2965 results for "愛の戦士完全破壊2-re-imagination-version-鞭首絞め・電撃・ヘソか"

in 15.87 milliseconds.

• BLUEPRINT release August 2015, Bisulfite-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  Bisulfite-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001486

• BLUEPRINT September 2016, ChIPmentation T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38

  ChIPmentation data for 2 sample(s) T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002938

• BLUEPRINT release August 2016, RNA-Seq for osteoclast, on genome GRCh38

  RNA-Seq data for 2 osteoclast sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002479

• WGS data set used in the study, 2 samples

  WGS data set used in the study, 2 samples

  Dataset EGAD00001007966

• Intellance-2: omics data on recurrent glioblastoma patients participating in the Intellance-2 clinical trial, prior to treatment.

  This study contains omics data from patients from the Intellance-2 clinical trial, in which effectiveness of ABT414 in EGFR amplified recurrent glioblastoma patients was tested. Patients were randomly assigned to one of three arms: (1) standard of care treatement (TMZ or CCNU), (2) Only ABT414 and (3) ABT414 + (TMZ|CCNU)

  Study EGAS00001005437

• BLUEPRINT release August 2016, DNase-Hypersensitivity for monocyte - T=0days, on genome GRCh38

  DNase-Hypersensitivity data for 2 monocyte - T=0days sample(s). 4 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002300

• RNAseq files (dataset 2 of 2) for Mullighan PAX5_B-ALL

  RNAseq files (dataset 2 of 2) for Mullighan PAX5_B-ALL paper titled "PAX5-driven Subtypes of B-cell Acute Lymphoblastic Leukemia"

  Dataset EGAD00001004463

• Transcriptome of (peripheral blood), from donor Sample B, replicate 2 time-course biological replicates; 10x lane replicate 2

  time-course biological replicates; 10x lane replicate 2

  Dataset EGAD00001010091

• NanoSeq of buccal swab samples

  16 buccal swab samples were analyzed by Nanoseq. S3 in the file names indicates 28 mm^2 swab size, and S5 indicates 254 mm^2 swab size. We analyzed 28 mm^2 swab samples using paired 254 mm^2 swab samples as controls. The files were generated by the Nanoseq pipeline using GRCh37 as the reference genome.

  Dataset EGAD50000000999

• WGBS analysis corresponding to representative cases of iBCP-ALL patients

  This dataset was conceived to characterize the epigenomic landscape of representative iBCP-ALL subtypes. To do so, we performed Whole Genome DNA bisulfite-sequencing on 2 MLL-AF4, 2 MLL-AF9 and 2 non-MLL rearranged leukemias, and also 2 pools of BCPs obtained from fetal liver.

  Dataset EGAD00001005010

• BLUEPRINT release August 2016, RNA-Seq for conventional dendritic cell, on genome GRCh38

  RNA-Seq data for 2 conventional dendritic cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002345

• BLUEPRINT release August 2016, RNA-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002295

• BLUEPRINT release August 2016, RNA-Seq for adult endothelial progenitor cell, on genome GRCh38

  RNA-Seq data for 2 adult endothelial progenitor cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002334

• BLUEPRINT release August 2016, ChIP-Seq for regulatory T cell, on genome GRCh38

  ChIP-Seq data for 2 regulatory T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002293

• BLUEPRINT release January 2015, RNA-Seq for CD38-negative naive B cell

  RNA-Seq data for 2 CD38-negative naive B cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001145

• BLUEPRINT release August 2015, RNA-Seq for CD38-negative naive B cell, on genome GRCh38

  RNA-Seq data for 2 CD38-negative naive B cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001500

• BLUEPRINT release January 2015, RNA-Seq for CD8-positive, alpha-beta T cell

  RNA-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001137

• BLUEPRINT release August 2015, RNA-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001488

• Single Nuclei RNA sequencing batch 2

  This dataset includes the 2 extra normal samples adjacent to PTC tumors that were multiplexed and profiled using kits from different batches.

  Dataset EGAD00001011364

• BLUEPRINT release January 2015, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001152

• BLUEPRINT release August 2014, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000934

• Optimizing single-cell transcriptomic discrimination of atopic dermatitis versus psoriasis vulgaris

  AD Samples 1 and 2. AD1 has 2 runs of additional sequencing, AD2 has 1 run of additional sequencing.

  Dataset EGAD00001011286

• BLUEPRINT release August 2016, RNA-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002436

• BLUEPRINT release August 2016, RNA-Seq for effector memory CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002456

• BLUEPRINT release August 2016, RNA-Seq for central memory CD4-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 central memory CD4-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002349

• BLUEPRINT release August 2016, RNA-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002341

• BLUEPRINT release August 2016, RNA-Seq for effector memory CD4-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 effector memory CD4-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002469

• BLUEPRINT release August 2016, RNA-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  RNA-Seq data for 2 mesenchymal stem cell of the bone marrow sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002473

• BLUEPRINT release August 2015, RNA-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001535

• BLUEPRINT release August 2015, RNA-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001496

• IL-17B uses IL-17RA and IL-17RB to induce Type-2 inflammation from human lymphocytes

  IL-17 family cytokines are critical to host defense responses at cutaneous and mucosal surfaces. Whereas IL-17A, IL-17F, and IL-17C induce overlapping inflammatory cascades to promote neutrophil-mediated immunity, IL-17E/IL-25 drives type 2 immune pathways and eosinophil activity. Genetic and pharmacological studies reveal the significant contribution these cytokines play in antimicrobial and autoimmune mechanisms. However, little is known about the related family member, IL-17B, with contrasting reports of both pro- and anti-inflammatory function in rodents. We demonstrate that in the human immune system, IL-17B is functionally similar to IL-25 and elicits type 2 cytokine secretion from innate type 2 lymphocytes, NKT, and CD4+ CRTH2+ Th2 cells. Like IL-25, this activity is dependent on the IL-17RA and IL-17RB receptor subunits. Furthermore, IL-17B can augment IL-33–driven type 2 responses. These data position IL-17B as a novel component in the regulation of human type 2 immunity.

  Study EGAS50000000579

• REDS-IV-P Epidemiology, Surveillance and Preparedness of the Novel SARS-CoV-2 Epidemic (RESPONSE)

  Leveraging access to the blood supply and blood donors, the REDS-IV-P program began conducting the RESPONSE study (REDS-IV-P Epidemiology, Surveillance and Preparedness of the Novel SARS-CoV-2 Epidemic) in early 2020 in order to 1) evaluate if SARS-CoV-2 RNA was found in blood donations in the U.S. using an assay that could potentially be used to screen the blood supply if evidence of SARS-CoV-2 transfusion-transmission became apparent 2) conduct serosurveys using optimized assays/algorithms to monitor antibody reactivity in blood donor populations over time, 3) enroll SARS-CoV-2 positive donors and others into a longitudinal cohort study to answer fundamental questions about the evolution of viremia and immune responses, and 4) establish a sharable biorepository that includes specimens collected early on in the infection and potentially large volumes of plasma from infected/convalescent donors.Screening for SARS-CoV-2 RNAemia was completed using a SARS-CoV-2 nucleic acid test (NAT) performed on retained blood donor minipool samples from six geographic regions in the US. The study also included serosurveillance (i.e. testing for antibody directed against the SARS-CoV2 spike protein) of donations from the same six regions to document accruing seroincidence in blood donor populations and to project these rates in the general population. To enrich for donors with acute SARS-CoV-2 infection, another part of the study focused on donors reporting post-donation information (PDI) consistent with COVID-19 by testing plasma from all available PDI donations for SARS-CoV-2 RNA by NAT. Subjects who were diagnosed with COVID-19 based on PDI reports or who tested positive by SARS-CoV-2 NAT on index donation plasma were enrolled into a longitudinal follow-up study which collected multiple samples for up to one-year post-infection. The longitudinal follow-up study also enrolled community members who reported a new positive SARS-CoV-2 NAT test in the prior 7-14 days. The specific aims of the RESPONSE study were to: Establish the incidence of SARS-CoV-2 RNAemia in blood donations from the American Red Cross (ARC) regions in Los Angeles, Boston, and Minneapolis metropolitan areas, Bloodworks Northwest (BWNW), New York Blood Center (NYBC), and Vitalant San Francisco Bay Area, monthly between March and September of 2020 Conduct serosurveys to study antibody reactivity in same six areas as above monthly for March to August 2020 Document rates of Post Donation Information (PDI) reports to determine PDI rates relevant to SARS-CoV-2 clinical disease and test index donation plasma from PDI donors for SARS-CoV-2 RNA Enroll SARS-CoV-2 infected subjects into a longitudinal cohort study to answer fundamental questions on the evolution of viremia, early immune responses and waning of immunity over 3-12 months of follow-up Establish a sharable biorepository of samples from all of the above Aims for future research The data from Aims 3 and 4 above is being made available in BioData Catalyst.Biospecimens for these Aims are managed by Vitalant Research Institute (VRI). More information on biospecimens is available.

  Study phs003578

• Synthetic - GDI synthetic dataset (Population 11 Finland, Subgroup 2)

  Synthetic - This dataset contains the pheno-clinical and genomic information of 42046 individuals from COVID Population 11 Finland, Subgroup 2. 2010 are affected by Phenotype 1, 2010 are affected by Phenotype 2, 188 are affected by Phenotype 1 and 2, and 37838 are control. The dataset also contains the information about the smoking habits of each individual.

  Dataset EGAD50000000955

• BLUEPRINT release January 2015, Bisulfite-Seq for erythroblast

  Bisulfite-Seq data for 2 erythroblast sample(s). 35 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001133

• Splicing signature analysis of RNU4-2, RNU5A-1 and RNU5B-1

  Pathogenic variants in the snRNA RNU4-2 were recently described as a frequent cause of neurodevelopmental disorders. In our study we further delineate the phenotype associated with RNU4-2 and we also identify pathogenic variants in RNU5A-A and RNU5B-1. Capture-based RNA-Seq were performed to compare splicing pattern between affected and control individuals. A strong signature based on alternative 5' splice site usage was found for RNU4-2 patients, and we suggest an either 5' or 3' signature depending on the variant's localiztion in U5 genes.

  Study EGAS50000000889

• The polarity and specificity of antiviral T lymphocyte responses determine susceptibility to SARS-CoV-2 infection in cancer patients and healthy individuals

  We monitored patient's anti SARS-CoV-2 immune responses using an in vitro cross presentation assay. The goal of this study was to identify immune correlates of clinical protection against SARS-CoV-2 infection. Briefly, peripheral blood mononuclear cells of patient were divided into a monocyte and lymphocyte. Monocyte were differentiated into monocyte derived dendritic (mo-DC)cells using GM-CSF and Interferon alpha. Mo-DC were then loaded with SARS-CoV-2 culture lysates , or VeroE86 lysates. SARS-CoV-2 loaded mo-DC were then used to stimulates their autologous lymphocytes and T cell cytokine secretion was monitored in the supernatant. We discriminated patients producing IL-2 and patients producing IL-5. RNA sequencing was performed for 18 patients, to identify gene profile associated with IL-2 or IL-5 production.

  Dataset EGAD00001008538

• 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

• MGA-NUTM1 fusion in high grade spindle cell sarcoma Data

  There is a total of 4 sample data (2 WGS and 2 RNAseq) belong to 2 patient deposited in this study.

  Dataset EGAD00001004479

• BLUEPRINT release August 2015, Bisulfite-Seq for erythroblast, on genome GRCh38

  Bisulfite-Seq data for 2 erythroblast sample(s). 35 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001484

• Field Studies of Human Immunity to Amebiasis in Bangladesh (NIH Birth Cohort) and Exploration of the Biologic Basis for Underperformance of Oral Polio and Rotavirus Vaccines in Bangladesh (PROVIDE)

  NIH birth cohort study Amebiasis is a common cause of diarrhea and is associated with malnutrition in grade-school aged children in an urban slum of Dhaka, Bangladesh. Field Studies of Human Immunity to Amebiasis in Bangladesh was designed to determine the contribution of amebiasis to illness in the first 2 years of life when most deaths due to diarrhea occur, and understand the immunologic and genetic factors that protect children from amebiasis. The hypothesis underlying the study is that susceptibility to amebiasis is determined by host innate and acquired immune responses that vary between individuals in part due to: human genetic polymorphisms; environmental influences including malnutrition and concurrent geohelminth infection; and virulence differences among Entamoeba histolytica genotypes. Specific aims proposed in the design of the study were to: a) Measure the incidence of amebiasis and correlate it with human and parasite genetic polymorphisms, immune responses, and environmental factors such as geohelminth infection and malnutrition; b) Test the hypothesis that protective immunity is mediated both by innate immune responses initiated via TLR stimulation as well as by mucosal IgA against the Gal/GalNAc lectin and systemic IFN-&#947;; c) Test for the association of common genetic polymorphisms in host innate and acquired immune genes with incidence of amebiasis. 629 newborn babies were enrolled and followed regularly through bi-weekly surveillance for diarrheal episodes, anthropometry at 3-month interval until 60 months of age. The infants that were consented for GWAS analysis were genotyped in 3 separate batches at different times, on 3 different arrays. Quality control was performed on the 3 separate data sets and then jointly after merging. Genetic data available on 447 infants together with their phenotype data is made available in this submission PROVIDE (Performance of Rotavirus and Oral Polio Vaccines in Developing Countries) Study Oral polio and rotavirus vaccines are significantly less effective in children living in the developing world. Environmental enteropathy, which is associated with intestinal inflammation, decreased absorption and increased permeability, may contribute substantially to oral vaccine failure in developing country settings. The primary objective of the study was to determine the association of environmental enteropathy with the efficacy of oral polio and rotavirus vaccines in children in Bangladesh. Secondary and exploratory objectives were designed to address other possible causes of oral vaccine underperformance including malnutrition, interference with maternal or breastmilk antibodies, changes in gut microbiota, and genetic susceptibility. The PROVIDE study was structured as a 2x2 clinical trial with a prospective birth cohort enrollment of 700 infants and their mothers in the urban slum of Mirpur, Dhaka, Bangladesh. All children received the full series of Bangladesh&#39;s Expanded Program on Immunization vaccines, including oral polio vaccine (OPV) and followed for their first 2 years of life. Half the children were randomized to receive an inactivated polio vaccine (IPV) for their 4th dose at 39 weeks instead of the standard OPV dose. In the other trial, half the infants received the 2-dose rotavirus vaccine (Rotarix) with delayed dosing at 10 and 17 weeks of age. A detailed description of the study design and procedures can be obtained from PROVIDE methods publication: Kirkpatrick B.D., Colgate R.E., Mychaleckyj J.C., Haque R., Dorothy D.M., Carmolli M.P., et al. (2015) Am J Trop Med Hyg 92, 744-751 The Poliovirus trial and results are described in Mychaleckyj et al, Vaccine 2016 The Rotavirus trial and results are described in Colgate et al, Clin Infect Dis 2016 The PROVIDE infants were genotyped on a custom Affymetrix Axiom array (30K SNPs) at the University of Virginia Center for Public Health Genomics; and on a pre-production version of the Illumina MEGA v2 chip at the Wellcome Trust Sanger Institute, UK. The latter genotyping was performed under the auspices of the VaccGene Consortium. Analyses are ongoing to identify variants associated with the included phenotypes. A manuscript describing the genotyping methods and analysis is in preparation for the initial phenotypes. The Infection Malnutrition Bangladesh Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001475 Infection Malnutrition Bangladesh Cohort. phs001476 Amebiasis Immunity phs001478 Polio Rotavirus Vaccines phs001665 Cryptosporidiosis Enteropathogens

  Study phs001475

• 10xscRNA sequencing of 2 samples RRMM (multiple myeloma)

  Paired scRNA sequencing using 10xgenomics library preparation and Illumina HiSeq4000 for sequencing of 2 samples RRMM (relapsed refractory multiple myeloma)

  Dataset EGAD00001009681

• Chromatin accessibility of clear cell renal cell carcinoma

  To investigate chromatin accessibility in ccRCC, we performed ATAC-seq in 3 ccRCC cell lines (786-O, A498, UMRC-2), and 1 normal kidney epithelium cell line (HK-2), cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions

  Study EGAS50000001325

• Genetic_Overlap_between_Metabolic_and_Psychiatric_disease

  The Genetic Overlap between Metabolic and Psychiatric Diseases (GOMAP) study comprises samples from four patient groups: 964 schizophrenia samples, 921 type 2 diabetes patients, 582 patients with comorbid schizophrenia and type 2 diabetes and 280 samples with another psychiatric diagnosis.

  Study EGAS00001002723

• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Study EGAS00001004689

• BLUEPRINT release January 2015, Bisulfite-Seq for central memory CD8-positive, alpha-beta T cell

  Bisulfite-Seq data for 2 central memory CD8-positive, alpha-beta T cell sample(s). 27 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001180

• BLUEPRINT release August 2015, Bisulfite-Seq for plasma cell, on genome GRCh38

  Bisulfite-Seq data for 2 plasma cell sample(s). 17 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001522

• BLUEPRINT release August 2015, Bisulfite-Seq for class switched memory B cell, on genome GRCh38

  Bisulfite-Seq data for 2 class switched memory B cell sample(s). 21 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001548

• BLUEPRINT release August 2015, Bisulfite-Seq for conventional dendritic cell, on genome GRCh38

  Bisulfite-Seq data for 2 conventional dendritic cell sample(s). 30 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001497

• RNA-sequencing and targeted DNA-sequecing of human thyroid tumors and normal samples

  RNA-sequencing data: 5 normal thyroid tissues, 14 papillary thyroid carcinomas, 2 lymph node metastases, 19 poorly differentiated thyroid carcinomas and 17 anaplastic thyroid carcinomas; Targeted DNA-sequencing of the 165 genes included in the “Solid and Haematological tumors” panel (BRIGHTCore, Brussels, Belgium): 2 normal thyroid tissues, 2 poorly differentiated thyroid carcinomas and 7 anaplastic thyroid carcinomas; 2 FASTQ files for each sample (paired).

  Dataset EGAD00001011678

• Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2

  Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which is the cause of a present global pandemic, infects human lung alveolar type 2 (hAT2) cells. Characterizing pathogenesis is crucial for developing vaccines and therapeutics. However, the lack of models mirroring the cellular physiology and pathology of hAT2 cells limits the study. Here, we develop a feeder-free, long-term three-dimensional (3D) culture technique for hAT2 cells derived from primary human lung tissue, and investigate infection response to SARS-CoV-2. By imaging-based analysis and single-cell transcriptome profiling, we reveal rapid viral replication and the increased expression of interferon-associated genes and pro-inflammatory genes in infected hAT2 cells, indicating robust endogenous innate immune response. Further tracing of viral mutations acquired during transmission identifies full infection of individual cells effectively from a single viral entry. Our study provides deep insights into the pathogenesis of SARS-CoV-2, and the application of defined 3D hAT2 cultures as models for respiratory diseases.

  Study EGAS00001004508