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• Relevance of TMPRSS2, CD163/CD206 and CD33 in clinical severity stratification of COVID-19

  Our main objective is to incorporate new markers to classify COVID-19 patients based on mild or severe disease progression. To achieve this, we characterize SNP genotypes in critical genes involved in SARS-CoV infection (ACE2 (rs2285666), MX1 (rs469390), and TMPRSS2 (rs2070788) variants) and study the monocyte population by mass cytometry (CyTOF). Finally, the results obtained will be integrated to search for the best set of predictors of disease aggressiveness.

  Study EGAS00001007003

• Genotyping_of_additional_Inflammatory_Bowel_Disease_cases___2014

  Both internal and external funding has enabled 5000 inflammatory bowel disease cases to be whole genome sequenced (CD @4X, UC @2X). The Anderson and Barrett groups are currently generating genotypes across these samples for comparison to 4000 population controls sequenced as part of UK10K. The UK10K project has shown that imputing sequenced genetic variation into previously GWASed samples greatly increases power to detect association. Given that our study has been designed to detect association to low frequency variation (0.5% and above) these gains in power are especially important. Overall, the UKIBDGC has GWAS data for around 1800 CD samples (Affy 500K) and 3000 UC samples (Affy6), though some of these samples have also been whole genome sequenced. Here, we apply to get all remaining non-GWAS and non-WGS IBD cases in the UKIBDGC (N=X) genotyped genotyped on the Illumina Core Exome Array

  Study EGAS00001000924

• Genome-wide genotyping and methylation data from Understanding Society

  Genome-wide genotyping and methylation data from Understanding Society. Please visit https://www.understandingsociety.ac.uk/ for further information.

  Study EGAS00001008417

• High-depth whole genome sequencing of 26 premalignant breast lesions

  Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer, representing 20-25% of newly diagnosed breast cancer lesions. It is currently not possible to predict which DCIS patients will progress to invasive breast cancer. The samples deposited here are part of a larger study using high-depth whole-genome sequencing (WGS) to investigate the somatic mutation genomic landscape of DCIS. Comprehensive evaluation of DCIS genomes aims to uncover biological insights into breast cancer progression and potential opportunities to stratify DCIS patients for personalised treatment options or active surveillance. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.

  Study EGAS50000001559

• Discovery and Characterization of Genetic Risk Loci in Sjogren's Syndrome

  The Sjögren's Genetics Network (SGENE) is an international collaboration focused on identifying and understanding the genetic variations that influence Sjögren’s pathology. Collectively, SGENE collaborators from 26 different sites (5 in the United States; 21 in foreign countries) have recruited a large cohort of geographically diverse participants of European ancestry. Recruitment, sample collection, and genotyping were performed at unique SGENE sites in compliance with local institutional review board approval. High-density SNP genotyping data were collated by the Oklahoma Medical Research Foundation (OMRF) and used to perform a GWAS of Sjögren's of European ancestry. Participants underwent extensive medical assessment for Sjögren's Syndrome using internationally accepted American-European Consensus Group (AECG) classification criteria or the American College of Rheumatology/European League Against Rheumatism classification criteria. Data quality control, GWAS imputation using the Haplotype Reference Consortium, panel version 1.1, and dbGaP preparation/posting were performed at the OMRF. To facilitate research focused on understanding the genetics of Sjögren's syndrome, the Genomic Summary Results from this GWAS are being made available herein using a total of n=3232 Sjögren's cases and n=17,481 controls. A total of n=8962 controls were obtained from our SGENE collaborators or from our previous study (Lessard, et al. Nature Genetics 2013. PMID: 24097067). To achieve adequate case-to-control ratios for the GWAS analyses, population-based control GWAS data were also obtained from dbGaP (phs000428.v2.p2; phs000672.v1.p1; phs000196.v3.p1; phs000187.v1.p1). In accordance with IRB approval, subject consents, and data sharing restrictions, we are also making available the individual-level genotyping data for a subset of Sjögren's cases (n=1,199) that were genotyped at the OMRF.

  Study phs002723

• Genetic Aberrations and Subclonal Structure Impact Chronic Lymphocytic Leukemia

  Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enable the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome.Additionally, we performed RNA-seq for 268 CLL samples (including 26 follow-up samples) and used them to identify expression subtypes of CLL. RRBS for 30 of these samples was also generated. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs000922

• IMCISION DNAseq

  Standard-of-care (SOC) surgery for locoregionally advanced head and neck squamous cell carcinoma (HNSCC) is intensive and results in 30‒50% five-year overall survival. Anti-PD1 immune checkpoint blockade (ICB) durably improves survival rates in recurrent/metastatic HNSCC. We report on the non-randomized phase Ib/IIa IMCISION trial (NCT03003637) of 32 HNSCC patients treated with two doses neoadjuvant nivolumab (NIVO MONO, n=6, phase Ib arm A) or two doses of nivolumab plus a single dose of ipilimumab (COMBO, n=26, 6 in phase Ib arm B and 20 in phase IIa) prior to surgery and, if indicated, adjuvant radiotherapy. Neoadjuvant ICB was feasible in all phase Ib patients, meeting the phase Ib primary feasibility endpoint. One phase IIa patient had progressive disease precluding surgery. Primary tumor pathological response (phase IIa primary endpoint), defined as the % change in viable tumor cells from baseline biopsy to on-treatment resection, was evaluable in 29 patients. . We observed a major pathological response (MPR, 90‒100% response) in 8/23 (35%) evaluable COMBO and 1/6 (17%) NIVO MONO patients. None of the patients with MPR after NIVO MONO or COMBO developed a tumor relapse after 24.0 months median follow-up. FDG-PET-based total lesion glycolysis identified MPR patients prior to surgery. A baseline AID/APOBEC-associated mutational profile and an on-treatment decrease in hypoxia signature expression were observed in MPR patients. Our data indicate that neoadjuvant NIVO MONO and COMBO are safe in HNSCC, and that particularly COMBO ICB shows encouraging effectivity. IMCISION provides rationales for future HNSCC trials aiming to pre-operatively select patients with a likely MPR after neoadjuvant ICB for de-escalation of SOC.

  Study EGAS00001005466

• DNA methylation database for gynecological cancer detection, classification and assay development

  DNA methylation changes are associated with cancer the best predictor of the presence of cancer. In order to detect and classify gynecological cancer, we performed MeD-seq to generate DNA methylation profiles of vulvar, cervical, endometrial, fallopian tube and ovarian cancers and their associated healthy tissues. DNA methylation profiles were used to find general cancer, regional cancer and specific cancer biomarkers that can be used for cancer detection, classification and treatment monitoring.

  Study EGAS50000000417

• Tools

  EGA Tools This page provides details of the applications available at the EGA. Submission Tool Description EgaCryptor Encrypt and create md5sum values. Crypt4gh Encrypt, decrypt or re-encrypt files. INBOX Upload your files once encrypted. FTP Upload your files once encrypted. Submitter Portal Submit and manage your submission metadata online (SEQUENCING AND PHENOTYPE ONLY) Submitter Portal API Submit and manage your submission metadata programmatically. Webin Submit and manage your submission metadata online (array data) Webin API Submit metadata using XML files. Aimed to array-based submissions. Star2xml Format conversion tool to transform tabular formats (e.g. spreadsheets) into EGA's XMLs. Used for large programmatic submissions. Data Access Tool Description DAC Portal Manage and control data access request. Download Tool Description PyEGA3 Download and decrypt datasets requested through your EGA web account. Live Outbox Download and decrypt datasets requested through your EGA web account. Fuse Client A quick and convenient way to browse through EGA files without the need for complete downloads. EGA QuickView A quick and convenient way to browse through EGA files without the need for complete downloads.

  Documentation tools

• TARGET Trial Study Cohort

  In a randomized controlled clinical trial, investigators will compare the effects on [18F]-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT) from two treatment regimens in rheumatoid arthritis (RA) patients deemed methotrexate inadequate responders (MTX-IRs). Two common RA treatments will be compared: triple therapy (sulfasalazine, methotrexate, and hydroxychloroquine) versus tumor necrosis factor (TNF) inhibitor (etanercept or adalimumab, plus background methotrexate for all subjects and hydroxychloroquine for subjects who were taking this at screening). Consenting subjects will be screened for eligibility and randomized to a treatment arm. Subjects will be randomized to a treatment arm with either synthetic disease-modifying antirheumatic drugs (DMARDs) [triple therapy: sulfasalazine, methotrexate, and hydroxychloroquine] or biologic DMARDs [etanercept or adalimumab, plus background methotrexate for all subjects and hydroxychloroquine for subjects who were taking this at screening]. Once randomized, a baseline visit will be conducted with each subject. Baseline data collection includes questionnaires, disease activity score, and the first FDG-PET/CT imaging. After the baseline at week 0, subjects will visit with their rheumatologist at weeks 6, 12, 18, and 24 for safety labs and further collection of disease activity scores and questionnaires. The second FDG-PET/CT will be performed at week 24. Blood specimens will be collected at weeks 0, 6, 18, and 24 for bioassays. Subject participation will end after the week 24 visit. Patients and care providers will be unblinded. The FDG-PET/CT image readers will be blinded to treatment arm as well as timepoint of image acquisition.

  Study phs003720

• Coeliac Disease Immunochip dataset

  Illumina Immunochip genotype data for coeliac disease and control samples. Data is in PLINK binary format. Calling algorithm for genotypes is based on GenomeStudio (GenTrain), with manual clustering of selected variants (please see published manuscript). Genotypes called in this way may not be exactly identical to those generated by other algorithms - this is particularly relevant for groups wishing to utilise the control data (e.g. 1958 Birth Cohort). Please contact the investigators if you wish to discuss access to other data formats (e.g. .idat).

  Study EGAS00000000053

• Genome-wide search for higher order epistasis as modifiers of treatment effects on bone mineral density in childhood cancer survivors

  Survivors of pediatric acute lymphoblastic leukemia (ALL) exposed to curative treatments that adversely affect BMD (age- and sex-adjusted BMD Z-scores, measured via QCT). Specifically, after SNP QC and annotation, we considered 75523 autosomal SNPs mapped to putative promoter or enhancer regions to restrict our search to 3-way SNP interactions that potentially reflect gene regulation events that influence BMD. We replicated 3-SNP interactions as modifiers of treatment effects in a cohort of adult survivors of non-ALL pediatric cancers (N=1428).

  Study EGAS00001002645

• Target sequencing of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in Japanese renal cell carcinoma patients

  Identifying causative genes via genetic testing is useful for the screening, prevention, and treatment of cancer. Several hereditary syndromes are known to occur in renal cell carcinoma (RCC). However, these evidences came from the European population; it remains unclear how the RCC-related genes and other cancer-predisposing genes contribute to the development RCC in the Japanese population. A case-control study of 14 RCC-related genes and 26 cancer-predisposing genes was performed using 1,563 Japanese patients with RCC and 6,016 controls. Patients were divided into two major histological subtypes of clear cell RCC (ccRCC) or non-clear cell RCC (nccRCC). Gene-based analysis of germline pathogenic variants in patients with each subtype and cancer-free subjects was performed. Following quality control, 1,532 patients with RCC and 5,996 controls were further analyzed. For ccRCC, 52 of 1,283 (4.05%) patients carried pathogenic variants mainly in the cancer-predisposing genes such as TP53 (P = 1.73 �� 10-4; OR, 5.8; 95% CI, 2.2���15.7). Approximately 80% of patients with pathogenic variants in TP53 had p.Ala189Val that was specific in East Asian population. For nccRCC, 14 of 249 (5.62%) patients carried pathogenic variants mainly in the RCC-related genes such as BAP1 (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf), and FH (P = 6.27 �� 10-5; OR, Inf; 95% CI, 10.0���Inf). Our study showed different and population-specific contributions of risk genes between ccRCC and nccRCC in Japanese for better-personalized medicine.

  Study JGAS000414

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.

  Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dac EGAC50000000169

• Neoadjuvant combination PD-L1 plus CTLA-4 blockade in patients with cisplatin-ineligible operable urothelial carcinoma

  Immune checkpoint therapy (ICT) is being tested in the neoadjuvant setting for patients with localized urothelial carcinoma (UC), with one study reporting data in cisplatin-ineligible patients who received anti PD-L1 monotherapy. The study reported that patients with bulky tumors, a known high-risk feature defined as greater than clinical T2 disease, had fewer responses, with pathologic complete response (pCR) rate of 17%. Here, we report on the first pilot combination neoadjuvant trial (NCT02812420) with anti-PD-L1 (durvalumab) plus anti-CTLA-4 (tremelimumab) in cisplatin-ineligible patients, with all tumors identified as having high risk features (N=28). Primary endpoint was safety and we observed 6 of 28 patients (21%) with grade ≥3 immune-related adverse events, consisting of asymptomatic laboratory abnormalities (N=4), hepatitis and colitis (N=2). We also observed pCR of 37.5% and downstaging to pT1 or less in 58% of patients who completed surgery (N=24). In summary, we provide initial safety, efficacy and biomarker data with neoadjuvant combination anti-PD-L1 plus anti-CTLA-4, which warrants further development for patients with localized UC, especially cisplatin-ineligible patients with high-risk features who do not currently have an established standard-of-care neoadjuvant treatment. Publication: Gao et al. Neoadjuvant PD-L1 plus CTLA-4 blockade in patients with cisplatin-ineligible operable high-risk urothelial carcinoma. Nature Medicine volume 26, pages1845–1851(2020)

  Study EGAS00001004074

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• Single-cell targeted DNA-sequencing and protein sequencing

  We performed single-cell targeted DNA sequencing (MissionBio) on 13 high hyperdiploid B-ALL patients at diagnosis to study the genetic heterogeneity. For a number of patients single-cell surface protein antibody sequencing was added (DAB-seq) to better characterize the different cell types. Furthermore, additional samples during treatment were collected and analysed for some patients. In this way we want to study the clonal heterogeneity of these B-ALL samples, based both on mutations and CNVs, and identify resistant clones that could be targeted after relapse.

  Study EGAS50000000580

• Single-cell RNA and ATAC sequencing data analysis of human postmenopausal fallopian tube and ovary

  In this study, we used a combination of technologies, including Drop-seq, 10X single-cell RNA-seq (scRNA-seq), and single-cell assay on transposase accessible chromatin (scATAC-seq) to generate  a high-quality cell atlas that consists of four tissue sites from the reproductive tract of postmenopausal women. This atlas, by far the most comprehensive map of the postmenopausal female reproductive system to date, will pave the way to a better understanding of the pathophysiology of many diseases affecting older women.

  Study EGAS00001006780

• 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

• Genomic platform specific polygenic risk scores impact breast cancer risk stratification

  Background: At present, there is no consensus on which genotyping platform should serve as the standard for clinical polygenic risk score (PRS) implementation. Previous studies have compared the overall performance and concordance of different genotyping and sequencing technologies; however, these analyses have generally averaged the results over the whole genome. We evaluated differences in a 313-variant breast cancer PRS (PRS313) across genomic platforms and their impact on risk stratification. Methods: We compare PRS313 derived from genotyping arrays (Global Screening Array [GSA], OncoArray-500K [OncoArray], Global Diversity Array [GDA], custom Axiom_PrecipV1 array [ThermoFisher]) and low-coverage genome sequencing (lc-WGS) in 2 cell lines and 92 individuals. Probes are designed for all variants on ThermoFisher (success rate: 259/313). Sanger sequencing profiles indels. Concordance of high-risk classification (PRS313scoresum > 0.6) across platforms is assessed using Kappa statistics. Results: In saliva samples, indel concordance with Sanger sequencing varies widely (Kappa: 0.007-1.000). PRS313-ThermoFisher is predictable from other platforms using linear models, despite systematic differences. Greater agreement is observed between arrays with high imputation overlap (e.g., GDA ~ GSA slope=0.986). Agreement in high-risk classification before mean correction is moderate (Fleiss's Kappa=0.552) and improves after mean correction (Kappa=0.650). Arrays with similar designs show higher agreement before mean correction (Kappa=0.745). Mean correction narrows high-risk proportions from 4-45% to 15-21%. Overall, 26 of 92 samples are classified as high risk on at least one platform, but only 7 are high risk across all. When restricting to identical variants across all platforms for PRS313 calculation, the corresponding number of high-risk individuals are 24 and 11. Conclusion: Our findings demonstrate that platform-specific variability can influence PRS313 estimates to potentially reclassify individuals around clinically relevant thresholds.

  Study EGAS00001008439

• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES)

  The T2D-GENES/GoT2D 13K exome sequencing study includes ~13,000 samples, half T2D cases and half T2D controls, from five ancestries (~5K Europeans, ~2K each of African-American, East-Asian, South-Asian, and Hispanic). Samples underwent deep exome sequencing, with SNVs and INDEls called according to GATK best practices; variant sites were then filtered according to the GATK best practices, and then samples and variants underwent further filtering based on aggregate genotype quality as described in Fuchsberger et al. (e.g. low call rate, excess heterozygosity for samples, low call rate or coverage for variants). Please note that one of the samples in the T2D-GENES vcf does not have phenotype data.

  Dataset EGAD00001002246

• Research in Adaptive Interests, Skills, and Environment

  The Research on Adaptive Interest, Skills, and Environments (RAISE) project is a coordinated set of pilot studies funded and otherwise supported by the Center for the Study of Adolescent Risk and Resilience (C-StARR) at Duke University. The initial data collection effort (Adolescent T1; 2015; NAHDAP 100737) was conducted by telephone and focused on self-regulation and related skills during early adolescence and their role in early instances of health risk behavior. The survey was comprised of brief measures of constructs in six areas of interest to C-StARR investigators: (1) background and home environment; (2) self-regulation and personality; (3) physical and mental health; (4) problem behaviors; (5) academics and school; and (6) technology use. The representative sample of 2104 adolescents was drawn from the population of fifth through eighth graders enrolled in North Carolina public schools during the 2014-2015 school year.In 2016, a subsample of 395 participants from the Adolescent T1 survey (selected on the basis of having resided within 100 miles of study personnel hubs in Durham, North Carolina and Sylva, North Carolina) participated in an additional home visit study that involved the collection of biological data and measures of cognitive ability and executive functioning. The molecular data made available to dbGaP were obtained from saliva samples that were collected (a) in person from 377 of 395 home visit study participants and (b) by mail from 60 participants who had participated in the Adolescent T1 survey but had not participated in the home visit study. The resulting data file was imputed to a 1000G phase 3 panel and is comprised of N = 437 individuals and 7,193,135 markers after filtering. Data were filtered with MAF ≥ 0.01, HWE p-value > 10-6, and genotype rate > 95%.

  Study phs003982

• Dataset for liposarcoma-RNA

  Rare cancer sequencing data of 40 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008854

• Quick Guide for data submission

  Quick Guide This is a quick guide to submit data to the EGA. Please select data type to display the right detailed instructions. Sequence data Array-based data Get your submission account You first need to create your EGA user. Then, once your account has been verified by the Help Desk team, request your submission account and provide details of the data type and platform(s) in your submission. Register Study/DAC Use Submitter Portal to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the and upload it to your inbox using SFTP. Register experiments and runs Associate each data file to a registered sample and study by Linking files to samples. Details of the experimental procedure you followed must be provided. Finalise your submission Group your runs/analysis into datasets and link them to your new or existing DAC and policy using DAC Portal. Data request are done at a dataset level, thus files within a datasets must share release conditions. Release and admin When finalising the submission, set a released date to instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released. Get your submission account Fill the submission form and provide details of the data type and platform(s) in your submission. Register Study/DAC Use EGA Programmatic submission to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the EgaCryptor and upload it using default FTP clients or Aspera. Complete the Array-Format (AF) spreadsheet Download the AF spreadsheet and complete all four sections. Return the spreadsheet to the EGA helpdesk. Release and admin Instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released.

  Documentation submission/quickguide