15077 results for "cancer studies using rna-seq"

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• MiRNA_Validation

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002752

• MiRNA_TrainTest

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002754

• 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

• Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be Heart Health Study (nuMoM2b Heart Health Study)

  Participants from study sites that recruited during the original study funded by NICHD of pregnant people, called nuMoM2b, participated in this study. The nuMoM2b-HHS1 was a prospective observational follow-up study of the nuMoM2b cohort consisting of interval contacts via phone or web every 6 months to about a year, and an in-person visit 2 to 7 years after the end of the nuMoM2b pregnancy including: Demographics Self-administered questionnaires Clinical measurements Lab results An in-home sleep breathing assessment for the subset of participants with at least one valid sleep breathing assessment during nuMoM2b Abstraction of medical records for pregnancies subsequent to nuMoM2b involving self-reported adverse pregnancy outcomes or multiple births Abstraction of medical records of selected cardiovascular risk-related events or procedures reported by participants. The study capitalized on the rich and unique data prospectively collected during nuMoM2b (biomarkers, uterine artery Doppler studies, fetal growth, psychosocial determinants, sleep, and blood pressure) and rigorous definitions of adverse pregnancy outcomes. These data are stored in the NICHD repository DASH (https://dash.nichd.nih.gov/study/226675). A total of 8,838 nuMoM2b participants were targeted for contact during nuMoM2b-HHS and 7,872 participants were reached, of whom 7,003 completed one or more interval contacts. Of these, 5,206 agreed to the visit, and 4,508 attended an in-person visit.

  Study phs002808

• Characterizing the Neurobehavioral Phenotype(s) in MPS III (Pilot Study)

  Mucopolysaccharidosis III (MPSIII) syndrome is characterized by a severe cognitive decline ending in dementia and death. MPSIII is also associated with a range of abnormal and disruptive behaviors that can include, but go well beyond, childhood noncompliance and oppositionality. The purpose of this study is to conduct a cross-sectional investigation to identify the behavioral phenotype and its neural basis in MPSIII. An overall goal of this research is to develop easily administered, sensitive and specific neurobehavioral markers to characterize the behavioral phenotype(s) of MPSIII, track their progression, and to delineate their possible neural substrates. The study looks to develop develop a sensitive and specific behavioral rating of disease progression in MPS III which can be used for clinical outcome studies. The research objectives are: Develop a measure for the use of health professionals to use in tracking MPSIII phenotypes and disease progression. Test our model of MPSIII with objectively recorded behaviors in a well-defined experimental setting. Elucidate the neural bases of MPSIII by correlating behavioral profiles with changes in brain structures through quantitative neuroimaging. Determine the relationship between the loss of cognitive functions and development of behavioral abnormalities in MPSIII. This is an observational pilot study that will enroll 45 individuals with MPS III Type A or B. Those participating in the study will be evaluated during a one-day assessment and chart review.

  Study phs001330

• Center for Common Disease Genomics [CCDG] - Autoimmune: Inflammatory Bowel Disease (IBD) Exomes and Genomes

  The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases; understanding how best to design rare variant studies for common disease; developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The overarching aim of the Inflammatory Bowel Disease (IBD) program is to define the full allelic spectrum of protein-altering variation in genes associated to IBD, and assess their role in both Crohn's Disease (CD) and Ulcerative Colitis (UC) risk. The whole genome sequencing data generated here is comprised of samples from US-based diverse populations including African American, Puerto-Rican, Caribean and Cuban origins.

  Study phs001642

• NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)

  ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID: 18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID: 20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID: 21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID: 24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252.

  Study phs001472

• Mid-pass Whole-genome Sequencing in a Malagasy Cohort Uncovers Body Composition Associations

  The majority of human genomic research studies have been conducted in European-ancestry cohorts, reducing the likelihood of detecting potentially novel and globally impactful findings. Here, we present mid-pass whole-genome sequencing data and a genome-wide association study in a cohort of 264 self-reported Malagasy individuals from three locations on the island of Madagascar. We describe genetic variation in this Malagasy cohort, providing insight into the shared and unique patterns of genetic variation across the island. We observe phenotypic variation by location, and find high rates of hypertension particularly in the Southern Highlands sampling site as well as elevated self-reported malaria prevalence in the West Coast site relative to other sites. After filtering to a subset of 214 minimally-related individuals, we find a number of genetic associations with body composition traits, including many variants that are only observed in African populations or populations with admixed African ancestry from the 1000 Genomes Project. This study highlights the importance of including diverse populations in genomic research for the potential to gain novel insights, even with small cohort sizes. This project was conducted in partnership and consultation with local stakeholders in Madagascar and serves as an example of genomic research that prioritizes community engagement and that has potential impacts on our understanding of human health and disease.

  Study EGAS50000000496

• Novel CNV contribution to schizophrenia from a genome wide study of 41,321 subjects

  Genomic copy number variants (CNVs) have been strongly implicated in the etiology schizophrenia (SCZ). However, apart from a small number of risk variants, elucidation of the CNV contribution to risk has been difficult due to the very low frequencies of risk alleles, all occurring in less than 1% of patients. We sought to address this obstacle through a collaborative effort unprecedented in psychiatry in which we applied a centralized analysis pipeline to a large SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden is observed in SCZ patients (OR=1.11, P=5.7e-15), and persists after excluding loci implicated in previous studies (OR=1.07, P=1.7e-6). CNV Burden is also enriched for genes associated with synaptic function (OR = 1.68, P = 2.8e-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3e-05). While only previously implicated loci surpass strict genome-wide testing correction, we identify “novel” CNVs (BH-FDR &lt; 0.05) that confer both protective and risk effects on SCZ and are predominantly mediated by non-allelic homologous recombination (NAHR). Our combined data find genome-wide significant support for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2.

  Study EGAS00001001960

• WES of 2 human osteosarcoma and corresponding cell lines

  Progress in the systemic control of osteosarcoma has been limited over the past decades thus indicating the urgent clinical need for the development of novel treatment strategies. Therefore, we have recently developed new preclinical models to study promising novel agents for the treatment of pediatric osteosarcoma. The checkpoint kinase (chk) inhibitor prexasertib (LY2606368) and its salt form (LSN2940930) have recently been shown to be active in adult and pediatric malignancies, including sarcoma. We have now tested the potency of prexasertib in clonogenic survival assays in two new lines of primary patient-derived osteosarcoma cells and in two established osteosarcoma cell lines as a single agent and in combination with cisplatin and the poly ADP-ribose polymerase (PARP) inhibitor talazoparib. Prexasertib alone results in strongly reduced clonogenic survival at low nanomolar concentrations and acts by affecting cell cycle progression, induction of apoptosis and induction of double-stranded DNA breakage at concentrations that are well below clinically tolerable and safe plasma concentrations. In combination with cisplatin and talazoparib, prexasertib acts in a synergistic fashion. Chk1 inhibition by prexasertib and its combination with the DNA damaging agent cisplatin and the PARP-inhibitor talazoparib thus emerges as a potential new treatment option for pediatric osteosarcoma which will now have to be tested in preclinical primary patient derived in vivo models and clinical studies.

  Study EGAS00001003923

• UK10K NEURO ASD MGAS

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The MGAS (Molecular Genetics of Autism Study) samples are from a clinical sample seen by specialists at the Maudsley hospital and who have had detailed phenotypic assessments with ADI-R and ADOS.For further information on this cohort please contact Patrick Bolton (patrick.bolton@kcl.ac.uk).

  Study EGAS00001000113

• UK10K NEURO ASD TAMPERE

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Tampere Autism sample set consists of samples from Finnish subjects with ASD (autism spectrum disorders) with IQs over 70 recruited from a clinical centre for the diagnosis and treatment of children with ASD. For further information on this cohort please contact either Terho Lehtimaki (terho.lehtimaki@uta.fi) or Kaija Puura (kaija.puura@pshp.fi).

  Study EGAS00001000115

• Methylome profiling of Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) and a patient derived cell-line model

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1 using the twist human methylome panel.

  Study EGAS50000000026

• Familial Exome Sequencing in Rare Pediatric Phenotypes

  To discover novel candidate genes associated with rare Mendelian phenotypes, we will conduct individual genomic and phenotypic characterization using genome-wide array, pedigree exome sequencing, candidate genotyping, and pertinent clinical testing to define phenotype. Pedigrees included in this submission will have a variety of clinical pathological phenotypes.

  Study phs000553

• Base modification analysis using single molecule real-time sequencing

  This dataset was generated using single-molecule real-time sequencing for both training and testing purposes. The DNA samples isolated from human buffy coats or placenta of healthy individuals (n=4,) were prepared in a way that four types of base modifications were incorporated, including unmodified controls, 5mC, 5hmC, and 6mA. The sequence data for each sample consists of subreads produced by single-molecule real-time sequencing and stored in a bam format. Details of the specific experiments conducted in this study are outlined in our manuscript.

  Dataset EGAD50000000541

• Low-coverage Single-cell Whole Genome Sequencing Data from Paired Meningioma Samples

  This dataset comprises low-coverage (~0.5X) whole genome sequencing data from 179 single cells isolated from paired meningioma samples (88 cells from initial grade II and 91 cells from recurrent grade III tumor from the same patient). The single-cell libraries were constructed using Primary Template Amplification and ResolveDNA protocol, with libraries subsequently sequenced on NextSeq 1000 using 2x150bp paired-end reads targeting 8M reads per cell. This dataset includes the sequencing data in Fastq format.

  Dataset EGAD50000001254

• WES of tumor samples from patients with renal medullary carcinoma (RMC)

  The dataset, in .bam file format, consists of whole exome sequencing (WES) data of tumors from patients (n=24) with Renal Medullary Carcinoma (RMC), generated using Illumina NovaSeq 6000 sequencing technology. DNA was extracted from FFPE solid tumor samples using the AllPrep DNA FFPE Kit (Qiagen, CA). Libraries from FFPE tissue were prepared with the SureSelect XT HS2 DNA Kit (Agilent, CA) for exome capture. The All Exon V7 exome probe set (Agilent, CA) was used for hybridization and capture of DNA.

  Dataset EGAD50000001822

• Metagenomic data of patients with bipolar disorder or schizoprhenia spectrum disorder

  Metagenomic data of stool samples from 111 patients with either bipolar disorder or schizophrenia spectrum disorder. Data includes fq.gz files, mostly 1 forward and 1 reverse read per sample. Samples analysed in multiple lanes have 4 (paired) fastq files, which will have the same patient ID (example: 048_1 and 048_2, or 088_L1 and 088_L2. DNA was extracted from using the QIAamp Fast DNA Stool Mini Kit (Qiagen) following the manufacturer’s instructions. Shotgun metagenomic sequencing was carried out using llumina Novaseq 6000.

  Dataset EGAD50000001414

• Molecular characterisation of paediatric PDX cells before and after 3D RASTRUM bioprintin

  This dataset is a part of the publication and contains source data for comparative analysis of the molecular (TSO500, RNAseq) characteristics between patient-derived xenograft (PDX) cells from high-risk paediatric neuroblastoma and sarcoma models before and after 3D bioprinting using RASTRUM Bioprinter.

  Study EGAS00001008220

• An exome sequencing pilot study of HIV elite-long term non progressors and rapid progressors

  A pilot study examining genetic determinants associated with elite long term non progression and rapid progression using exome sequencing of individuals at the extremes of the distribution of HIV control and progression. Data can only be used for HIV related research.

  Study EGAS00001000057

• Human_Evolution_3

  The mtDNA and Y chromosome of up to 15 Australian Aborigines, concentrating on individuals with indigenous lineages, will be sequenced using the standard whole-genome sequencing followed by filtering out of autosomal and X sequences, so that only mtDNA and the Y chromosome will be analysed and released.

  Study EGAS00001000315

• Australia_and_New_Guinea_haplotype_phasing_

  Whole-genome sequencing and phasing of admixed Aboriginal Australian genomes and Papua New Guinean genomes using 10x Genomics Chromium technology. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001853

• Whole-exome sequencing of the transposition of the great arteries

  Transposition of the great arteries (TGA) is one of the most severe types of congenital heart diseases. Understanding the pathogenesis of TGA is urgently needed for patient management of this severe disease. We sought to systematically examine thegenetic etiology for isolated nonsyndromic TGA using whole-exome sequencing.

  Study EGAS00001004175

• the Yemeni-Somali 5 million SNP array dataset

  The three new samples (two from Yemen and one from Somalia) that carry a maternal lineage affiliated with the Malagasy motif were assayed for genome-wide SNP genotypes using the Illumina Human Omni5 Bead Chip (Illumina), which surveys 4,284,426 single nucleotide markers regularly spaced across the genome.

  Study EGAS00001003425

• USARC 10X Genomics Single Cell DNA Sequencing Data

  We investigated the impact of ploidy heterogeneity on copy number inference at a single cell level using fluorescence-activated cell sorted (FACS) nuclei from an undifferentiated soft tissue sarcoma. FACS revealed the presence of three aberrant subpopulations, including a haploid, a near diploid and a whole genome doubled population. Once sorted, single cell nuclei underwent whole genome sequencing using the chromium CNV single cell DNA library kit (10X Genomics). We sequenced single normal nuclei (2n) and single aberrant / tumour nuclei (1n, 2n and 2n+).

  Dataset EGAD00001008668

• SNF_OLINK_20

  Matrix of normalized values from Olink assay performed on baseline BM Plasma. The Olink Immuno-Oncology multiplex proteomic Panel included 92 proteins associated with human inflammatory conditions. Data is analyzed using real-time PCR analysis software via the Ct method and Normalized Protein Expression (NPX) manager. Data were normalized using internal controls in every single sample, inter-plate controls, negative controls and a correction factor and expressed as Log2 scale, which was proportional to the protein concentration. One NPX difference equals the doubling of the protein concentration.

  Dataset EGAD00001011147

• Identification of low frequency variants associated with ulcerative colitis using whole-genome sequencing

  2000 ulcerative colitis cases drawn from the UKIBD Genetics Consortium cohort and whole-genome sequenced at 2X depth. A case control association study using control samples whole-genome sequenced by UK10K will be undertaken to identify common, low-frequency and rare variants associated with ulcerative colitis. Data will be combined with similar data across 3000 Crohn's disease cases from the same cohort to identify inflammatory bowel disease (IBD) loci and better understand the genetic differences and similarities of the two common forms of IBD.

  Dataset EGAD00001000409

• RNASeq_EGAS00001001306

  RNASeq sequencing. Each library was sequenced using TruSeq SBS Kit v3-HS, in paired-end mode with a read length of 2 × 76 bp. We generated more than 20 million paired-end reads for each sample in a fraction of a sequencing lane on HiSeq2000 (Illumina Inc.) following the manufacturer’s protocol. Image analysis, base calling and quality scoring of the run were processed using the manufacturer’s software Real Time Analysis (RTA 1.13.48) and followed by generation of FASTQ sequence files.

  Dataset EGAD00001001443

• V(D)J and 5' Gene Expression data of bone marrow cells from patients with aplastic anemia

  Viably frozen blood MNCs from 9 cGVHD patients were sorted with BD Influx Cell sorter, to enrich for CD45+ cells. Gene and V(D)J transcript profiles were studied with 10x Genomics Chromium Single Cell Immune Profiling platform. The Chromium Single Cell 5’RNAseq run and library preparation were done using the Chromium Next GEM Single Cell Immune Profiling version 1.1 chemistry. The raw data was processed using Cell Ranger v3.1 pipelines.

  Dataset EGAD00001012117

• Reference exome data for Australian Aboriginal populations from Western Australia and the Northern Territory

  Here we provide a catalogue of variants called after sequencing the exomes of 50 Aboriginal individuals from the Northern Territory (NT) of Australia and compare these to 72 previously published exomes from a Western Australian (WA) population of Martu origin. Sequence data for both NT and WA samples were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. The data is provided as 2 VCF files, one for the WA population and one for the NT population.

  Dataset EGAD00001005189

• Array-based DNA methylation analysis in blood from patients with Snijders Blok–Campeau syndrome (CHD3)

  DNA methylation array data generated using the Illumina Infinium MethylationEPIC BeadChip (v1.0 and v2.0) from whole-blood DNA of patients with Snijders Blok–Campeau syndrome (ORPHA:599082). Raw IDAT files were generated to identify differentially methylated regions in typical and atypical patients.

  Study EGAS00001008414

• Evaluation of clonal hematopoiesis regarding TP53 mutation status in 140,597 individuals

  The existence of clonal hematopoiesis, in which somatic mutations accumulate in the peripheral blood with age and expand clonally, is becoming clear, and various clinical implications are being suggested. This study analyzed clonal hematopoiesis regarding TP53 mutation status by targeted sequencing in 140,597 individuals, including those with breast cancer, gastric cancer, colorectal cancer, heart failure, stroke, etc. The clinical characteristics of clonal hematopoietic carriers were evaluated.

  Study JGAS000782