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• Submitting array based metadata

  Submitting array based metadata For further information please check our Submission FAQs, submission quickguide as well as submission terms! The submission metadata required for Array-based submission must be submitted using EGA programmatic submission and by completing the Array-based format (AF) template. The guidelines for this workflow are described on this page. Please notice that all files should be encrypted and uploaded prior to the processing of your EGA Array-based-Format (AF) template. 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. Please notice that all files should be encrypted and uploaded prior to the processing of your EGA-Array-based-Format (AF) template. Metadata Model Registering Metadata Use the EGA programmatic submission to register your Study, Samples, Data Access Committee (DAC) and Policy. This online interface enables you to create new and edit existing submissions. Do not use the Submitter Portal to register the metadata objects for array submissions. Please, go to the EGA programmatic submission. Registering Study Go to the EGA programmatic submission Submit an study XML Take a note of your study accession number (EGASXXXXXXXXXXX) To use the study accession number in a publication, 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 "The European Genome-phenome Archive of human data consented for biomedical research"(https://doi.org/10.1093/nar/gkab1059 ). Registering Samples Go to the EGA programmatic submission Submit a sample XML Save the list of accession numbers. These will be needed for the AF template. Registering Data Access Committee Further information on the role of your DAC. Go to the EGA programmatic submission Submit a DAC XML Take a note of the DAC accession number (EGACXXXXXXXXXXX) Registering 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 (DAA) Go to the EGA programmatic submission Submit a Policy XML Take a note of the Policy accession number (EGAPXXXXXXXXXXX) Complete the Array-based format (AF) spreadsheet Once you have completed the registration of your Study, DAC and Policy using the programmatix submission, you must then complete and return the AF spreadsheet The AF spreadsheet consists on four components: Do not use EGA IDs registered using the Submitter Portal. You can easily identify objects registered in the Submitter Portal by their EGA ID pattern: EGA[A-Z]5{10 more digits} (e.g. for a sample EGAN50000002506). For populating an AF spreadsheet, please exclusively use EGA IDs following this specific pattern: EGA[A-Z]0{10 more digits} (e.g. for a sample EGAN00001691542). Tab1) Webin accessions : Provide the accession numbers for your study, DAC and policy. Please, also add your ega-box number. Tab2) Sample & phenotypes: Please, leave this tab blank. Tab3) Dataset: Describe the dataset to be created Tab4) Data files: Define how your data is going to be organised into datasets and packets for distribution (linkage between samples and files). Should further assistance be required after going through the guide below; please do not hesitate to contact the EGA helpdesk Once the AF spreadsheet is populated, please send it to our EGA helpdesk for further validation. AF spreadsheet Should your submission require multiple DAC's or policies, use ' ; ' to separate the accession numbers. Accessions AF spreadsheet: Samples & phenotypes Samples and phenotypes AF spreadsheet: Datasets We suggest that each dataset consists of a common set of data. The example below consists of two datasets, grouped according to shared data type, technology and by case/control. We also like to capture the number of unique samples that make up the dataset and the Data Access Committee (DAC) responsible for providing the named dataset and their policy (EGAP). Datasets AF spreadsheet: Data files What follows is an example of how to map your samples to the array based files added to your upload account (4th tab). Data Files Please, find below some practical examples on how to register the linkage between samples-files Case 1) 1 sample or list of samples in different datasets: Data Files In case you have a list of samples that belong to different datasets, please, repeat the samples accession number/s in the first column and link the sample to the corresponding dataset each time (each row). Each row is one linkage between sample-file-dataset. Case 2) 1 sample links to several files: Data Files In order to add multiple files to one sample you MUST use “ ; “ between filenames. Example: file1.gpg;file2.gpg;file3.gpg In case that you want to add an extra file to the sample (phenotype or .Rdata), please use “Additional files” column. Important note: You MUST upload the encrypted and unencrypted md5sum values of all files uploaded to your submission account using the filename nomenclature (file.gpg, file.md5,file.md5.gpg). Your submission will not be processed without md5values supplied for all files in the CORRECT format. What happens after the submission of a dataset? All datasets affiliated to unreleased studies are automatically placed on hold until the authorised submitted or DAC contact instructs our EGA helpdesk for the study to be released. Finally, your data is archived within our databases and prepared for encrypted distribution upon the request of permitted EGA account holders. We strongly advise you NOT to delete your data until we confirm that your data has been successfully archived.

  Documentation submission/metadata/submission/array

• Powerful Identification of Cis-regulatory SNPs in Human Primary Monocytes Using Allele-Specific Gene Expression

  The aim of this study was to compare the power to detect associations between SNPs using cis-eQTL mapping and ASE analysis (allele specific expression).

  Study EGAS00000000119

• Exome sequencing of patients with Ewings sarcoma

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing,s sarcoma tumours.

  Dataset EGAD00001000333

• SNP_array

  33 ETMR samples were genotyped using Illumina HumanOmni2.5M array. Hybridization and scanning was done according to the manufacturer's instructions (Illumina). Copy number (Log R) and B allele frequency estimates were obtained sing the Genotyping module (v1.9.4) in GenomeStudio v2011.1 (Illumina). Normalized and log2-transformed copy number measurements were imported from genomestudio and analysed using R package CopyNumber to identify segments with similar copy number.

  Dataset EGAD00010001667

• Colorectal cancer GWAS on the Spanish population

  Data on Affymetrix 6.0 arrays for Genome-Wide Association Study of colorectal cancer in the Spanish population. Additionally, geographical origin for each sample is provided, which constitutes the largest to-date Spanish genomic sample population

  Dataset EGAD00010001715

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas for the study and all the datasets.

  This dataset contains PAIR files and processed somatic copy number alteration value for array CGH of stage I lung adenocarcinomas from Asian patients. In total, there are 111 patients and 222 samples, including 111 tumor samples and 111 adjacent normal samples.

  Dataset EGAD00010001902

• methylation_bc_cervix

  Raw methylation data from cervical samples in individuals with breast cancer.

  Dataset EGAD00010002081

• NSCCG_CRC_GWAS

  Genotype data of 7,281 individuals with colorectal cancer from the National Study of Colorectal Cancer Genetics (NSCCG) study. Individuals genotyped on the Illumina OncoArray. Data provided in plink format and has not been quality controlled. Control samples used were obtained from the PRACTICAL and BCAC consortia, and are available through the respective Data Access Coordination Committees (http://practical.icr.ac.uk and http://bcac.ccge.medschl.cam.ac.uk/)

  Dataset EGAD00010002184

• Single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with achalasia

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peripheral blood mononuclear cells (PBMC) from patients with achalasia. Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000250

• AmsterdamUMC Data Access Committee for the study entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype"

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data presented in the manuscript entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype" as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000178