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• scRNAseq of co-culture of human organoids with polarized pro-inflammatory or anti-inflammatory macrophages

  In order to know if the mechanisms we identified in mice – demonstrating that macrophages are able to orchestrate the intestinal regenerative process – are conserved in humans we develop a co-culture system with human intestinal organoids and human polarized macrophages. We co-culture human organoids with pro-inflammatory or anti-inflammatory macrophages for 48h. On day 3 cells were collected to perform single cell RNA sequencing.

  Dataset EGAD50000000675

• Single cell RNA sequencing of co-culture of human organoids with polarized pro-inflammatory (M1) or anti-inflammatory (M2) macrophages

  In order to know if the mechanisms we identified in mice – demonstrating that macrophages are able to orchestrate the intestinal regenerative process – are conserved in humans we develop a co-culture system with human intestinal organoids and human polarized macrophages. We co-culture human organoids with pro-inflammatory or anti-inflammatory macrophages for 48h. On day 3 cells were collected to perform single cell RNA sequencing.

  Dac EGAC50000000270

• 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

• using-ega-account

  Using your EGA account The purpose of this page is to help you access and download the data you have been granted permission to view through your EGA account. To obtain an EGA account please register here. Once your account is created, you can find details on how to manage your EGA account here. EGA access policy (New account holders please read) Access to EGA services are only provided to EGA account holders. EGA accounts are created, updated and closed upon direct instruction from the relevant DAC contact, using the EGA account management tools or through EGA Helpdesk. As part of the EGA account creation process, the EGA account holder must reset their password when instructed. Password resets are checked and verified usually within 24 business hours, during which time the EGA account is inaccessible. EGA accounts are assigned on an individual basis for the exclusive use of the registered EGA account holder; log-in details must remain private and only be used by the EGA account holder. Controlled access data files are only provided, in accordance to the permissions set by the DAC, to EGA account holders. EGA controlled access data files are encrypted prior to download and must be decrypted on the EGA account holders side. EGA account holders are provided access to the EGA download streamer to download access approved datasets and files therein. The EGA download streamer represents the primary means for the EGA account holder to download access approved datasets and files therein. EGA account holders may be provided with an EGA download account for accessing approved datasets and files therein, using FTP or Aspera in response to clearly defined technical reasons, which may restrict the use of the EGA download streamer. It is the sole responsibility of the EGA account holder to ensure full compliance to all terms and conditions of the Data Access Agreement are met once data is downloaded from the EGA. Should you move institute you must contact all Data Access Committee's contacts to update your details and, if necessary, re-apply for data access. The Data Access Agreement (DAA) is a contract made between the DAC and the EGA account holder; the EGA is not responsible for enforcing the DAA. EGA reserves the right to place EGA accounts 'onhold', pending DAC approval to re-activate, should EGA account 'misuse' be suspected. Further information Introduction to the EGA Frequently Asked Questions Subscribe to the EGA mailing list

  Documentation using-ega-account

• Using your EGA account

  Using your EGA account The purpose of this page is to help you access and download the data you have been granted permission to view through your EGA account. To obtain an EGA account please register here. Once your account is created, you can find details on how to manage your EGA account here. EGA access policy (New account holders please read) Access to EGA services are only provided to EGA account holders. EGA accounts are created, updated and closed upon direct instruction from the relevant DAC contact, using the EGA account management tools or through EGA Helpdesk. As part of the EGA account creation process, the EGA account holder must reset their password when instructed. Password resets are checked and verified usually within 24 business hours, during which time the EGA account is inaccessible. EGA accounts are assigned on an individual basis for the exclusive use of the registered EGA account holder; log-in details must remain private and only be used by the EGA account holder. Controlled access data files are only provided, in accordance to the permissions set by the DAC, to EGA account holders. EGA controlled access data files are encrypted prior to download and must be decrypted on the EGA account holders side. EGA account holders are provided access to the EGA download streamer to download access approved datasets and files therein. The EGA download streamer represents the primary means for the EGA account holder to download access approved datasets and files therein. EGA account holders may be provided with an EGA download account for accessing approved datasets and files therein, using FTP or Aspera in response to clearly defined technical reasons, which may restrict the use of the EGA download streamer. It is the sole responsibility of the EGA account holder to ensure full compliance to all terms and conditions of the Data Access Agreement are met once data is downloaded from the EGA. Should you move institute you must contact all Data Access Committee's contacts to update your details and, if necessary, re-apply for data access. The Data Access Agreement (DAA) is a contract made between the DAC and the EGA account holder; the EGA is not responsible for enforcing the DAA. EGA reserves the right to place EGA accounts 'onhold', pending DAC approval to re-activate, should EGA account 'misuse' be suspected. Further information Introduction to the EGA Frequently Asked Questions Subscribe to the EGA mailing list

  Documentation download/using_ega_account

• Influence of the Microbiome on Epigenetic Mechanisms in IBD

  Live CD4 T cells were sorted from inflamed and non-inflamed tissue samples of IBD patients or from healthy and IBD blood samples. ATAC-Seq libraries were generated from live CD4 T cells sorted from i) inflamed and non-inflamed tissue samples, ii) healthy and IBD blood samples, or from iii) CD4 T cell subsets polarised from healthy blood samples. After isolating crude nuclei, live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry. On the other hand, single cell RNA-Seq libraries were generated exclusively from inflamed and non-inflamed tissue samples of Crohn’s disease patients. Briefly, live CD4 T cells were captured and encapsulated before cDNA amplification using the 10X Genomics Chromium Platform. Samples were prepared as outlined by 10x genomics Single Cell 3’ Reagent Kits v2 user guide. Samples were sequenced on a HiSeq 2500 with the following run parameters: Read 1 – 26 cycles, read 2 – 98 cycles, index 1 – 8 cycles.

  Dataset EGAD00001011066

• Molecular characterization of invasive lobular carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Dataset EGAD00001000288

• Whole exome sequencing (WES) of EBV- primary central nervous system lymphoma (PCNSL)

  This dataset contains whole exome sequencing (WES) of 29 HIV- EBV- primary central nervous system lymphoma (PCNSL) tumors and 5 activated B-cell-like PCNSL (ABC-PCNSL) and activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL) cell lines (TK, HKBML, OCI-Ly3, HBL-1, TMD-8). Cases with secondary involvement of the CNS were excluded. DNA was extracted with AllPrep DNA/RNA FFPE kit and libraries were prepared using the Agilent SureSelect Human All Exon v6 + UTR kit. Paired end reads were aligned to GRCh37 using bwa mem v.0.7.17, and reads were sorted and duplicated were marked in the final BAM files. Access to this data is controlled. There are a number of steps that a researcher must take to obtain access to this data, including execution of a Data Access Agreement between the institutions. The process is overseen by the Technology Development Office; please contact our general email address TDOadmin@phsa.ca. Please only click the "request data" button on the EGA website after a Data Access Agreement is fully executed.

  Dataset EGAD50000000451

• Sudden Death in the Young Case Registry

  Knowledge gaps persist about the incidence of and risk factors for sudden death in the young (SDY). The SDY Case Registry is a collaborative effort between the National Institutes of Health, the Centers for Disease Control and Prevention, and the Michigan Public Health Institute. Its goals are to: (1) describe the incidence of SDY in the United States by using population-based surveillance: (2) compile data from SDY cases to create a resource of information and DNA samples for research; (3) encourage standardized approaches to investigation, autopsy, and categorization of SDY cases; (4) develop partnerships between local, state, and federal stakeholders toward a common goal of understanding and preventing SDY; and (5) support families who have lost loved ones to SDY by providing resources on bereavement and medical evaluation of surviving family members. Built on existing Child Death Review programs and as an expansion of the Sudden Unexpected Infant Death Case Registry, the SDY Case Registry achieves its goals by identifying SDY cases, providing guidance to medical examiners/coroners in conducting comprehensive autopsies, evaluating cases through child death review and an advanced review by clinical specialists, and classifying cases according to a standardized algorithm. The SDY Case Registry also includes a process to obtain informed consent from next-of-kin to save DNA for research, banking, and, in some cases, diagnostic genetic testing. The SDY Case Registry will provide valuable incidence data and will enhance understanding of the characteristics of SDY cases to inform the development of targeted prevention efforts. For cases where informed consent has been obtained for research genomic sequencing has been performed. On these cases genomic data, phenotype information and on a limited number of cases redacted autopsy reports will be available through dbGaP.

  Study phs003221

• Single-cell multidimensional profiling of tumor cell heterogeneity in supratentorial ependymomas

  Supratentorial ependymomas (ST-EPNs) are aggressive and treatment-resistant pediatric brain tumors that form along the human cortex, with suspected origin from radial glia cells. Although histologically similar, ST-EPNs are molecularly classified into six distinct subgroups, many of them remaining understudied. Here, we integrated molecular cell states and spatial architecture to resolve the cellular origins and aberrant differentiation trajectories of ST-EPNs at single-cell resolution. We show that, while all ST-EPNs display a unified origin from neuroepithelial cells, different subgroups harbor highly diverse cell states and differentiation potential associated with neural or ependymal differentiation. Spatial mapping uncovered a higher-order structural tumor organization driven by presence of the mesenchymal state, and refines classical histological features based on detailed molecular resolution. By benchmarking a morpho-molecular cell-state classification system in different disease models and human tumors, we identified four cellular subtypes defined by the architecture of neurite-like extensions that mediate either self-renewal or fast, saltatory invasive phenotypes reminiscent of neurons during neurodevelopment. Collectively, our study provides a comprehensive framework for the study of ST-EPN cellular states, and reveals biologically relevant tumor compartmentalization with potential clinical implication.

  Study EGAS50000001513

• Transcription Factor Analysis of SLE

  Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with protean manifestations. This study identifies two histone marks of activation and the binding of p300 genome-wide in three cell types and three clinical subsets to better understand cell-specific effects and differences across clinical subsets. Results: We examined 20 patients with SLE and 8 controls and found the TNF, IL-2/STAT5, and KRAS pathways were identified across multiple cell types and ChIP data sets. Patients with cutaneous lupus and lupus nephritis generally had less dramatically altered chromatin than the general SLE group. Conclusions: NFkB and classical inflammatory pathways were strongly associated with increased peak heights across all cell types but were the highest-ranking pathway for all three antibodies in monocytes according to fgsea analysis. IL-6 Jak/STAT3 signaling was the most significant pathway association in T cells marked by H3K27ac change. Therefore, each cell type experiences the disease process distinctly although in all cases there was a strong theme of classical inflammatory pathways. These studies define important cell type differences and emphasize the breadth of the inflammatory effects in SLE.

  Study phs003713

• Mutational analysis of an oligoprogressive sarcomatoid hepatocellular carcinoma treated with an immune checkpoint inhibitor.

  In this study, we describe a patient diagnosed with metastatic sarcomatoid hepatocellular carcinoma that showed a remarkable tumor response to Nivolumab, an immune checkpoint inhibitor, followed by an oligoprogression. Molecular analysis of the primary tumor in addition to a bone and brain metastasis was performed and we were able to identify driver genetic alterations indicating a possible role in the tumorigenesis process besides some alterations that may be associated with metastasis.

  Study EGAS00001005064

• SCLC study MGH - WES dataset

  For whole-exome sequencing 1 µg of DNA from fresh-frozen tumors was fragmented by sonication technology (for DNA from fresh-frozen tumors: Bioruptor, diagenode, Liѐge, Belgium; for DNA from FFPE material: Covaris). The fragments were end-repaired and adaptor-ligated, including incorporation of sample index barcodes. After size selection, libraries were subjected to an enrichment process with Sure select XT (Agilent). The final libraries were sequenced with a paired-end 2×75 bp protocol for an average coverage of 100-120x

  Dataset EGAD00001003970

• Hyperdiploid Acute Lymphoblastic Leukemia RNA-Seq

  Few genetic drivers of children with hyperdiploid precursor B-cell acute lymphoblastic leukemia (ALL) have been identified to date. In an effort to detect novel genomic rearrangements that could be promoting leukemogenesis in this subset of patients, we sequenced ribosomal RNA-depleted transcriptomes isolated from 5 hyperdiploid acute lymphoblastic leukemia samples. In addition to looking for novel genomic rearrangements, we also sought to identify transcripts that could be created as a result of a novel posttranscriptional process. Surprisingly, we identified transcripts created as the result of exon circularization. The results of our studies are present in the paper "Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types" published in PLoS ONE (PMID: 22319583).

  Study phs000522

• Cross-site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms of CIMAC-CIDC Network

  The Cancer Immune Monitoring and Analysis Centers (CIMACs) and the Cancer Immunologic Data Commons (CIDC)  has engaged in efforts to harmonize Whole-exome (WES) and RNA-sequencing (RNA-seq) data from three different experimental platforms (MD Anderson, NCI MoCha lab, and Broad Institute) and are using a series of developed pipelines to process the early trial samples. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the CIMACs-CIDC conducted a systematic harmonization study. DNA and RNA were centrally extracted from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) non-small cell lung carcinoma (NSCLC) tumors and distributed to three centers for WES and RNA-seq profiling

  Study phs002295

• Myeloid cell programming in patients with non-medullary thyroid carcinoma

  This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

  Dataset EGAD00001008108

• Mutated H3 Histones Drive Human Pre-Leukemic Hematopoietic Stem Cell Expansion And Promote Leukemic Aggressiveness

  Leukemogenesis is a stepwise progression from mutated, pre-neoplastic hematopoietic stem cells (HSCs) to full-blown leukemia. Our ability to prevent or treat acute myeloid leukemia (AML) is limited by our incomplete understanding of the epigenetic disruption that is central to this process, including improper histone methylation. Comprehensive analysis of 16 histone H3 genes in 434 primary AML samples identified Q69H, A26P, R2Q, R8H and K27M/I mutations (1.6%), and a higher incidence in secondary AML (s-AML) (9%). We establish that these mutations are important early events in leukemogenesis. They occur in pre-leukemic HSCs, increase the frequency of functional human HSCs, and alter differentiation. The mutations are present in the major leukemic clones in primary samples, and the mutant histones amplify leukemic aggressiveness with increased proliferation, expansion of leukemic progenitor and blast cells, and superior competitiveness in vivo. These effects are dependent on the specific mutation. Genome-wide analysis of K27 mutants revealed increased expression of genes involved in erythrocyte and myeloid differentiation with a corresponding decrease in histone H3 K27 tri-methylation and increase in K27 acetylation. The functional impact of histone mutations is independent of RUNX1 mutations, although they can co-occur. These data establish the involvement of H3 mutations as initial drivers of pre-cancerous stem cell expansion and leukemogenesis.

  Study EGAS00001003288

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. One possibility for this inefficiency is an incomplete understanding of the molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to develop a foundational dataset for identifying candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Study EGAS00001003667

• Whole Exome Sequencing of a Chinese Cataract Girl

  Whole exome sequencing of a Chinese girl with congenital cataract. The dataset contains one sample with two fastq files. The novel PAX6 mutation (c.221G>A) is associated with congenital cataract, and the WFS1 mutation (c.2070_2079del) interactively aggravates this process.

  Dataset EGAD00001008267

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• A Genome Wide Scan of Lung Cancer and Smoking

  The majority of cases of lung cancer are the culmination of a dynamic process that begins with smoking initiation, proceeds through dependency and smoking persistence, continues with lung cancer development and ends with progression to disseminated disease or response to therapy and survival. We are conducting a whole genome study of lung cancer and smoking to examine critical steps in lung cancer progression. This study is a genome-wide association study (GWAS) to investigate the genetic determinants of lung cancer risk. The study design efficiently allows identification of genes that also contribute to smoking persistence and outcome from lung cancer using a single GWAS of 5,900 subjects using the primary GENEVA dataset, derived from two studies. The first is the Environment and Genetics in Lung Cancer Etiology Study (EAGLE), a population-based, biologically intensive, case-control study from the Lombardy region of Italy including ~2000 newly diagnosed lung cancer cases and ~2000 age-, gender- and region- matched controls. The second is the Prostate, Lung, Colon and Ovary Study (PLCO) Cancer Screening Trial from which we have selected ~850 lung cancer cases and ~850 controls, also matched on age and gender. Understanding the basis for the well-established hereditary component of lung cancer and smoking persistence could provide new insights into etiology, prevention, and treatment, and have an enormous impact on public health. The same GWAS genotyping data in the two studies will be used to investigate the genetic determinants of smoking persistence. Specifically, we will analyze current smokers and former smokers from EAGLE and PLCO for diverse smoking phenotypes, including persistence of smoking as well as ever/never smoking comparisons, quitting attempts, and the Fagerström index of tobacco addiction. PLCO participants are all European-Americans and EAGLE involves subjects from Italy. EAGLE is a case-control study and contains 3937 phenotyped subjects. PLCO is a screening trial with a cohort design and contains 1651 phenotyped subjects. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to lung cancer and smoking through large-scale genome-wide association studies of population-based samples of lung cancer cases and controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000093

• Germline TP53 mutations undergo copy number gain years prior to tumor diagnosis

  Li-Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome associated with germline TP53 mutations. We performed whole-genome sequence (WGS) analysis of tumors from 22 TP53 mutation carriers. We observed somatic mutations affecting Wnt, PI3K/AKT signaling, epigenetic modifiers and homologous recombination genes as well as mutational signatures associated with prior chemotherapy. We identified near-ubiquitous early loss of heterozygosity of TP53, with gain of the mutant allele. This occurred earlier in these tumors compared to tumors with somatic TP53 mutations, suggesting the timing of this mark may distinguish germline from somatic TP53 mutations. Phylogenetic trees of tumor evolution, reconstructed from bulk and multi-region WGS, revealed that LFS tumors exhibit comparatively limited heterogeneity. Overall, our study delineates early copy number gains of mutant TP53 as a characteristic mutational process in LFS tumorigenesis, likely arising very early in life or in utero.years prior to tumor diagnosis.

  Study EGAS00001005982

• POPRES: Population Reference Sample

  POPRES version 1 and 2 Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost-effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetic research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This resource was initially genotyped using the Affymetrix 500K SNP panel. This project includes nearly 6,000 subjects of African American, East Asian, South Asian, Mexican, and European origin. POPRES version 3 The discovery and development of novel drugs is challenging and with high attrition rates. Selection of the right target and optimal indications for novel therapeutics represent key decision points in this process, and are often hampered by our limited understanding of the biology of the target in humans. Building a robust body of knowledge of variation within drug target genes has in several cases increased the probability of success for novel therapeutics. Our knowledge of variation within drug target genes and their influence on traits of medical interest is still very limited. In an effort to fill this gap, we resequenced the exons of 202 known or suspected drug target genes in over 16,000 well-phenotyped individuals. A total of 863,883 bases were targeted, including 351 kb of coding and 323 kb of untranslated exon regions. The sequenced subjects included 3,381 from two studies that were part of the Population Reference Sample (POPRES) project: CoLaus (N = 2,059) and LOLIPOP (N = 1,322). Genotyping data generated through the targeted next generation sequencing is available through the dbGaP.

  Study phs000145

• Immune microenvironment and lineage tracing help deciphering Rosette-forming GlioNeuronal Tumors: a multi-omic analysis of 9 cases

  Rosette-forming GlioNeuronal Tumor (RGNT) is a rare central nervous system neoplasm containing two components, glial and neuronal. The delineation of histological diagnosis of RGNT from similar low-grade tumors such as pilocytic astrocytoma (PA) and ganglioglioma (GG) may be challenging. We performed here a comprehensive molecular analysis of a cohort of tumors with same histology features to identify molecular characteristics of RGNT. A cohort of 9 rosette-forming tumors histologically-diagnosed were analyzed at molecular level using multimodal approaches as Whole Exome Sequencing (WES), RNAseq and methylome. In our cohort, 3 tumors were plotted within the Methylation Class-RGNT (MC-RGNT) characterized by FGFR1 mutation associated with PIK3CA or NF1 mutations. Transcriptome analysis was performed in 7 cases. RNAseq identified a “Hot” and a “Cold” transcriptomic group; the latter includes the 3 MC-RGNT and 1 MC-Pilocytic Astrocytoma and exhibited a “Cold” immune tumor microenvironment in comparison with the “Hot” group. The distinct immune cell content of both groups was confirmed by quantitative immunostainings. Get Set Enrichment Analysis showed that the “Cold” group had upregulated NOTCH pathway and mainly oligodendrocyte precursor cell and neuronal phenotypes while the “Hot” group exhibited predominantly astrocytic and neural stem cell phenotypes. In silico deconvolution identified the cerebellar granule cell lineage as a putative origin and as the cell context to understand the effects of genetic alterations and NOTCH signaling. Histological diagnosis of rosette-forming tumors encompasses heterogeneous tumor entities. Our study identified distinct tumor cell contexts and microenvironments as key features to better understand and manage these neoplasms.

  Study EGAS00001006502

• DAC Portal documentation

  DAC Portal Welcome to the DAC Portal documentation! If you are involved in governance or legal aspects, technical or operational aspects, or serving as a data steward, this page will be helpful for you. By exploring these materials, you can define your own Data Access Committee (DAC) and policies, understand the minimal requirements for a DAC and a policy object, and comprehend how the EGA data access requests are managed. DAC Portal Index Setting up your account DACs and Policies Pending Request table Manage Data Requests History page Audit your DACs, policies, and datasets Deprecation User Preferences DAC API - A programmatic approach Setting up your account Register yourself as an EGA user. The Helpdesk team will validate your account (this could take up to 48 hours). After validation, you will receive an email with a link to verify your email - Make sure you click on the link to verify your account! If you don’t receive the email, please check your spam folder. Once your account is active you can login to the DAC Portal. We recommend you to check out the Take The Tour! DACs and Policies Create a DAC Click on Create a DAC Add the title and description to your DAC. Once ready, click on the ‘Create’ button. You will have to wait until the Helpdesk Team validates the creation of your DAC. Once approved by Helpdesk, your DAC will be assigned with a persistent identifier (EGAC). Edit a DAC Once your DAC is registered and approved, you can edit it and add contacts. Remember, you can add as many contacts as needed. And, you can also remove/add contacts anytime. To add a contact, you must write the username or email of a registered EGA user in the Members field. Once you have typed the whole username or email, a drop-down menu will appear where you can select the contact. Select a contact from the drop-down menu. Make sure you write the full username or email of the contact so it appears as an option. Make sure that you select one main contact. Set up the role you want to grant to the new contact of the DAC. We recommend you to check out the FAQ to learn more about the different roles! After adding all the necessary contacts and assigning roles, click on Update. This will send an email notification to the new DAC member, letting them know about the invitation to managing the DAC. Once they log into the DAC Portal, they will be able to either accept or turn down the invitation. Create a policy First, please note that all information registered in a policy metadata object will be publicly available on the EGA website. For each released dataset, all users will be able to read the policy under the “Data Access” tab. Select Create a Policy from the Policies tab. Select the DAC that you want your policy to depend on. Add the title and terms and conditions for accessing and using your data. If you already have an external website for data access requests, you can add the URL directly here (see example here). You can find a template of a Data Access Agreement (DAA) document in our Policy documentation page. The DAA template is provided for guidance only and should be adapted to suit your own purpose depending on the security policies, terms for publication or embargoes, and restrictions on data use or sharing. You can also add Data Use Ontologies (DUO) to your policy. These DUO codes are used to semantically tag the terms and conditions of using the data linked to the policy (example). For more information, you can refer to the Data Uso Ontology documentation. Once completed, make sure to click the Create button in order to register your policy. A persistent identifier (EGAP) will be assigned automatically. Edit a policy Please, note that you will not be able to edit the policy if it shows in orange. Meaning that you are a member of the DAC linked to that policy. Members don’t have edit rights. Only admins can edit objects. You can check your registered policies on My policies, available at the menu in the top-right corner. Select your policy. It will then display the information of that policy, allowing you to edit the information. Once you are done with the modifications, click Update. Pending Requests Table Table Settings Upon selecting a specific DAC, you will be presented with a customisable table showcasing all pending data access requests. This table allows you to tailor the displayed information according to your preferences by selecting desired columns. Available Columns (Displayed with the Eye Icon): Date: The date when the data access request was submitted. Full Name: Name and surname of the user submitting the request. Email: Email address associated with the user's request. Username: The username linked to the EGA account of the user submitting the request. Organisation: Affiliated organisation of the user submitting the request. Dataset: EGA accession ID for the requested EGA dataset. Dataset Title: Title of the requested dataset. DAC Comment: Space provided for internal comments related to the request. Expiration: Option to specify an expiration date for granted permissions. Check more information on the pending request table here! Table Filters By default, all data access requests are displayed. However, you have the option to apply filters to refine your view. Follow these steps to apply filters: Click on the More button. This action will reveal the different columns available for applying filters. As you select columns, the checked fields will be displayed at the top of the request table. Choose the specific values within the selected columns that you want to filter for. Click the Search button to apply the selected filters. Do you find yourself frequently applying the same filters? You can save multiple combinations of filters for easy access at any time! Here's how: Click the Save button. Provide a descriptive name for the filter combination. Click Save to confirm. To load saved filters, simply select the saved filter from the dropdown menu to apply it automatically. Check more information on filters here! Advanced Search For users requiring more granular control over their data access requests, the DAC Portal offers an Advanced Search feature using JIRA Query Language (JQL). With JQL, you can craft precise and complex queries to filter and retrieve specific data access requests based on various criteria such as date, user details, dataset attributes, and more. Using JQL's flexibility, you can create custom queries to meet your specific needs, allowing for advanced filtering options beyond the standard filters provided. You can find the Advanced Search feature following these steps: Click the … button Select Advanced To view the allowed fields for filtering and explore all available options, simply click on the info icon. Once you have written the filtering values, click the Search button to apply. Check more information on filters here! Manage Data Requests Upon logging into the DAC Portal, you'll notice a sand clock icon next to the DAC ID, indicating the number of pending requests. Click on the DAC to review these requests. Accept requests Click on the right side of the toggle button to grant access to the user. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with granting permissions. Deny requests Click on the left side of the toggle button to deny access to the user. Provide a reason for the denial. Note that the user will receive an email with this reason. Click on the Done button. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with denying permissions. Tips! Apply a filter to view all requests to be managed at once. Use the toggle in the row with column names to grant or deny permissions for multiple requests simultaneously. You can grant and deny permissions in the same action, simplifying the process. The confirmation box will provide a summary of all actions, including grants, denials, DAC comments, and expiration dates. History Page The History page serves as a dedicated space to view information regarding all requests managed by all DAC members. Here, you can review active permissions and revoke them as needed. Go to the History page by clicking on the "HISTORY" button from a DAC page in the DAC Portal. Here are the different row types you may find: Current permissions: row in green with a toggle button to revoke permissions on the right. Approved requests: row in green, with no toggle button. Request denied: row in red with “request denied” on the right. Permission revoked: row in red with “permission revoked” on the right. Distinctions to Note! Between Request Denied and Permission Revoked: Request Denied: Refers to requests that were rejected from the outset, indicating that access to the dataset was never granted. Permission Revoked: Indicates that permissions were previously granted but have since been revoked. Users with permissions revoked have previously accessed the dataset. Between Approved Request and Current Permissions: Approved Request: Represents an entry when a data access request has been approved in the past. Current Permissions: Denotes ongoing permissions where a user has present access to the dataset. An approved request may now appear as Permission Revoked in the present. By observing these different rows, users can gain insight into the complete history of a user's interactions and permissions regarding a dataset over time. To revoke access to a specific user for a dataset, follow these steps: Go to History page Look for the row with the specific permissions. You can use the filters! Click on the toggle button to revoke access. Add a denial reason. Bear in mind that the requester will receive the denial reason! Click on the Apply button. Check more information on the Hisotry page here! Audit your metadata objects In the DAC Portal, you can efficiently manage and audit various metadata objects pertinent to your role as a Data Controller. Upon accessing the DAC Portal, you will encounter three primary tabs on the homepage: DAC: Contains information about Data Access Committees (DACs). Policies: Provides insights into linked policies. Datasets: Displays datasets and relevant details. Within each tab, you'll find a comprehensive list of the objects you manage, these being grouped by type (DAC, Policies, Datasets), as well as by your role (member/admin). Whilst the lists give you a quick look, to check how things are connected, we've added a table at the bottom DACs and policies. DACs Let’s check which policies are linked to a specific DAC: Go to "My DACs." Select a DAC. Click on "EDIT" to see more details. You are now on this page: Scroll down to see the linked policies. Click on “List of linked policies of this DAC” and you will see a list of all policies linked to your selected DAC. Policies Do you want to view a list of datasets connected to a particular policy? Follow the same steps mentioned earlier, but head to the policy tab this time. In the policy tab, you'll find a list of all your policies. Here, you may notice two different icons next to the policy ID (EGAP): DAC Icon (): This represents the DAC. Hover your mouse over the icon to see the DAC ID. Dataset icon (): This indicates datasets falling under that policy. The number next to the icon tells you how many datasets are linked to the policy. For example, if you see "2" next to the icon, it means there are two datasets linked to that policy. If you want to check the linked datasets and their relevant information, simply click on a specific policy. You'll then find the "List of linked datasets of this policy" at the bottom of the page. Datasets Finally, in the dataset tab, by default you will see a list of all the datasets you can manage with all your DACs and policies. Yet, we've included two handy ways to organise them: DAC vs. policy: You can group by datasets, either by DAC or policy. Released vs. unreleased: You can sort out datasets based on their release status. Feel free to experiment with both options! For instance, if you want to see which DACs have unreleased datasets, simply select DAC and unreleased, and you'll get the details you need! Deprecation Do you have a bunch of metadata objects like DACs and policies that you don’t need anymore? This section shows you how to get rid of them! But what does "deprecation" mean for EGA? It's basically changing the status of a metadata object to "deprecated," which means we won't be using it in the future. In simple terms, it's like saying these objects are no longer useful. However, because we believe in making metadata FAIR, once an object has a persistent identifier, we can't just delete it. So, instead of deleting, we deprecate it. Here's a helpful tip! If you want to make a metadata object disappear from the DAC Portal, deprecate it. You won’t see it in the portal anymore! Let’s say you want to deprecate a DAC. Let’s do it! Go to "My DACs." Select a DAC. Click "EDIT" to see more details. You are now in this page: Click on the Deprecate button It will then appear a message. There are two options here: Your DAC is not linked to any policy, hence it’s ready to be deprecated. Click on “Yes. Confirm” to deprecate your DAC object! Your DAC is linked to at least one policy, and you need to either: Deprecate the linked policy first, or Link the policy to a different DAC Now, let’s say you don’t want to get rid of the policy altogether, but you want to change the DAC it’s linked to. Here's how: Go to the policy tab. Find the policy you want to change (for example, EGAP50000000019). Choose a new DAC to link it to. Click on Update. See the Edit Policy section for more details. After ensuring that the DAC we want to deprecate isn’t linked to any policy, return to the "My DACs" section and follow the steps outlined previously. This will lead you to a confirmation message. You can only deprecate DACs and Policies. To deprecate a dataset, please contact our Helpdesk team. Check more information on how deprecation works here! User Preferences We have implemented email notifications in the DAC Portal. Here’s the complete list: DACs: Pending requests Approved by Helpdesk Rejected by Helpdesk DAC Invitation Requesters: Data access request approved Data access request denied Permissions revoked Upcoming expiration date As a DAC member, you will be able to decide whether you want to receive the DAC notifications or not. For that, go to the top-right corner menu, select User Preference. You will be able to decide whether you want to receive notifications for: Approved by Helpdesk Rejected by Helpdesk DAC Invitation For pending requests, you will be able to select how often do you want to receive the notification: Daily Weekly Fortnightly As a DAC member, you are responsible for managing data access requests. Consequently, you will receive notifications for pending requests. If you prefer not to manage these requests, please arrange to be removed as a contact for your DAC. Here's a tip! Do you have a pending request that you don’t want to receive a notification? Add a DAC comment! 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! DAC API - A programmatic approach In addition to the new DAC Portal, we are excited to announce the release of the DAC API. This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can click the button below. Check out the DAC API specification!

  Documentation access/data-access-committee/dac-portal