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• Multiomic profiling of pleomorphic rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) describes rare soft-tissue tumors that exhibit features of skeletal muscle differentiation. The most common subtypes in children are alveolar and embryonal rhabdomyosarcoma, with the alveolar subtype characterized by PAX3/7 fusions. A lesser known and rarer subtype, pleomorphic rhabdomyosarcoma (PRMS), occurs most frequently in adults vetween the ages of 40 and 50. This pleomorphic subtype is often misdiagnosed and little is known about its molecular characterization. Here, we conducted comprehensive genomic, transcriptomic, and methylation profiling of these tumors.

  Study EGAS00001007230

• Aggressive genomic features in clinicallyindolent primary HHV8-negative effusion-based lymphoma

  Human herpesvirus 8-negative effusion-based lymphoma (HHV8-negative EBL) is a distinct lymphoma entity related to fluid overload states caused by underlying medical conditions. Due to a phenotypical resemblance with secondary effusion of diffuse large B-cell lymphoma (DLBCL), HHV8-negative EBL is easily misdiagnosed. However, in contrast to DLBCL, HHV8-negative EBL follows a mild clinical course, underpinning the importance to differentiate between the two entities. Only limited molecular data of HHV8-negative EBL has been reported and characteristic genomic patterns are lacking. We performed extensive genomic profiling on 8 HHV8-negative EBL cases. A mean number of 33.6 copy number gains and losses per case were found, with recurrent focal deletions of chromosome 3p14.2 and 6q21 in 6/8 cases, encompassing tumor supressor genes FHIT and PRDM1, respectively. We observed a high rate of mutations across genes frequently involved in DLBCL, including patterns of somatic hypermutation. The most abundant hotspot mutation was found in MYD88L265P (3/8 cases). In addition, 5/8 cases had one or more translocations, involving MYC, BCL2, BCL6, TP63, EXOC2 and KMT2D, with Ig and non-Ig partners. We conclude that HHV8-negative EBL is characterized by genomic features that are commonly found in more aggressive B-cell lymphomas, but despite this follow an indolent clinical course.

  Study EGAS00001002743

• TOPDECC-Trans-omics for Precision Dentistry and Early Childhood Caries: Genome-Wide Genotyping (CIDR) and Microbiome in the ZOE 2.0 Study

  The ZOE 2.0 study is a cross-sectional genetic epidemiologic investigation of early childhood oral health, conducted in a state-wide, community-based, multi-ethnic sample of 3-5-year-old preschool-age children in North Carolina, United States. Between 2016-2019, 8,059 children were enrolled and 6,404 of them underwent comprehensive oral-clinical examinations that provided usable data on dental caries (i.e., early childhood caries; ECC) phenotypes. Saliva samples and supragingival biofilm samples were collected by 10 trained and calibrated examiners during the clinical encounters that took place in enrolled children's preschool (Head Start) centers. Specifically, the study enrolled participants and conducted clinical examinations in 260 Head Start centers that belonged to 34 Head Start programs in NC. 6,262 participants provided clinical data and had extracted DNA that met quantity and quality criteria for high-density genotyping and 6,144 of them were retained in the genome-wide association study (GWAS). Additional information on oral health-related behaviors, risk factors and self-reported outcomes was collected prior to the conduct of the clinical exam using self-administered questionnaires completed by children's guardians. Height and weight measurements were used to derive measures of adiposity. A domestic water sample for fluoride concentration measurement was obtained after the clinical examination for approximately 25% of study participants, to provide a measure of environmental exposure to this known caries-preventive agent and this information was subsequently imputed to the entire cohort using a novel GIS-informed method. Supragingival biofilm samples for microbiome analyses were collected from all participating children. Biofilm samples from a pilot 5% (n=300) of the cohort were carried forward to WGS (metagenomics; MTG) and RNAseq (metatranscriptomics; MTX) analyses, and these sequence data are being released via the Sequence Read Archive (SRA) in this dbGaP accession: 300 participants with MTG, 297 of those with MTX. Of note, the 17 participants with MTG data did not have genotypes produced, therefore the study's released participant total count is 6161, including 6144 (with genotypes released) plus 17 (with no genotypes released but with MTG data in the SRA).The study's primary objective is to identify risk loci and gene sets/pathways for ECC and related traits (e.g., caries prevalence and severity) by conducting a trans-ethnic GWAS. Genotyping is based on the Infinium™ Global Diversity Array and the TOPMed panel is used for imputation via the University of Michigan Imputation server. Secondarily, the ZOE 2.0 seeks to determine prevalence and severity of dental caries, other oral disease outcomes, and putative risk factors for dental caries in this low-income population-based sample of European-, African-, and Hispanic/Latino-American preschool-age children.

  Study phs002232

• Bulgarian Trio Sequencing Study to Identify de Novo Mutations in Schizophrenia

  The primary aim of this study is to whole exome sequence complete Bulgarian trios to identify de novo mutations in schizophrenic probands. We are investigating the rate of de novo mutations in probands as well as looking for enrichment among previously implicated genes and synaptic gene sets.

  Study phs000687

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  Chronic myeloid leukemia (CML) is a clonal disease, initiated and sustained by a subpopulation of CML stem cells (CML-SC) containing the BCR::ABL1 oncogene. Genetic markers that enrich for CML-SC have been identified, including CD26 being most specific. Genome sequencing analysis remain yet to be performed at single cell level in order to determine differences and heterogeneity in the genetic profile of CML-SC versus normal hematopoietic stem cells (HSC). Here we show that CD26 and CD33 separate CML-SC from normal HSC in freshly isolated bone marrow samples from newly diagnosed CML patients. DNA sequencing confirms that single CML-SC derived colonies are positive for BCR::ABL1 and harbor a recurrent set of patient-specific clonal somatic mutations across different CML-SC derived colonies. In contrast, marker-negative (CD26-CD33-) HSC from the same patients are negative for the BCR::ABL1 oncogene and do not carry recurrent, clonal mutation across different colonies. These results support the concept that CD26/CD33 expression separates genetically defined, clonal mutant CML-SC from normal HSC that carry individual sets of random mutations in CML patients. We provide whole exome DNA sequencing data for 23 clinical samples of CML-SC plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed HSC at remission were selected from bone marrow samples by FACS, according to genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform. Following GATK best practices for somatic mutation calling, novel CML variants and random mutation events during remission phase were obtained.

  Study EGAS00001006904

• Distribution of data using Live Distribution

  Live Distribution Welcome to the documentation for using the Live Distribution feature for distributing data files securely through the EGA platform. This guide will walk you through the process of downloading encrypted files and decrypting them using Crypt4GH. Please follow the steps below to ensure a smooth experience. Before Downloading Create an EGA user. Make sure that you have the permissions to download the dataset of interest. In case you don’t have access, request access to the dataset. Add your Crypt4GH-compatible public key to your EGA account. Please allow a few hours for your public key to be synced with your profile. Afterwards, you will be able to connect to your EGA outbox using the SFTP protocol. Download Graphical User Interface (GUI) You can use any GUI that supports SFTP connections, such as FileZilla, an open-source FTP client. For Filezilla as your GUI, follow these steps to download files: Open FileZilla and access Site Manager (File > Site Manager). Create a new connection with the following settings (Figure 1): Protocol: SFTP - SSH File Transfer Protocol Host: __EGA_OUTBOX_DOMAIN__ Logon Type: Key file User: your EGA username Key file: path/to/your/private_key Figure 1: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using a key file as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the EGA outbox, ensuring seamless data transfers. Click Connect to access your Outbox. This folder serves as your storage space within the EGA cloud, containing files accessible for download in a secure way. Browse the remote directory on the right side of the FileZilla screen. Select the files you wish to download, right-click, and choose Download (Figure 2). Figure 2: Step-by-step process of manually downñoad files from __EGA_OUTBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can downñoad data from the EGA outbox to their local storage by following the depicted steps SFTP command line You can also use the SFTP command line to securely download files from the EGA Outbox. Using SFTP command line client in Linux/Unix Open a terminal window Enter the following command to connect: sftp username@hostname Enter your EGA password To see a list of available sftp commands type help sftp> put – Upload file sftp> get – Download file sftp> cd path – Change remote directory to ‘path’ sftp> pwd – Display remote working directory sftp> lcd path – Change the local directory to ‘path’ sftp> lpwd – Display local working directory sftp> ls – Display the contents of the remote working directory sftp> lls – Display the contents of the local working directory Type get command to download files. For example: get encrypted_file.c4gh Use the bye command to close the connection (SFTP session). Convenient SSH settings Include the following settings in your SSH config file, located in ~/.ssh/config Host __EGA_OUTBOX_DOMAIN__ EGA-outbox hostname __EGA_OUTBOX_DOMAIN__ User username IdentityFile path/to/the/private/key Replace username and path/to/the/private/key with the appropriate settings, and you will be able to connect to the __EGA_OUTBOX_DOMAIN__ simply using sftp EGA-outbox. How to decrypt Files archived at the EGA are encrypted based on Crypt4GH. Hence, to decrypt the files you need to install Crypt4GH. You can install a python implementation of it, with pip install crypt4gh or directly from the Github repository pip install git+https://github.com/EGA-archive/crypt4gh.git After installing Crypt4GH, decrypt files using the following command: crypt4gh decrypt --sk /path/private/key < encrypted_file.c4gh > decrypted_filename The command reads the encrypted file from stdin (with <) and output the decrypted version to stdout (with >). Replace encrypted_file.c4gh and decrypted_filename with the appropriate filenames but make sure to not use the same filename for both reading and writing because your SHELL would then truncate both files before you even read or write. Frequently Asked Questions What username should I use to log in to my outbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username, not your email address. Therefore, if you registered a username different from your email address when creating your EGA account, you must use that username to log in. If you have forgotten your registered username, please, contact our Helpdesk team for assistance. I see that some files in my dataset have 'unavailable' as extension. What should I do? Within your Outbox, you'll find a list of all the datasets available for download. Occasionally, certain files may be marked as "unavailable". These unavailable files can be identified by the "unavailable" extension added to their filenames (e.g. filename.fastq.gz.unavailable.c4gh). If you encounter an unavailable file that you need, please reach out to our Helpdesk. We'll promptly work on making the file accessible for download as soon as possible. Specific to using keys Can I access one EGA account from different devices? Yes, you can access your account from different devices by linking several public keys to your EGA account. Each device can generate a unique public-private key pair, and the corresponding public keys can be linked to the same account. This way, you can use different public keys on different devices and still have access to the same account and data. I have several keys and I don't remember which one is which When generating SSH keys, it's a good practice to add a comment using the -C flag. This will allow you to add a descriptive tag to your key, making it easier to identify later on. Here's an example command that generates an SSH key with a comment: ssh-keygen -t ed25519 -C work-pass In this example, we're generating an ed25519 SSH key with the comment work-pass. Once you have multiple keys with different comments, you can use the comments to easily identify each key. To view the comments for your existing SSH keys, you can use the following command: ssh-keygen -l -f /path/to/key This will display the key fingerprint and the associated comment. By checking the comments, you should be able to identify which key is which. What if I can't find my SSH keys for uploading files with a key file, and how can I use new keys? If you can't find your SSH keys, don't worry - you can make new ones. To do this, open your terminal or command prompt and type a command to make a new SSH key. You can pick a name for the key, and choose a password to keep it safe. After making the key, you can add the new key to your account or server where you want to upload files using the key file. This usually involves copying and pasting the key's "public" (e.g. file.pub) part to the right place. If you lose track of the key again, just make a new one and add it again. Keep in mind that SSH keys belong to you and your computer, so if you switch computers or accounts, you'll need to make new keys. I don't want to type the passphrase every time I use the key. What can I do? You can use an ssh-agent to avoid typing the passphrase every time you use the key. An ssh-agent is a program that stores your private keys in memory and provides them to ssh when needed. You can add your key to the ssh-agent using the command ssh-add followed by the path to your key file.Here's an example of the steps to follow: Open a terminal window.Start the ssh-agent by typing the command eval $(ssh-agent).Add your key to the ssh-agent by typing the command ssh-add [key filepath]. For instance, if your key file is located in the home directory with the name mykey, the command will look like this: ssh-add ~/mykey After adding your, key to the ssh-agent, you should be able to use ssh without having to enter your passphrase every time. Can I use my password for authentication (without my private key)? If you prefer to use your username and password for authentication instead of your private key, you can still do so. When using a Graphical User Interface (GUI) such as FileZilla, you can select Ask for password as your Logon Type (Figure 3). This option will prompt you to enter your password when you click Connect, instead of using your private key. Figure 3: This option will prompt you to enter your password when you click "Connect", instead of using your private key. Figure 3: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using your password as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers. It's worth noting that using a password for authentication can be less secure than using an SSH key, as passwords can be more easily compromised through various means. However, if you choose to use your password for authentication, selecting "Ask for password" as your Logon Type is a good way to do so securely via a GUI. Why is it better to use my key and not my password? SSH keys for authentication is generally considered to be more secure and convenient than using passwords. SSH keys are more difficult to crack than passwords, and they can be restricted to specific users and machines, giving you more control over access. Once you set up your SSH keys, you can use them to authenticate quickly and easily, without having to enter a password every time. This makes automation of tasks, such as uploading encrypted files, much simpler. Additionally, SSH keys provide better logging, allowing you to keep track of who is accessing your systems and when. All in all, using SSH keys is a good practice for improving security and convenience in your authentication process.

  Documentation access/download/files/live-outbox

• Anaplastic Meningioma WGS-X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Dataset EGAD00001001267

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• Base Editing Reduces Misfolded Protein Accumulation and Toxicity in Alpha-1 Antitrypsin Deficient Patient iPSC-Hepatocytes

  This study evaluates the efficiency and biological consequences of base editing of the single base &#8220;Z&#8221; mutation in the SERIPNA1 gene responsible for causing misfolding of the alpha-1 antitrypsin protein that leads to the clinical disease &#8220;alpha-1 antitrypsin deficiency". Samples on which the editing is performed are patient-derived iPSCs from a single PiZZ patient. The iPSC line is named &#8220;PiZZ-1&#8221;. To evaluate possible off-target editing, 5 samples underwent whole genome sequencing. These samples include: 1) PiZZ-1 patient iPSCs at passage 34 (&#8220;ZZ p34&#8221;); 2) PiZZ-1 patient iPSCs at passage 42 (&#8220;ZZ p42&#8221;); 3) PiZZ-1 patient iPSCs that underwent nucleofection but not base editing at passage 34, and then were passaged until passage 42 (&#8220;ZZ nucleofected&#8221;); 4) PiZZ-1 patient iPSCs that underwent base editing of a single allele (&#8220;MZ&#8221;), and analyzed at passage 42; and 5) PiZZ-1 patient iPSCs that underwent base editing of both alleles (&#8220;MM&#8221;), and analyzed at passage 42.

  Study phs002471

• Genomic Analysis of Fibrolamellar Hepatocellular Carcinoma

  Fibrolamellar hepatocellular carcinoma (FL-HCC) is a very rare and distinct subtype of hepatocellular carcinoma that occurs in the previously healthy livers of adolescents and young adults. The low incidence rate has kept FL-HCC an understudied cancer, thus the list of FL-HCC markers is limited and the genetic alterations driving its growth have remained unknown. In order to gain a better understanding of the molecular mechanisms underlying FL-HCC initiation and progression, we performed an in-depth genomic analyses of one tumor followed by immunohistochemistry validation on seven other tumors. We showed the expression of neuroendocrine markers in FL-HCC. In addition, DNA/RNA sequencing revealed that common cancer pathways are not visibly altered in FL-HCC but identified two novel structural variants, both resulting in fusion transcripts. Through in vitro studies, we demonstrated the oncogenic properties of these fusion transcripts. These experiments further highlight the tumorigenic role of gene fusions in the etiology of pediatric solid tumors and identify both candidate biomarkers and possible therapeutic targets for this lethal pediatric disease.

  Study phs000828