23272 results for "ega"

in 37.50 milliseconds.

• NeurOmics_HD_Biomarker-1_V1

  This data set includes RNAseq data from 136 samples from the TRACK-HD cohort including premanifest, manifest and control subjects. Data can only be used for Huntington's disease related research.

  Dataset EGAD00001002699

• Rare coding variants in lupus risk genes

  Set of 133 bam files from patients affected with Lupus. BAM alignments for exonic variants present in 76 Lupus-related genes. VCF file describing the variants.

  Dataset EGAD00001004859

• Dataset WES of RRMM patients

  Dataset consists of forty vcf files, outcome of variant calling with caveman algorithm of matched bam file (TUMOR and NORMAL) of RRMM patients. Bam files were obtained from whole exome sequencing!

  Dataset EGAD00001005098

• Whole exome sequence of intratumor heterogeneity study

  This dataset contains whole exome sequence data from 86 samples from 6 patient. All the experiments were performed on Illumina HiSeq platform with raw reads stored in fastq format.

  Dataset EGAD00001005453

• Ovarian cancer organoid biobank - followup

  WGS of more samples in the ovarian cancer organoid biobank dataset.

  Dataset EGAD00001005707

• Whole exome sequencing study for 8 pairs of primary NSCLCs and distant metastases

  Whole exome sequencing study for 8 pairs of primary NSCLCs and distant metastases. This dataset includes a total of 30 samples.

  Dataset EGAD00001005764

• 10X Genomics WGS data of de novo assembly individual EGYPT

  10x Genomics linked read data used in variant phasing and de novo assembly scaffolding for the EGYPT individual (mapped against GRCh38).

  Dataset EGAD00001006035

• Somatic evolution in the non-neoplastic IBD affected colon

  Whole genome and whole exome sequencing data supporting the manuscript 'Somatic evolution in the non-neoplastic IBD affected colon' by Sigurgeir Olafsson et al.

  Dataset EGAD00001006061

• OSCC WES and genomes

  WES (N=18) and WGS (N=2) of OSCC tumors and normals with the aim of identifying novel mutational signatures in Asian tumors

  Dataset EGAD00001006077

• Accurate mapping of mitochondrial DNA deletions and duplications using deep sequencing

  The dataset comprises of muscle samples from three patients with mitochondrial disease: Patient 1, age9; Patient 2, age16; and Patient 3, age 58.

  Dataset EGAD00001006079

• subset of WES data from umbrella study EGAS00001004338, used in EGAS00001004786

  linking 82 samples/82 runs of WES from EGAS00001004338 Umbrella study to EGAS0001004786 study

  Dataset EGAD00001006613

• PBMCs of HCC Patients treated with anti-PD1 ICB

  10 samples (one baseline, 9 on-treatment). Fastq files containing 5'GEx data, prepared using 10x Genomics pipeline, sequenced on Illumina HiSeq4000.

  Dataset EGAD00001006645

• Single cell sequencing of newly-diagnosed and recurrent GBM

  Single cell RNA and CITE sequencing of newly-diagnosed and recurrent GBM

  Dataset EGAD00001006778

• 1000IBD.eQTL.study.release.inflammation.eQTLsummary

  eQTL.study.release.inflammation.eQTLsummary

  Dataset EGAD00001006798

• WES of CTCL patients

  Paired end whole exome sequencing (WES) data of tumor/normal pairs (sorted malignant CD3+/Vb+ T-cells and CD19+ non-malignant B-cells) for the identification of somatic mutation.

  Dataset EGAD00001006895

• Initial WGS of plasma cell neoplasms in fire fighters exposed to the WTC attack

  Initial WGS of plasma cell neoplasms in fire fighters exposed to the WTC attack

  Dataset EGAD00001006896

• PIK3CA SiMSen-Seq

  Simple, Multiplexed, PCR-based barcoding of DNA for Sensitive mutation detection using Sequencing (SiMSen-Seq) of 11 PIK3CA hotspot mutations in plasma DNA of breast cancer patients.ng

  Dataset EGAD00001006897

• ctDNA dataset

  ctDNA data from IMvigor010: ctDNA data include TMB_status, cfDNA_extracted_ng, Plasma_Volume_Used_ml, Sample_Call, Sample_Number_Positive_Calls, Sample_Mean_VAF_In_Plasma (%), Sample_MTM_per_mL_In_Plasma for 581 patients across IMvigor010.

  Dataset EGAD00001007574

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - sequence data (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - sequence data (Mutographs)

  Dataset EGAD00001015386

• The University of Hong Kong Intestinal Metaplasia Organoids Study RNASeq Data

  RNASeq data generated from organoid cultures established from normal gastrointestinal organoids, long-term and paired tumor frozen tissues.

  Dataset EGAD00001015421

• A98284A

  Whole genome sequencing for single cells for library A98284A 1265 samples; filetype=bam

  Dataset EGAD00001008262

• Genome and transcriptome sequence data from a fibrovascular brain tumor tumor patient

  Genome and transcriptome sequence data from a fibrovascular brain tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015271

• Genome and transcriptome sequence data from a papillary thyroid carcinoma tumor patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015276

• Genome and transcriptome sequence data from a multifocal glioblastoma multiforme tumor patient

  Genome and transcriptome sequence data from a multifocal glioblastoma multiforme patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015281

• Assessing mitochondrial bioenergetics in coronary artery disease: A translational left ventricular tissue study in humans (The AMBITION study).

  Single nuclei transcriptomic data from the AMBITION study.

  Dataset EGAD00001011078

• 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

• Sequencing data for oesophageal and related samples - Ganguli et al (sWGS)

  Data supporting: "TBC" Ganguli et al (sWGS for 75 samples)

  Dataset EGAD00001011189

• Molecular mechanism of Vd2 T cells upon mevalonate metabolism inhibition

  Raw molecular data of Vd2 T cells upon treatment with different stimuli and mevalonate pathway inhibitors.

  Dataset EGAD00001011322

• Effects of busulfan, fludarabine and clofarabine treatment on human small intestinal organoids.

  Instestinal organoids treated with either busulfan, fludarabine or clofarabine for 24h

  Dataset EGAD00001011336

• Single-cell RNA and TCR sequencing of 40 advanced HCC biopsies.

  Single-cell RNA and TCR sequencing of 40 advanced HCC pre-treatment biopsies from 38 patients.

  Dataset EGAD00001011347

• scRNA-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

  Study describing the differentiation trajectory...

  Dataset EGAD00001015545

• Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Dataset EGAD00001015487

• Dataset for ChIP-seq data for neuroblastoma tumor samples(NB,Neuroblastoma)

  Dataset for H3K27me3 ChIP-seq data of neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 2500

  Dataset EGAD00001015813

• 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

• atrial appendage RNA-seq in non-, paroxysmal and persistent atrial fibrillation

  64 left atrial appendages from patients without atrial fibrillation (AF) undergoing cardiac surgery, patients with paroxysmal AF and with persistent AF (~20 per group). Trizol RNA isolation, rRNA depletion, paired transcriptome sequencing on illumina NovaSeq 6000. Provided are FastQ and BAM files. Additional data (e.g. clinical characteristics, RIN values etc.) can be provided upon reasonable request. The same RNA samples (62 out of 64) were used for miRNA sequencing. Results from miRNA seuqencing are stored in the EGA database managed by the same DAC.

  Dataset EGAD00001007693

• PCA Atlas Chromium scRNA-seq and demultiplexing support (FASTQs, BAMs, capture-level VCFs and mapping tables)

  This dataset contains Chromium single-cell RNA-seq data and demultiplexing support for the PCA Atlas study EGAS00001008332. Included data objects: - 16 Chromium scRNA-seq FASTQ runs (EGAR accessions) for captures PCa1–PCa16. - 16 aligned BAM analyses (one Cell Ranger possorted_genome_bam.bam per capture). - 16 capture-level genotype VCF analyses derived from the Axiom UK Biobank array, used as demultiplexing panels. - demux_map.csv (EGAZ00001945520): donor–capture–sample mapping for genotype-based demultiplexing. - chromium.csv (EGAZ00001945537): run-level mapping linking captures, EGA samples, runs (EGAR), experiments (EGAX) and BAM analyses. Together these objects provide a complete view of the Chromium scRNA-seq data and the genotype-based demultiplexing support needed to reproduce donor assignment and downstream analyses.See also https://zenodo.org/records/17372603

  Dataset EGAD00001015795

• Targeted sequencing of 72 prostate cancer driver in 712 plasma cell free DNA samples

  Dataset contains targeted sequencing data of 712 plasma cell free DNA samples and 428 white blood cell samples collected from 428 men with metastatic prostate cancer. Target capture was performed using a hydridization-based custom Roche SeqCap EZ Choice kit, designed to capture all exons of 72 prostate cancer driver genes. Cell free DNA was extracted from 10 mL blood samples. Libraries were sequenced using Illumina HiSeq 2500 or Illumina MiSeq instruments to a median coverage of 750x. 62% of samples had ctDNA fraction above 2% of total cfDNA. Note that "Dataset type" is erroneously listed as "Amplicon sequencing", because "Captured-based targeted sequencing" or "Hybridization-based targeted sequencing" were not available options in EGA at the time of submission.

  Dataset EGAD00001004208

• WTCCC case-control study for Autoimmune Thyroid Disease - Combined Controls

  WTCCC genome-wide case-control association study for Autoimmune Thyroid Disease (ATD) - Combined Controls.

  Study EGAS00000000021

• WTCCC2 Pharmacogenomic Response to Statins study

  A WTCCC2 project genome-wide study for pharmacogenomic response to statins (PR) in individuals from Scotland.

  Study EGAS00000000121

• HLA has strongest association with IgA nephropathy in genome-wide analysis

  GWAS study of families with probands with IgA nephropathy from the UK Glomerulonephritis DNA bank

  Study EGAS00000000031

• Sequencing data (BAM files) from - A mutation in VPS15 (PIK3R4) causes a ciliopathy and affects IFT20 release from the cis-Golgi. The Data Access Committee (DAC) is responsible for sequencing data release to external requestors based on consent and/or National Research Ethics terms.

  Dac EGAC00001000552

• EGAD00000000004

  WTCCC1 project Coronary Artery Disease (CAD) samples

  Dataset EGAD00000000004

• EGAD00000000005

  WTCCC1 project Inflammatory Bowel Disease (IBD) samples

  Dataset EGAD00000000005

• EGAD00010000744

  Subset 2 of osteoarthritis cases genotyped on Illumina 610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with consent for osteoarthritis studies only.

  Dataset EGAD00010000744

• EGAD00010000434

  Normalised mRNA expression

  Dataset EGAD00010000434

• EGAD00010000438

  Normalized miRNA expression data

  Dataset EGAD00010000438

• EGAD00010000442

  Affymetrix SNP 6.0 CEL files

  Dataset EGAD00010000442

• Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma

  Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma

  Dataset EGAD00001000001

• Unraveling the genetic basis of a collagen migration defect in patients with a combined platelet dysfunction and reduced bone density

  Unraveling the genetic basis of a collagen migration defect in patients with a combined platelet dysfunction and reduced bone density

  Dataset EGAD00001000109

• Glioma GWAS summary statistics

  Meta-analysis association statistics from case-control analysis (includes imputed SNPs)

  Dataset EGAD00010001657

• VIKING Health Study - Shetland 30X WGS

  30x whole genome sequencing of samples from the VIKING Health Study - Shetland. 500 DNA samples were sequenced using the Illumina HiSeq X system. FASTQ files are deposited

  Dataset EGAD00001005378

• The sanger result of LAM disease

  Tumor biopsies from LAM disease were analyzed by sanger to characterize the alterations in patients ,to elucidate the landscape of genetic/genomic alterations. The dataset include 21 samples.

  Dataset EGAD00010001761

• Single cell PDAC samples

  h5 files from 15 single cell PDAC samples described in "Transcription phenotypes of pancreatic cancer are driven by genomic events events during tumour evolution"

  Dataset EGAD00010001811

• AI

  Allelic imbalance (AI) region calls: start and end positions and the measured mBAF and LRR mean of each region after the BAF segmentation algorithm. Software: Illumina GenomeStudio;PennCNV v. 1.0.4;BAF segmentation v1.2.0.

  Dataset EGAD00010001926

• HumanMethylation450_NL

  This dataset includes IDAT files from 2,790 blood samples. The samples were profiled using the Illumina Infinium HumanMethylation450 (450k) BeadChip.

  Dataset EGAD00010001938

• HSP90 inhibitor resistant cells

  K562 cells were treated with different HSP90 inhibitors (PuH71 and Coumermycin A1) and the CNV profil was compared to the parental K562 (untreated). In addition, the CNV profile of HSP90AB1 knockout K562 cells was analyzed.

  Dataset EGAD00010002336

• Mexican_Biobank_Genotypes

  Samples from the Mexican Biobank

  Dataset EGAD00010002361

• vaccgene_1000G_MKK_hla

  VaccGene HLA imputation panel variants and HLA allele calls for all individuals across all tested sequence platforms and countries, and the high quality direct genotypes for these individuals (with genotype data available) across the MHC in PLINK format

  Dataset EGAD00010002577

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Transcriptomic sequencing on pre-immunotherapy melanoma patients.

  Dataset EGAD00001007710

• OncoScan SNP data set for localized follicular lymphoma (lFL)

  149 unpaired initial tumor samples (133/149 FFPE and 16/149 fresh frozen samples) of lFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002593

• Methylation profiling of sarcoma and TFCP2-rearranged rhadomyosarcoma samples

  Methylation profiling of 345 sarcoma and TFCP2-rearranged rhadomyosarcoma samples, using the approach described "Genomic, transcriptomic, functional, and mechanistic characterization of rhabdomyosarcoma with FUS-TFCP2 or EWSR1-TFCP2 fusions"

  Dataset EGAD00010002451

• Long-read mRNA sequencing of retinal organoids

  Long-read (PacBio) sequencing of two retinal organoid samples. One sample was treated with cyclohexamide. Files are ccs BAM format files generated by a Sequel IIe machine.

  Dataset EGAD50000000100

• Peru.mg.maf.subsetEGA

  Genotypes generated for study investigating signals of selection in Peruvians from three ecological regions. 96 genotypes in plink format after QC filtering (missingness per individual, per variant and minor allele freq). See publication for more details on QC filtering.

  Dataset EGAD00010002261

• Evolutionary Trajectories of Small Cell Lung Cancer under Therapy

  We performed whole exome sequencing, whole genome sequencing and transcriptome sequencing of multiple tumor regions from 65 patients with SCLC.

  Dataset EGAD50000000243

• SECRETO Oral metagenome

  The dataset comprises data for n=329 participants who underwent saliva sampling. Shotgun metagenomic paired-end sequencing was conducted using the Illumina NovaSeq 6000 platform, and the resulting files are in FASTQ format.

  Dataset EGAD50000000283

• Multi time/space shallow whole genome sequencing of esophageal adenocarcinoma's

  Shallow whole genome sequencing of 170 samples from 24 esophageal adenocarcinoma's. DNA was obtained from FFPE stored material. Illumna Hiseq 400 was used for sequencing.

  Dataset EGAD50000000318

• Multimodal epigenetic sequencing analysis for colon cancer

  Targeted methylation sequencing (enzymatic conversion) data of plasma samples collected from colon cancer patients and non-cancer subjects.

  Study EGAS50000000052

• Longitudinal 3'RNA-Seq data from MEMORI trial

  80 bam files generated from 3'RNAseq of tumour biopsies from oesophageal adenocarcinoma. Samples were collected within the clinical MEMORI trial.

  Dataset EGAD50000000357

• AmsterdamUMC Data Access Committee for the EPIC-CD study

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired as part of the EPIC-CD project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000097

• ATAC Dataset for 19 T-ALL patient samples and 1 normal control sample

  19 ATAC-seq from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference

  Dataset EGAD50000000024

• Ion Proton WES raw and processed data from and novel immunodeficiency proband.

  BAM and VCF files from WES of an affected proband with a novel immunodeficiency phenotype caused by homozygous mutation of SLC19A1.

  Dataset EGAD50000000524

• Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness

  RNAseq from patient-derived primary tumor cells, cultured or not on organotypic cultures mimicking the tumor microenvironment

  Study EGAS50000000355

• Methylation array data of thymic epithelial tumors (TC, NET, THYM)

  Methylation microarray data (Illumina 850K) of 52 thymic epithelial tumors. 13 patients with thymoma A and B, 32 thymic carcinoma (TC) and 7 neuroendocrine tumors of the thymus (NET).

  Dataset EGAD00010002355

• L1-Architect Project DAC

  This Data Access Committee and policies are for controlling the correct use of the omics datasets generated within the L1-Architect Project, to investigate the impact of L1 transposable elements in tumours with high and ultrahigh rates of somatic retrotransposition

  Dac EGAC50000000289

• Whole-exome sequencing of acute myeloid leukemias with aberrations of chromosome 7

  This dataset contains the bam files of 60 paired samples of AML and remission samples.

  Dataset EGAD50000000621

• 16SV4-sequence data

  Raw 16SV4-sequence data from bronchial brushing DNA obtained from healthy volunteers prior to and four weeks after ICS treatment.

  Dataset EGAD50000000527

• Usher patients and USH2A-associated RP patients

  This is a Next Generation Sequencing approach based on whole Usher Syndrome genes sequencing with the aim of diagnosing USH patients and USH2A-associated RP patients

  Dataset EGAD50000000687

• Structural variants

  Structural variants assessed in 6 patient samples with varying phenotypes, through the use of sniffles2 with a support parameter of 1 and at a length of 30 bp

  Dataset EGAD50000000741

• SCLC MeDIP-seq

  Methylation profile of 33 patients with small cell lung cancer (SCLC) for both, tumour and normal lung samples using MeDIP-seq.

  Dataset EGAD50000000724

• 10X single-nuclei RNA sequencing

  Single-nuclei sequencing data from four neuroblastoma patients. Each patient was run on two lanes, resulting in two runs per patient. Data is provided in paired-end fastq files.

  Dataset EGAD50000000727

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  We sought to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk.

  Dac EGAC50000000235

• ExerFiber (Single muscle fiber exercise responses)

  Individual fibers of human skeletal muscle biopsies - collected immediately post-exercise and after 3h of recovery. m. vastus lateralis

  Study EGAS50000000419

• Detection of MEIS2 inversion using ONT adaptive sequencing

  DNA was extracted from whole blood, and sequenced on a Promethion flow cell. The target region covered chr15:22874354-55370932 (Grch38). The resulting data was aligned to Grch38 using minimap2.

  Dataset EGAD50000000893

• WTCCC case-control study for Ankylosing Spondylitis - Combined Controls

  WTCCC genome-wide case-control association study for Ankylosing Spondylitis (AS) - Combined Controls.

  Study EGAS00000000019

• Clinical data and mapping file

  Patient demographic characteristics, treatment, and survival data for IMbrave151 (N = 162), with one patient per line. Mapping file to map anonymized subject IDs to RNAseq IDs

  Dataset EGAD50000000569

• WGS FASTQ files studied in A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  This data set contains 2 paired fastq files (WGS).

  Dataset EGAD50000000947

• UMI-4C in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  UMI-4C sequencing data generated for MLH1 promoter to assess allele-specific interactions in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  Dataset EGAD50000000713

• COVID-19 progression and convalescence in common variable immunodeficiency patients

  Longitudinal analysis of single-cell RNAseq datasets of PBMCs from COVID-19 CVID patients and controls.

  Study EGAS50000000368

• NanoRCS and Reference samples

  Genome-wide NanoRCS of cell-free DNA from plasma of healthy controls (4 samples) Genome-wide sequencing of reference blood sample of healthy controls (4 samples)

  Dataset EGAD50000000974

• RNAseq TPM

  RNAseq TPM matrix (transcriptome profiling by high-thoughput sequencing) Matrix (30,727 features by 2,803 samples) of log2-transformed TPM counts from RNAseq data for the four IMvigor trials.

  Dataset EGAD50000001100

• WGBS dataset for lymphnode metastasis samples from prostate cancer

  This dataset contains WGBS sequencing data of lymphnode metastasis samples from prostate cancer. Sequencing was performed on Illumina HiSeq X Ten. The sequencing was always paired.

  Dataset EGAD50000001183

• small RNA sequencing for 6 patients

  small RNA sequencing data for 3 patients with type 2D diabetes, and 3 patients with non diabetes. Single end sequencing was performed with read length of 100.

  Dataset EGAD50000001259

• McQuillin_Global_WES_Schizophrenia

  Whole Exome Sequencing of Schizophrenia cases and matched controls performed at the Broad Institute on a cohort from UCL, London, UK

  Study EGAS50000000901

• Guardant ctDNA

  This data table represents each patient molecular response based on ctDNA (using Guardant 360) percentage at baseline and cycle 3 day 1

  Dataset EGAD50000001339

• Linked-read data of additional normal blood samples

  Linked-read whole genome sequencing data of 15 normal blood samples from brain tumour patients. The dataset consists of BAM files generated by the Long Ranger pipeline from 10x Genomics.

  Dataset EGAD50000001390

• Dac for "Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)" with PD Dr. med. Tobias Kessler, t.kessler@dkfz.de/ Prof. Dr. med. Wolfgang Wick, wolfgang.wick@med.uni-heidelberg.de

  Dac EGAC00001003521

• Macrophage polarisation to M1 and M2 phenotypes

  iPSC-derived macrophages were polarised with LPS/IFN-gamma or IL4 to M1 and M2 phenotypes, respectively.

  Study EGAS50000000820

• PCNSL single-cell dataset

  This dataset includes 4 samples with scRNA-seq and 3 sample with CITE-seq, scTCR-seq and scBCR-seq.

  Study EGAS50000000474

• Bulk transcriptomics of Human High-Grade-B-Cell-Lymphomas differentiated according to IGH status

  GCB DLBCL MB2 DE and HGBCL-DH-BCL2(-BCL6) cases classified according to IGH status in IGH+ or IGH-undetectable

  Dataset EGAD50000001524

• Long-read RNA sequencing of human normal liver organoid with or without SF3B4 overexpression

  Project aims to find alternative splicing events and resulting transcript isoforms modulated by SF3B4

  Study EGAS50000000849