Data Access Committee Account 1.0 February 6, 2019 EGA User Account Privacy Notice for EGA User Account 1.0 February 6, 2019 EGA Helpdesk Service Privacy Notice for EGA Helpdesk Service 1.0 February 6, 2019 EGA Website Service Privacy Notice for EGA Website Service 1.0 February 6, 2019 Documentation Title Version Description EGA Security Overview Security Document 1.1 The EGA Security Document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. EGA Data Processing Agreement Data Processing Agreement 1.5 The Data Processing Agreement must be completed and returned as part of the submission process. Please note that this document is non-negotiable. Authorised Submitters Authorised Submitters Formulary 1.0 The Authorised Submitters Form must be completed and returned as part of the submission process. Please list all those that should have access to the submission account in order to submit to the EGA should be detailed here. Dispute Resolution Any controversy or claim arising out of, or relating to, the DPA (including the enforceability or breach thereof, any question regarding its existence, validity or termination) or relating to the EGA Service shall be resolved using the internal dispute resolution mechanisms of EGA including those related to Data Protection. The EGA’s internal dispute resolution mechanism has the following procedure: EGA OPERATIONAL PHASE: Meetings between EGA staff and the Data Controller.LEGAL MANAGEMENT PHASE: Meetings between legal teams of EMBL, CRG and the Data Controller. DIRECTION MANAGEMENT PHASE: Negotiation between the legal representatives of EMBL, the CRG and the Data Controller. If the internal dispute resolution mechanism doesn’t resolve the controversy or claim the next phase is:ARBITRATION PHASE: Resolution by arbitration under the WIPO Expedited Arbitration Rules (“Rules”).

  Documentation about/privacy-notice