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• PSCP_mutation analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shred by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002231

• PSCP_bisulphite analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. 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/

  Dataset EGAD00001002235

• Sequence data for study: Mobilization of tissue-resident memory CD4+ T lymphocytes from bone marrow and their contribution to a systemic secondary immune reaction

  Resident memory T lymphocytes (TRM) of epithelial tissues and the bone marrow protect their host tissue. To what extent these cells are mobilized and contribute to systemic immune reactions is less clear. Here we show that in secondary immune reactions to the measles-mumps-rubella (MMR) vaccine, CD4+ TRM are mobilized into the blood within 16 to 48 hours after immunization. This mobilization of TRM is cognate: TRM recognizing other antigens are not mobilized, unless they cross-react with the vaccine. We also demonstrate through methylome analyses that TRM are mobilized from the bone marrow. These mobilized cells make significant contribution to the systemic immune reaction, as evidenced by their T-cell receptor Vβ clonotypes represented among the newly generated circulating memory T-cells, 14 days after vaccination. Thus, TRM of the bone marrow confer not only local, but also systemic immune memory.

  Study EGAS00001005475

• Stratton__WGS___Identification_of_Early_Life_Exposures_in_Paediatric_Colonic_Crypts_of_Healthy_Individuals

  The Stratton team uses DNA sequencing for somatic mutations to advance understanding of the causes of cancer. In particular, the investigation of “mutational signatures”, which report the mutational processes operative over the lifetime of each individual, to understand whether they are generated by endogenous or exogenous exposures and the extent to which these vary between human populations. Our work brings together global cancer epidemiology and genomics and is particularly characterised by large-scale multinational studies. Whole genome sequencing of colon crypts from healthy paediatric individuals for identification of early life exposure to carcinogens.

  Study EGAS00001007921

• A Retrospective and Cross-Sectional Analysis of Patients Treated for SCID Since January 1, 1968

  Individuals with a past diagnosis of severe combined immune deficiency (including many cases of "leaky SCID", Omenn syndrome, and reticular dysgenesis) who have undergone blood and marrow transplant, gene therapy, or enzyme replacement in the past may be eligible for 6902. The purpose of 6902 is very similar to 6901, except 6902 is looking backwards at what has already been done in the past (compared to 6901 which is looking into the future). Over 800 patients with SCID are expected to be enrolled on 6902. This makes 6902 the largest study ever to describe outcomes for patients with SCID treated at many different hospitals around North America. One of the most important components of the 6902 study is the "cross sectional" study. Patients who have received their treatments (BMT, gene therapy, enzyme replacement) many years ago are asked to come back to the hospital where they were treated. During this visit, additional research blood work is drawn and information is gathered regarding long-term transplant outcomes such as infections, graft-versus-host disease, autoimmune diseases, and quality of life. This will allow PIDTC researchers to better understand long-term outcomes from procedures that occurred many years ago (sometimes over 30 years ago) - something that is not possible at the present time with 6901. This will help researchers to best design new treatments and clinical trials in the future for children with SCID.

  Study phs001326

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

• eMERGE Phase III Clinical Center at Partners HealthCare

  The Partners HealthCare Biobank is a large research data and sample repository working within the framework of Partners Personalized Medicine. It provides researchers access to high quality, consented samples to help foster research, advance understanding of the causes of common diseases, and advance the practice of medicine. The Partners Biobank provides banked samples (plasma, serum and DNA) collected from consented patients. These samples are available for distribution to Partners HealthCare investigators with appropriate approval from the Partners Institutional Review board (IRB). They are linked to clinical data that originates in the Electronic Medical Record (EMR), as well as additional health information collected in a self-reported survey. The Partners Biobank will be genotyping 25,000 subjects with the Illumina Multiethnic Beadchip 1.6 million SNPs with exome and custom content (> 60,000 LoFs). Of the participants genotyped so far, 4929 of 4962 (99.3%) individuals have genotype data that passed the default quality thresholds for the Infinium array (call rate >= 0.99). We are submitting the genotype data to dbGaP for 4929 subjects with 12 phenotypes (based on icd9 codes). We will do annual releases until we reach the full 25,000 genotyped subjects.

  Study phs000944

• The epigenomic response of skeletal muscle in life-long high-level trained and untrained men and women after acute exercise

  To investigate the influence of lifelong exercise training on the response of skeletal muscle to a bout of acute exercise we generated targeted epigenomic data from long-term endurance (8 men) and strength (8 men) trained individuals and healthy age-matched untrained controls (8 men). Skeletal muscle biopsies were taken from M. vastus lateralis before, directly after, and 3hrs following acute exercise. Control subjects completed one bout of acute endurance exercise and one bout of acute resistance exercise, separated by 4-8 weeks, athletes completed one bout in their respective form of sports. All 96 samples were used for DNA extraction and targeted library construction using a custom Twist Biosciences panel and following EM-methylation tranformation were sequenced (2x150bp paired end) on the Illumina NovaSeq 6000.

  Dataset EGAD50000000512

• DNA Methylation in Prostate Tumor and Paired Benign Tissue for African and European Ancestry Men

  We recruited prostate cancer (PCa) patients undergoing robotic-assisted laparoscopic radical prostatectomy at the University of Chicago Medical Center Urology Clinic between 2011 and 2017. Our study includes 76 African American (AA) and 75 European American (EA) men with PCa of Gleason Score (GS) ≥7, recruited by the Epidemiology Research Recruitment Core at the University of Chicago. All patients consented to the collection of questionnaire data, prostate tissue, and medical records. The study was approved by the Institutional Review Board of the University of Chicago. Following prostatectomy, prostate tissue was sent to the Human Tissue Research Center (HTRC) at the University of Chicago. Each sample underwent histological examination and Gleason scoring by University of Chicago genitourinary pathologists. The presence of adenocarcinoma was confirmed by overexpression of alpha-methylacyl-coenzyme-A racemase (AMACR) and areas for DNA extraction were marked. Tissue samples used for DNA extraction were obtained using with either a 1mm biopunch or laser microdissection of a 100 µm2 area of tissue. Genome-wide DNA methylation profiles were generated using Illumina's Infinium MethylationEPIC BeadChip array kit. Genome-wide SNP data was generated (from benign tissue DNA) using the Illumina Infinium Multi-Ethnic Global-8 v1.0 array at the University of Chicago Genomics Core Facility. We performed imputation using the Haplotype Reference Consortium (HRC, Version r1.1 2016) panel, which includes all samples from the 1,000 Genomes Project (Phase 3), using the Michigan Imputation Server. The imputed SNP data for mQTL analysis was imputed based on genotype SNP data which was all from benign tissue DNA and the methylation data was identified in both tumor and benign tissue, both AA and EA men, and identified QTLs co-occuring with prostate cancer susceptibility loci.Data including SNP genotypes, DNA methylation, tissue type, and participant characteristics will be available in dbGaP.

  Study phs003516

• Longitudinal Study of Urea Cycle Disorders

  Individuals with Urea Cycle Disorders (UCD) cannot remove ammonia, a waste product, from the blood. The purpose of this study is to conduct a longitudinal investigation of the natural history, morbidity, and mortality in people with UCD. This study will look at how people with a UCD grow and develop over time and how often they get sick. The research questions are: What is the prevalence of specific morbid indicators of disease severity, including hyperammonemia, developmental disabilities, and various long-term kidney and liver effects? What is the fatality rate associated with the various forms of UCD? What are the correlations between various biomarkers and disease severity and progression? What is the safety and efficacy of currently used and new UCD therapies? This is a longitudinal study of individuals with urea cycle disorders. Those participating in this study will be evaluated every three to twelve months, depending age and time of diagnosis. Participants two years of age and younger that were diagnosed with UCD within the first four weeks of life will be evaluated every three months. Those who are over two years of age or were diagnosed after four weeks of age will be evaluated every six months. Participants older than 18 years of age will be evaluated once every year.

  Study phs000577

• Clonal_haematopoiesis_in_patients_with_AAA

  Recent advances in genomics have demonstrated that clonal haemopoiesis driven by leukaemia associated somatic mutations is a relatively common phenomenon that increases in frequency with advancing age. Whilst individuals with clonal haemopoiesis have an increased risk of developing haematological malignancies, they also have an increased mortality from other causes. Additionally, certain mutations are almost exclusively seen in individuals aged 70 years or older, whilst others are seen in individuals with non-haematological cancers including breast and ovarian. Recently, clonal haemopoiesis was found to be associated with a significantly increased risk of atherosclerotic cardiovascular disease. This association is thought to be causative with clonally-derived macrophages showing elevated expression of several chemokine and cytokine genes that contribute to atherosclerosis. Another vascular pathology, abdominal aortic aneurysm (AAA), increases with age and shares risk factors with atherosclerosis (including smoking, male sex, high cholesterol). However, the impact of these risk factors and the overlap between AAA and atherosclerosis is poorly understood. To investigate a possible link between clonal haemopoiesis and AAA, we will study DNA samples from 300 patients with AAA and up to 200 controls for evidence of clonal haemopoiesis. This will be done using target DNA enrichment with biotinylated RNA baits followed by high throughput sequencing.

  Study EGAS00001002873

• 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

• Single cell transcriptomics of human adrenal gland reveal chromosomal alterations in adrenocortical cells

  Adrenocortical cells get replenished throughout our lifetime and as such they are a cellular population of high interest in relation to adrenocortical tumours. Single cell transcriptomics of human adrenal gland were performed to identify rare subpopulations of cells, dynamics of cellular turnover and clone expansions in the adrenal cortex. The adrenal gland of this particular individual is characterized by the presence of mutant clone charecterized by aneuploidy in chromosomes 8, 9, 13 and 22, occupying the zona glomerulosa and zona fasciculata. Differential expression analysis of the mutant cells revealed upregulation of MC2R (adrenocorticotropic hormone receptor), CYP21A2, HSD3B2 genes (enzymes involved in cortisol production). Overall, this donor sample is an example of clonal tissue expansions carrying chromosomal rearrangements that likely impact organ morphology and function but are seemingly benign.

  Study EGAS00001007488

• Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

  This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

  Dataset EGAD50000001557

• eMERGE Geisinger eGenomic Medicine (GeM) - MyCode Project Controls

  A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patient agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. For the initial eMERGE Geisinger eGenomic Medicine (GeM) genotyping project, a subset of 1,232 unique samples were genotyped using Illumina HumanOmniExpress-12 v1.0 arrays, and used as population controls for other Geisinger Clinic case cohorts, including abdominal aortic aneurysm and gastric bypass surgery cases. These samples were selected from a larger subset of approximately 6,000 MyCode DNA samples using a partial matching algorithm that included age, sex, and body mass index as variables.

  Study phs000381

• Loss of SDHB promotes dysregulated iron homeostasis, oxidative stress and sensitivity to ascorbate

  Succinate dehydrogenase is a key enzyme in the tricarboxylic acid cycle and the electron transport chain. All four subunits of succinate dehydrogenase are tumor suppressor genes predisposing to paraganglioma, but only mutations in the SDHB subunit are associated with increased risk of metastasis. Here we generated an Sdhd knockout chromaffin cell line and compared it to Sdhb-deficient cells. Both cell types exhibited similar SDH loss of function, metabolic adaptation, and succinate accumulation. In contrast, Sdhb-/- cells showed hallmarks of mesenchymal transition associated with increased DNA hypermethylation and a stronger pseudo-hypoxic phenotype compared to Sdhd-/- cells. Loss of SDHB specifically led to increased oxidative stress associated with dysregulated iron and copper homeostasis in the absence of NRF2 activation. High-dose ascorbate exacerbated the increase in mitochondrial reactive oxygen species, leading to cell death in Sdhb-/- cells. These data establish a mechanism linking oxidative stress to iron homeostasis that specifically occurs in SDHB deficient cells and may promote metastasis. They also highlight high-dose ascorbate as a promising therapeutic strategy for SDHB-related cancers.

  Study EGAS00001005279

• Barcoding reveals complex clonal dynamics of de novo transformed human mammary cells

  Most human breast cancers have already diversified genomically when they first become clinically evident, by which time extensive heterogeneous histopathologies, transcriptomes and growth patterns are also apparent. Accordingly, important initial events and the cellular context in which they occur have been difficult to characterize. Using DNA barcoding, we now demonstrate the high efficiency with which both purified basal and luminal cells isolated directly from normal adult human mammary tissue can be rapidly transformed by a single oncogene (KRASG12D) resulting in the production within 8 weeks in vivo of serially transplantable, polyclonal, invasive ductal carcinomas that are phenotypically heterogeneous and transcriptionally distinct from the initial cells transduced. Barcoding also revealed a consistent dramatic change in the clonal content of passaged tumours. This system thus provides a powerful new platform for examining early events in the genesis, evolution and treatment response of malignant human mammary cells generated using defined mutations.

  Study EGAS00001001310

• Pangenomic classification of pituitary adenomas

  Pituitary neuroendocrine tumors (PitNETs) are common. They are classified in five main histological types: PitNETs of POU1F1 (Pit1) lineage -lactotroph, somatotroph and thyrotroph -, gonadotroph, and corticotroph PitNETs. Pituitary tumorigenesis is poorly understood. We report here a pangenomic characterization of 134 PitNETs from all types, based on exome, genome, transcriptome, miRnome and methylome. Pit1 lineage was associated with a specific epigenetic signature of diffuse DNA hypomethylation, and correlated with expression of Pit1 markers and chromosomal instability. 45% of somatotroph PitNETs showed GNAS mutations. GNAS-wild type somatotroph showed a distinct transcriptome profile, expressing gonadotroph transcription factor NR5A1 (SF1). Sparsely granulated somatotroph PitNETs was classified apart from somatotroph, owing to a thyrotroph transcriptome signature. 43% of corticotroph PitNETs showed USP8 mutations, sharing a low epithelial-mesenchimal transition (EMT) transcriptome signature. Silent corticotroph PitNETs showed a gonadotroph transcriptome signature evoking transdifferentiation, and lost somatostatin target SSTR5 expression.

  Study EGAS00001003642

• Analysis of T-cell receptor clonotypes in tumor micro-environment identifies shared cancer type-specific signatures

  Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias towards the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T-cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus- driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T-cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (ie viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer, but in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific motifs that were unique to each cancer type, suggesting they may be enriched for specificity to common antigens found in the tumor microenvironment. The identification of shared TCRs in infiltrating tumor T-cells not only adds to our understanding of the tumor adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

  Study EGAS00001005480

• Long read transcriptome of DM1 patients whole blood

  DM1 is characterized by dysregulation of alternative mRNA splicing, to an quantitative as well as qualitative extend that is heterogenous between clinically similar patients. Hundreds of transcripts have been identified that can be misspliced in DM1, and for many of these it is still unclear whether they generate stable proteins in DM1 patients. We generated long-read transcriptome data of DM1 patients whole blood after hemoglobin depletion. Each sample is a mix of 5 patients of varying age.

  Study EGAS50000000196

• South African Blood Regulatory (SABR) Resource

  Functional genomics resources are critical for interpreting human genetic studies, however they are predominantly from European-ancestry individuals. Here we present the South African Blood Regulatory (SABR) resource, a map of blood regulatory variation that includes three South Eastern Bantu-speaking groups. Using paired whole genome and blood transcriptome data from over 600 individuals, we map the genetic architecture of 40 blood cell traits derived from deconvolution analysis, as well as expression, splice, and cell type interaction quantitative trait loci (QTL).

  Study EGAS50000001008

• Longitudinal study of whole blood gene expression in Kenyan children exposed to malaria

  We have collected RNA samples from whole blood of Kenyan children exposed to malaria in the Kilifi region of Kenya. Collections were performed each year from 2015 until 2018. This is a follow-up study to that described in Bediako et al. (in preparation). The SIMS consortium is seeking to identifying the underlying reasons why some children are more susceptible to malaria than others. In this study we hope to track changes in children’s immune systems over time which relate to the number of malaria episodes they experience. 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/

  Dataset EGAD00001015405

• What is a DAC?

  What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant.  For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source.  Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions.  You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks.  Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.

  Documentation access/data-access-committee/what-is-dac

• FinHer_Breast_Cancer_Study

  The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.

  Study EGAS00001000648