20311 results for "Fc coins Buyfc26coins.com is EA Sports official for FC 26 coins They are efficient and quick always..Z2Xg"

in 20.99 milliseconds.

• Genome Diversity in Africa Project: Uganda (2021-02-17)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics . This dataset contains all the data available for this study on 2021-02-17.

  Dataset EGAD00001006976

• Gabriella Miller Kids First Pediatric Research Program in Pediatric T-Cell Acute Lymphoblastic Leukemia

  The outcome for patients with relapsed T-ALL is dismal with 3-year event free survival of AALL0434 was a Children's Oncology Group-initiated phase 3 randomized clinical trial comparing Capizzi-style escalating methotrexate plus pegaspargase (CMTX) vs. high dose methotrexate (HDMTX), with/without six 5-day courses of nelarabine. Survival on this study was superior to any prior trial for de novo T-ALL, changing the standard of care. Yet, a substantial minority (~15%) of patients had relapsed or refractory (r/r) disease. Through the TARGET initiative, RNA sequencing (RNA-Seq), DNA copy number analysis, and whole-exome sequencing (WES) were performed on 264 T-ALL patients treated on AALL0434, demonstrating recurrent alterations could be grouped into 10 different potentially targetable functional pathways. This analysis was not powered to examine associations between genetic lesions with outcome, because too few patients with r/r disease were included. This project is dedicated to testing the hypothesis that comprehensive genomic profiling of the entire AALL0434 cohort will identify recurrent genetic alterations that can be segregated into biologically relevant deregulated pathways that can be combined with MRD to identify patients at risk for poor outcomes before they relapse and provide rationale for treatment with alternative therapies. In addition, a number of small recent studies demonstrated that many of the biologically relevant alterations in T-ALL occur in non-coding regions of the genome, but no large studies have performed whole genome sequencing (WGS) in T-ALL. This project also tests the hypothesis that WGS of a large cohort of patients with T-ALL will identify novel lesions in coding and non-coding regions that will be highly impactful in the understanding of T-ALL pathogenesis.These hypotheses are tested by performing comprehensive genomic profiling (WGS, WES, RNA-Seq, and copy number analysis) of the entire AALL0434 cohort with available samples with the following specific aims: (1) identify recurrent genetic alterations that predict poor outcome in T-ALL; (2) identify novel alterations, including non-coding alterations in T-ALL; and (3) identify germline genetic variants that predispose to T-ALL and to increased toxicity to chemotherapy.

  Study phs002276

• Genetic Determinants of Viral Clearance in HCV-Infected Populations

  The World Health Organization estimates there are 170 million persons with HCV infection worldwide, and an estimated 4 million persons are infected in the United States. Persistent HCV infection can cause cirrhosis and hepatocellular cancer. Long term disease consequences do not occur in persons who spontaneously recover. It is not known why 10-40% recover from hepatitis C (and are not at increased risk of cirrhosis and cancer), but that knowledge would contribute to efforts to treat and/or prevent HCV infection. The overall purpose of this study is to investigate the host genetic basis for recovery from hepatitis C virus (HCV) infection. There is strong evidence that host genetic differences determine HCV recovery. After accidental exposure to the same HCV inoculum, some persons recover while others develop persistent infection. Recovery from HCV infection is an outstanding phenotype for genetic studies since both viral exposure and viral recovery can be ascertained with high sensitivity and specificity and since there are no known viral or environmental determinants. The study group is comprised of an ethnically and geographically diverse international population. All cohorts comprising this study group of 3350 individuals are well characterized. This case-control study is comprised of approximately 40% clearance individuals who are matched by age and HIV status within their respective cohorts at a ratio of 1:1 or 1:2 with HCV chronically infected individuals.

  Study phs000248

• Nala GSI GSAv3 PGx Study

  Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100 % phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

  Study EGAS00001007710

• Dataset for transcriptome sequencing of forebrain organoids from Lissencephaly patients

  This dataset contains transcriptome sequencing for 16 samples of forebrain organoids from Lissencephaly patients. The sequencing was performed on Illumina NextSeq 6000 . The sequencing was always paired.

  Dataset EGAD00001015688

• Out with the Java, in with the Python - new EGA data download client unveiled

  We will shortly be deprecating the Java-based download client also known as API V2. The Java client began its life at the back end of 2014, and during its time has seen many developments that have served our users well. During its tenure, the Java client enabled distribution of over 6.5 million files totalling nearly 15 petabytes of data to researchers around the globe. Recent increases in genomic and phenotypic data file sizes, the number of datasets archived in the EGA, the number of users downloading data, and the diversity of download locations has meant that at times the Java client struggled to distribute data efficiently. In response, our team of developers have built a new download client with more robust features and better functionality and reliability. Enter stage left our shiny new API V3.1! The new API V3.1 will replace both API V2 and API V3. The download client for the new API V3.1 is written in Python, and the code is openly available on Github. This Python client makes https calls to the EGA AAI (https://ega.ebi.ac.uk:8443/) and to the EGA Data API (https://ega.ebi.ac.uk:8052), both of which must be accessible from the client location. In addition to general updates to improve performance, the API V3.1 has three new features enhancing the EGA distributions services. First, requested data are now downloaded over secure https connections rather than http, meaning that data can be delivered unencrypted. Instead of separately requesting, downloading, and decrypting data using the Java client, data can now be requested and downloaded using a single command without the need for decrypting. The API V3.1 also automatically verifies each file’s unencrypted md5 after download to ensure the file has downloaded correctly. Second, the new API supports segmenting and automatic resuming. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the new resume feature, downloads - both segmented and continuous stream - will automatically resume if they encounter any errors or the connection is interrupted. These features result in both a faster and more reliable download experience. Finally, the new API V3.1 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file saving both time and storage space. The new features of the Python-based API V3.1 represent significant improvements in security, speed, reliability, and flexibility that are sure to provide a better data download experience. To take full advantage of these features, users must update to Python 3.X. Considering the changes in the data structures with the new API, the upgrade to a new version of the Python client is also mandatory. Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 -U We are excited for users to try out the new features and take advantage of the multifariously growing EGA distribution services for human biomedical omics data. If you have any questions or feedback, please email the EGA Helpdesk team. We'd love to hear from you!

  Blog new-ega-data-download-client

• ICARUS-LUNG01 dataset

  A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

  Dataset EGAD50000001014

• Neuropsychiatric Genetics of African Populations - Psychosis (NeuroGAP-Psychosis)

  The NeuroGAP-Psychosis study was conducted in South Africa, Kenya, Uganda and Ethiopia as a response to the lack of genetic diversity in large genomic studies of psychiatric disorders. The study aims to expand knowledge of the genetic and environmental risk factors for neuropsychiatric disorders in Africa through large-scale sample collection and analysis. The initial design is a case-control study in which cases are individuals with schizophrenia or bipolar disorder and controls are age, sex and ancestry matched with individuals from the same geographic location. Cases are patients who are recruited from clinical facilities, both inpatient and outpatient. Controls are people who present for treatment for general medical conditions at health facilities. Data on phenotype, mental disorders, history of physical health problems, substance use and history of past traumatic events was collected from all participants. Additionally, a sample of saliva is collected for DNA extraction. DNA samples were sent to the Broad Institute for genotyping using Illumina Infinium Global Screening Array.  

  Study phs002528

• Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

  While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE [Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics] project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis.

  Study phs001703

• Dataset for WGS and RNA samples of acute myeloid leukemia with MNX1 expression

  This dataset contains 10 samples of WGS, ATAC, 4C and RNAseq samples of patients with acute myeloid leukemia. The sequencing was performed on Illumina HiSeq 4000, 2000 and HiSeq X using Illumina TruSeq Nano DNA and Agilent Strand Specific RNA Kits. The sequencing was always paired.

  Dataset EGAD50000001098

• Dataset for Multiple Myeloma RNA data

  This dataset contains 371 case and control RNA sequencing samples of patients with multiple myeloma. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X, HiSeq 4000 and HiSeq 2000 using TruSeq Stranded RNA and TruSeq Stranded total mRNA Kits. The sequencing was always paired.

  Dataset EGAD50000000683

• Dataset for RNA sequencing of Glioblastoma samples

  This dataset contains 10x scRNA sequencing of glioblastoma samples. Sequencing was performed on a Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD50000000081

• Dataset for RNA PCNSL

  RNA sequencing of 19 samples from PCNSL tumors. Sequencing was performed on a HiSeq X Ten using Illumina TruSeq Stranded mRNA Kit. Sequencing was always paired.

  Dataset EGAD00001011119

• Dataset for desmoplastic small round cell tumor - WES

  This dataset contains 45 WES sequencing samples of patients with desmoplastic small round cell tumor. Sequencing was performed on Illumina HiSeq 2500, Illumina HiSeq 4000 and NovaSeq 6000 using Agilent SureSelect Human All Exon V5 Kit. The sequencing was always paired.

  Dataset EGAD50000000910

• Dataset for MCPlus_WES

  WES/WGS sequencing data of 75 chromothriptic tumor and control runs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001009276

• Dataset for negative_WES

  WES/WGS sequencing data of 242 chromothriptic tumor and control runs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001009278

• Genomic DNA analysis for malignant mesothelioma from the patients of Japan and USA.

  Malignant mesotheliomas (MMs) are highly aggressive adult malignancies and exposure to asbestos is the major factor involved in MM pathogenesis. It is desirable for a better understanding of the molecular pathogenesis of MM will lead to more specific and effective targeted therapies. In addition it is reported that germline mutation in a specific gene (ex. BAP1) associates familial MMs, and new candidate markers to determine a subject?s predisposition to MM and for early detection need to be identified. Analysis of genomic DNA from MM tumors and reference peripheral blood from Japan and USA are ongoing to find the common genomic characters beyond race.

  Study JGAS000108

• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• Neural Systems, Inhibitory Control, and Methamphetamine Dependence

  The Neural Systems, Inhibitory Control, and Methamphetamine Dependence study started in 2011 and is currently finishing data collection for its last participants. The study included methamphetamine abusing individuals and healthy control participants aged 18-55 years. Participants who qualified over the telephone were scheduled to visit the London Laboratory at the UCLA Semel Institute for Neuroscience and Human Behavior for the In-Person Screening Phase. The screening procedures, usually scheduled over two visits, determined if participants were eligible to complete the subsequent study visits. Both groups completed identical screening procedures, with the exception of more in-depth drug use questions for the methamphetamine users. After providing written consent, participants completed questionnaires about their mood, medical, psychiatric and drug use history, personality and life experiences. They also provided a urine sample to determine what drugs they recently used and a breath sample to determine the carbon monoxide levels in their system. The drug screen tested for recent methamphetamine, cocaine, opiates/opioids, benzodiazepines, THC and other amphetamines. Methamphetamine participants needed to test positive for methamphetamine at admission. If methamphetamine participants tested positive for any drugs other than methamphetamine or marijuana, and if healthy control participants tested positive for any drugs other than marijuana, they were excluded from the study. Additionally, the urine samples of female participants were tested for pregnancy; pregnant females were also excluded. If no exclusionary criteria were met during the first screening visit, participants completed a second screening visit to ensure they were mentally and physically healthy enough to participate. The second screening visit included a psychiatric diagnostic interview (DSM-IV (SCID-I) for first 500 participants and the MINI International Neuropsychiatric Interview M.I.N.I for the last 50 participants). Additionally, laboratory tests and procedures were completed by the UCLA General Clinical Research Center and interpreted by a study physician. Laboratory tests included vital signs (heart rate--BPM, blood pressure, and respirations), an electrocardiogram (ECG) to record the electrical activity of the heart, and an 18-cc blood sample to perform laboratory tests which included a complete chemistry and metabolic panel, hepatic panel, Hepatitis-C tests, and HIV test. The laboratory tests from this blood sample ensured that participants' liver and kidneys were functioning normally, and that their standard blood counts (red cell, white cell, and salts) were also normal. If a Hepatitis-C (HCV) or HIV test was positive, participants were not allowed to continue in the study and their results were reported to the California State Health Department. Participants deemed eligible to continue in the methamphetamine group participated on an outpatient basis or were admitted to the UCLA Medical Center to participate on an inpatient basis for up to 10 days. Typically, detectable levels of methamphetamine in urinalysis remain for 2-3 days, therefore inpatient days 0-3 served as a "washout period" and the methamphetamine abusing inpatient participants provided daily urine samples to test for recent drug use and pregnancy (female participants only). Outpatient participants were also required to remain abstinent from all drugs except nicotine and marijuana for at least 4 days prior to study sessions. Self-reported abstinence for outpatients was verified by urine toxicology and saliva screening at every visit to UCLA before completion of study procedures. Neurocognitive assessments, about three hours each, typically took place on two separate days. The purpose of the neurocognitive sessions were to assess participants' intellectual and neurocognitive functioning. On either the same day as the neurocognitive testing or on separate days, both methamphetamine abusers and healthy controls were administered a structural MRI to collect information on brain structure.

  Study phs001197

• Dataset for "CutNRun" sequencing of 12 samples of patients with colorectal cancer

  This dataset contains 12 "CutNRun" sequencing samples of patients with colorectal cancer. The sequencing was performed on Illumina NextSeq 550 using Cell Signaling TechnologyDNA Library Prep _Kit for Illumina Systems. The sequencing was always paired.

  Dataset EGAD00001015694

• How to upload Crypt4GH files

  Uploading files Users who hold an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files, please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention, such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. To manage the available resources, we enforce a limit of 10TB per submission account at any one time. If you exceed this limit, a “permission denied” message will be displayed. This will prevent you from uploading more files, but connecting to your inbox.For submissions larger than 10TB, please perform uploads in 10TB batches: register all the metadata and then finalise the submission. Upload the next batch of files and repeat the same metadata registration and finalisation process until you have completed the file upload. Further information can be found in the SP documentation. INBOX FTP The INBOX is only compatible with files encrypted using the Crypt4gh tool Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated, you will be able to request a submitter role. [Optional] Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g., ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. To upload files to your account, you can use the graphical user interface (GUI) or the command line. Graphical User Interface (GUI)We recommend using FileZilla, a free, open-source FTP client. However, you can use any other GUI that allows connecting over the SFTP protocol. For FileZilla as your GUI, follow these steps to upload files: Create a new connection in Site Manager (File > Site Manager) and select the following options (Figure 1): Protocol: SFTP - SSH File Transfer ProtocolHost: __EGA_INBOX_DOMAIN__Logon Type: Key fileUser: your EGA usernameKey file: Path/to/your/private_keyFigure 1: Process of establishing a new connection to __EGA_INBOX_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 inbox, ensuring seamless data transfers.Click Connect, and you will log in remotely to your home directory. You can think of this folder as a storage "in the EGA cloud" in which you will add your files for the EGA. The uploading area has three folders:To-encrypt: Files uploaded in this folder will be encrypted automatically on the fly.Encrypted: Files uploaded in this folder must already be encrypted with Crypt4gh. Upload your files here if your connection is unstable or you have problems completing the upload into-encrypt.Etc: This folder contains two files that allow the server to show you your username and group instead of some internal numbers. Please do not upload files here; otherwise, you will obtain a permission denied error. Find the files you want to upload by browsing your local storage (left side of your screen in FileZilla). Select all the files you want to upload, then right-click on them and select Upload (Figure 2). Figure 2: Step-by-step process of manually uploading files to __EGA_INBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can transfer data from their local storage to the "EGA cloud" by following the depicted steps Please note that regardless of which folder you upload your files in, both folders (to-encrypt, encrypted) will point to the same path (/) (Figure 3). Therefore, you will see your files in both folders. Figure 3: Both folders, to-encrypt and encrypted, point to the same path (/)" If your connection is unstable, please encrypt your files first using Crypt4gh. Then upload them to the ‘encrypted’ folder. The example above shows how to connect to __EGA_INBOX_DOMAIN__ using the private key. However, if you prefer to log in using your credentials, you can do so. Please go to the Frequently Asked Questions (FAQs)  for more information. SFTP command line To upload files securely to your private area of the EGA, you can use SFTP(Secure File Transfer Protocol) with your favorite FTP client. Here's what you need to know to get started: Connect to the target host __EGA_INBOX_DOMAIN__. This is the new hostname for the EGA SFTP service. Log in with your EGA username and key files (or password). Upload files to your private EGA inbox to ensure that only you can access the files. By following these steps, you can securely upload your files to the EGA for safe storage and sharing. Using the SFTP command line client in Linux/Unix Open a terminal and type sftp username@hostnameEnter your EGA passwordTo see a list of available SFTP commands, type helpsftp> put – Upload filesftp> get – Download filesftp> cd path – Change remote directory to ‘path’sftp> pwd – Display remote working directorysftp> lcd path – Change the local directory to ‘path’sftp> lpwd – Display local working directorysftp> ls – Display the contents of the remote working directorysftp> lls – Display the contents of the local working directoryType the "put" command to upload files. For example: put *.bamUse the bye command to close the connection (SFTP session). After uploading- Once you have uploaded files to the inbox, please bear in mind that the checksum needs to be calculated, which can take up to two days. You will only be able to link your files to a run/analysis once the encrypted checksum has been calculated.- When linking your files to the 'Run' or 'Analysis', ensure that the file name matches the file path '/name' in the INBOX folder.- Please delete the files from your SFTP INBOX after all the runs/analyses have been registered and files are ingested (SP > Files > Files ingested). This will clear your inbox space an allow you to upload more files. This will also prevent the files from reappearing in your Submitter Portal inbox. Frequently Asked Questions Specific to the inbox What username should I use to log in to my inbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username.  If you have forgotten your registered username, please contact our Helpdesk team for assistance. How are checksums calculated in your inbox? If you encrypt the file beforehand and upload it to the "encrypted" folder, the unencrypted checksum will not be calculated until the file is ingested (i.e., until it is used in a run/analysis). If the file is uploaded to the "to-encrypt" folder, then both checksums are calculated.Please bear in mind that after files have been uploaded to the inbox, the checksum must be calculated, which can take from a few hours to two days.  Specific to using keys to authenticate 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_INBOX_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 submission/data/uploading-files/inbox

• Molecular defects in pseudohypoparathyroidism or related disorders

  Maintaining calcium levels within a narrow normal range is of critical importance for numerous different cellular functions. One of the most important regulators of blood calcium levels is parathyroid hormone (PTH), which mediates its actions through the PTH/PTHrP receptor, a G&#945;s-coupled receptor. Few inherited disorders are characterized by diminished blood calcium levels and elevated blood phosphate levels; some of these disorders are caused by too little PTH synthesis and/or secretion (hypoparathyroidism, HP), while others are caused by resistance towards PTH (pseudohypoparathyroidism, PHP). Only few of the inherited forms of HP (&lt;10&#37;) have been defined at the molecular level. In contrast, genetic mutations have been identified for several inherited forms of PHP. For example, PHP type Ia (PHP-Ia) is caused by maternally inherited mutations in those GNAS exons that encode G&#945;s, while autosomal dominant PHP type Ib (AD-PHP-Ib) is caused by maternal inherited deletions within or up-stream of GNAS, which are associated with abnormal GNAS methylation. However, a large number of patients with PTH-resistance and thus hypocalcemia show GNAS methylation changes, but their underlying genetic defects have not yet been defined at the DNA level. These &#34;sporadic&#34; patients may be affected by an autosomal recessive form of PHP-Ib (AR-PHP-Ib), which is most likely not linked to the GNAS locus. In our studies, we propose to search through exome sequence analyses for novel genetic mutations responsible for novel autosomal dominant forms of HP that are not caused by mutations in the known disease-causing genes; some of these families are large enough to perform genetic linkage studies. We furthermore propose to search for the genetic mutation(s) responsible for the autosomal recessive variant of PHP-Ib through the analysis of whole exome sequences; for these studies we focus particularly on patients, whose parents are likely to be consanguineous. The proposed efforts are expected to lead to the identification of novel genes that are involved in parathyroid development and function (HP) and genes that are involved in the establishment or maintenance of GNAS methylation (AR-PHP-Ib).

  Study phs000476

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities WGS

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006865

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities RNA-Seq

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006866

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities DNA-Methylation

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006881