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• Effects of nucleases on cell-free extrachromosomal circular DNA

  Effects of nucleases on cell-free extrachromosomal circular DNA

  Study EGAS00001005873

• International Verapamil SR/Trandolapril [INVEST] Genes Study

  INternational VErapamil SR-Trandolapril STudy (INVEST) was a prospective, multicenter, randomized, open-label, parallel-clinical trial that evaluated blood pressure response and adverse outcomes in patients randomized to either an atenolol-based or a verapamil SR-based hypertension treatment strategy in 22,576 patients with documented coronary artery disease and hypertension (PMID: 9809930,14657064). Hydrochlorothiazide and trandolapril were added as needed to achieve BP control or end organ protection in a protocol-defined manner. Briefly, the protocol required patients to be followed up at bassline, 6, 12, 18 and 24 weeks and then every 6 months thereafter until 2 years after the last patient was enrolled. At each visit, patients had BP and heart rate measured, clinical assessment performed, and additional antihypertensive medications added as needed to meet JNC VI blood pressure goals. The primary outcome was the first occurrence of all-cause death, nonfatal myocardial infarction (MI), or nonfatal stroke (clinicaltrials.gov identifier: NCT00133692). The genetic substudy of INVEST, INVEST-GENES, collected genomic DNA samples from 5,979 INVEST study participants. INVEST-GENES samples were genotyped on the Illumina OmniExpressExome GWAS chip. This data release includes 1529 samples that passed quality control including 657 whites, 537 Hispanics and 155 blacks. Two case-control subsets were created: one for the primary outcome of all-cause death, nonfatal MI or nonfatal stroke; the other one is for new-onset diabetes. Resistant hypertension was also evaluated in 1349 participants based on the medication use and blood pressure measurements at the visit prior to experiencing study outcomes or censoring (PMID:30237584).

  Study phs002319

• Genetic Model of MS Severity Predicts Future Accumulation of Disability

  The goal of "Comprehensive Multimodal Analysis of Neuroimmunological Diseases of the CNS" is to define the pathophysiological mechanisms underlying the development of disability in immune-mediated disorders of the central nervous system (CNS) and to distinguish these from physiological (and often beneficial) responses of the human immune system to CNS injury. The long-term objective of the trial is to acquire knowledge that would allow us to therapeutically inhibit the pathogenic mechanisms and enhance repair mechanisms in immune-mediated CNS diseases, thereby minimizing the extent of CNS tissue damage and promoting recovery. To date, 460 patients with a confirmed diagnosis of multiple sclerosis (MS) have been enrolled into the natural history clinical trial. In addition to standardized clinical, functional, neuroimaging and molecular/immunological data, blood samples were also collected for genetic research. However, only 299 study participants with confirmed MS currently have whole genome sequencing data available. In addition to the genome-wide data available for the 299 MS patients, this dbGaP submission provides demographic and phenotypic information for each subject collected at various points throughout the trial. We include race and family history of MS collected at the baseline visit as well as age and measures of disease severity collected at the most recent visit. As these data were randomized into discovery and validation cohorts, we also indicate the assigned group in the phenotypic data. It is hoped that these data may be applied to the development of clinically-useful tools such as diagnostic tests and new, sensitive scales of neurological disability, disease severity and CNS tissue destruction.

  Study phs001833

• WES of melanoma tumours prior to combined immune checkpoint blockade treatment.

  Paired melanoma tumor and normal (PBMC) WES data from a cohort of 26 patients subsequently treated with combined immune checkpoint blockade.

  Dataset EGAD00001005941

• Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure (GUIDE-IT-BioLINCC)

  Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Objective: To determine whether an amino-terminal pro-B-type natriuretic peptide (NT-pro-BNP)-guided treatment strategy improves clinical outcomes vs usual care in high-risk patients with heart failure (HF) and reduced ejection fraction (HFrEF).Background: Heart failure is a common disorder. Standard treatment for HF includes diuretics to control fluid, and drugs called "neurohormonal antagonists" (such as beta-blockers and ACE-inhibitors) to help the heart work more efficiently. The natriuretic peptides, specifically NT-pro-BNP, are biomarkers that reflect HF severity and are significantly associated with adverse outcomes in HF. Smaller studies have evaluated adjusting HF therapy based on natriuretic peptide levels (“guided therapy”) with inconsistent results.Participants: A total of 894 participants were enrolled at 45 sites in the United States and Canada, with 446 randomized to the NT-pro-BNP-guided strategy treatment group and 448 randomized to the usual care treatment group.Design: GUIDE-IT was a multicenter randomized clinical trial with participants randomized to either the NT-pro-BNP-guided therapy strategy or usual care. Given the nature of the study intervention, treatment assignment was not blinded. For participants randomized to the NT-pro-BNP-guided strategy, clinicians were instructed to titrate HF therapy to target an NT-pro-BNP level After an initial visit at 2 and 6 weeks, visits occurred every 3 months throughout the remainder of the study. After therapy adjustment for HF (whether driven by NT-pro-BNP levels or clinical reasons), participants had a 2-week follow-up visit for reassessment. All participants in either group also had blinded NT-pro-BNP concentrations measured in a core laboratory at each study visit. The primary end point was the composite of time-to-first HF hospitalization or cardiovascular mortality. Secondary end points included all-cause mortality, total hospitalizations for HF, days alive and not hospitalized for cardiovascular reasons, the individual components on the primary end point, and adverse events. Conclusions: The guided strategy intervention was stopped in July of 2016 (median follow-up of 15 months) after the study met prespecified inefficacy criteria. Compared to usual care, a strategy of NT-pro-BNP-guided therapy was not more effective in improving time-to-first HF hospitalization or cardiovascular mortality in high-risk participants with HFrEF.

  Study phs003621

• Duplex sequencing of 26 genes

  Buccal samples and paired esophageal epithelium were obtained using the three sizes of swabs and endoscopic biopsy, respectively. Forty samples from 10 subjects were analyzed via duplex sequencing. This dataset contains bam files that were mapped to the GRCh37 reference genome.

  Dataset EGAD50000000998

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• Somatic mutations in twin breast cancers (2019-04-03)

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004890

• Virginia PrIMeD Study

  The goal of this study was to determine whether screening children (2-16 yrs) in pediatric waiting rooms for genetic risk of type 1 diabetes (T1D) could be applied to diverse (by geography, genetic ancestry) communities, and for those at "high genetic risk," if barriers prevent subsequent screening for presence of islet autoantibodies. A total of 3,818 children were recruited from eight general pediatric and specialty clinics across Virginia. Clinical Research Coordinators were stationed at each clinic and obtained informed consent/assent, a brief medical history, and a saliva sample for DNA extraction and determination of their genetic risk using a T1D Genetic Risk Score (T1D GRS). Children were present in the clinic for a "healthy" visit, although children with and without a history of T1D were recruited into the study. Age, sex, self-reported ancestry/race, T1D history, and other medical history information was obtained. DNA was extracted from the saliva samples and genotyping with a T1D-focused array using 74 SNPs (including 26 SNPs in the HLA region) provided data to generate a T1D GRS for each individual. Of the 3,818 children recruited, there was a slight excess of males (1,959, 51.3%), a majority of white and Hispanic/Latino ancestry (82.8%), and 91 (2.4%) with prevalent T1D. A total of 542 (14.2%) had "high T1D genetic risk" (T1D GRS > 5). Although the T1D GRS included non-HLA genetic variants, 80% of those with "high genetic risk" would have been classified using only those SNPs in the HLA region alone. Of children with "high genetic risk" and without pre-existing T1D (n=494), 7.0% (34/494) consented for islet autoantibody screening. Among children with pre-existing T1D (n=91), 52% (n=48) also had a "high genetic risk." The HLA-focused T1D GRS was not significantly associated with age at onset of T1D. Of those at high genetic risk that consented for autoantibody testing (n=34) and completed the blood collection (n=28), two (2/28, 7.1%) tested positive for multiple autoantibodies and were at significant risk of developing T1D. Follow up of 55% of parents/guardians identified 2 (of 2,096, 0.095%) participants who developed T1D, one at "high genetic risk" and one with a first-degree relative with T1D. A major factor in obtaining islet autoantibody testing was concern over SARS-Cov-2 exposure and an independent non-scheduled blood collection.Individual-level data at each SNP (genotyped and imputed) for T1D genetic risk and affiliated data are provided in dbGaP.

  Study phs003609

• PCR-free shallow whole genome sequencing for chromosomal copy number detection from plasma of cancer patients is an efficient alternative to the conventional PCR-based approach

  Somatic copy number alterations (SCNAs) can be detected in tumor cell-free DNA (cfDNA) by shallow whole genome sequencing (sWGS). Polymerase chain reaction (PCR) is typically included in library preparations, but a PCR-free method could be an effective alternative for research and diagnostics. Peripheral blood samples (n=22) were collected in EDTA-containing tubes from non-small cell lung cancer patients (n=10) and healthy donors (n=12). PCR and PCR-free library preparations underwent sWGS and the following metrics were compared: mapping quality, proportion of duplicate reads, genome coverage, sequencing read length and copy number profiles. The PCR-free method was further evaluated on archived plasma samples (n=33) of varying pre-analytical quality collected in EDTA or lithium heparin tubes. Archived samples were from acute myeloid leukaemia (n=15) and B-cell lymphoma (n=18) patients. The percentage of unique reads was significantly higher for the 22 samples analysed by PCR-free (95.7%) compared to PCR (84%). PCR-free libraries from 33 archived samples produced data of a comparable quality, with 95.4% unique reads. All other evaluated metrics were highly comparable for PCR and PCR-free library preparations. We conclude that SCNA detection can be performed by PCR-free sWGS on cfDNA from cancer patients and is feasible for diagnostic and archival plasma collected in EDTA- or lithium heparin-containing tubes. Our results pave the way for an automated cfDNA workflow for cancer plasma samples.

  Study EGAS00001004692

• Data Quality Control

  Data Quality Control High-throughput sequencing techniques have become the leading method to study, decode and discover the genomic origins of biological phenomenons. EGA provides a secure archival of such identifiable genomics data with the purpose of data-upcycling, i.e. to re-use these data for research. High-quality data standards are essential to ensure the quality and credibility of the research. Moreover, a quality check report can assure a researcher beforehand about the data that they will request access, therefore saving time and effort. The EGA has developed a File Quality Control Report (QC Report) to provide generic quality control reports for Fastq, SAM/BAM/CRAM, and VCF files deposited at EGA. This QC Report will allow users to get information regarding the files submitted within a specific dataset. The data requesters will obtain information such as the quality of reads, mapped reads, number of variants, and other features before starting the requesting process, which will save the efforts and time.Accessing file quality control reportsIn each dataset page, the user can explore the files that it contains by clicking the "files" tab. The Quality Control report of a file has two sections. The first one, contains general information about the file, such as the inferred assembly, total reads, the dataset or study where it comes from, etc. The second section contains plots that summarise interesting information about the file, for example, the base coverage distribution, base quality or mapped reads. The description of each plot is accessible by clicking the "i" button at the top-right corner of each plot box. Technical Description For analysing the fastq, SAM/BAM/CRAM and VCF files, the EGA applies a set of tools widely used in the bioinformatics community. FASTQ: FastQC, recognised as the gold standard tool by the community.Per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, sequence duplication levels, etc.SAM/BAM/CRAM: samtools, also the gold standard, generates results plots useful to get an overall idea of the quality of the file.base coverage distribution, base quality, % of mapped reads, % of both mates mapped, singletons, duplicates, etc.VCF: vcftools and bcftools, combined with a custom script to infer the genome assembly.site frequency distribution, Ts/Tv, base changes, indel distribution, etc.

  Documentation access/request-data/quality-control-reports

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  Targeted DNA sequencing of high-grade serous ovarian cancer (HGSC) tumour and normal samples from 26 patients. Following target hybrid capture of 63 genes involved in DNA repair and response to treatment with an Agilent SureSelect XT panel, sequencing libraries were generated using the SureSelect XT Low Input Target Enrichment System (Agilent) as per the manufacturer's protocol. Libraries were sequenced on an Illumina NextSeq 500 at the Peter MacCallum Cancer Centre (Melbourne, Australia).

  Study EGAS50000000146

• L1 Retrotransposon sequencing in Cocaine Use Disorder - Study 1

  Cocaine Use Disorder (CUD) is a global public health problem, with no effective pharmacotherapies. While CUD is marked by high heritability, discovery of variants associated with risk for CUD has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from medial prefrontal cortex NeuN+ neuronal nuclei from 25 CUD cases and 26 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001966

• The biology of cell-free DNA fragmentation and the roles ofDNASE1, DNASE1L3 and DFFB

  The biology of cell-free DNA fragmentation and the roles of DNASE1, DNASE1L3 and DFFB

  Study EGAS00001003514

• Study of Osteoporotic Fractures (SOF)

  The Study of Osteoporotic Fractures (SOF) is a prospective multicenter study of risk factors for vertebral and non vertebral fractures. The cohort is comprised of 9704 community-dwelling women 65 years old or older recruited from populations-based listings in four U.S. areas: Baltimore, Maryland; Minneapolis, Minnesota; Portland, Oregon; and the Monongahela Valley, Pennsylvania. Women enrolled in the study were 99% Caucasian with African American women initially excluded from the study due to their low incidence of hip fractures. (A cohort of AA women was recruited at the 6th Visit.) The SOF participants were followed up every four months by postcard or telephone to ascertain the occurrence of falls, fractures and changes in address. To date, follow-up rates have exceeded 95% for vital status and fractures. All fractures are validated by x-ray reports or in the case of most hip fractures, a review of pre-operative radiographs. Blood samples were collected in 6795 women at their Year 2 exam (Visit 2) and with written consent for use of DNA in genetic studies. Of these, we have GWAS data on 3625 Caucasian participants. As a separate study, the SOF Osteoarthritis Project was funded separately to collect data about risk factors for osteoarthritis (OA) and analyze baseline hip and hand films for the presence and severity of OA. Raw GWAS data is housed at the study's coordinating center and not released as part of the dbGaP release. The raw data can be requested from the study's coordinating center. Only QC cleaned PLINK files are available at dbGaP. Auxiliary files are also available for duplicates and HapMap participants.

  Study phs000510

• Warfarin Pharmacogenetics: Pharmacogenetic Optimization of Anticoagulant Response (POAT) and Genetic and Environmental Determinants of Warfarin Response (GEDWR)

  Although the efficacy of warfarin in the treatment and prevention of thromboembolic disorders is proven, it is vastly underutilized with difficulties in management and risk of complications being the main deterrents. Recognition of genetic regulation of warfarin response has fueled efforts to quantify this influence, but the focus has been restricted to select genes and outcomes mainly in European Americans. Race appears to influence warfarin dose requirements with African Americans requiring larger and Asians requiring lower doses compared to Europeans. This variation in dose requirement by race may at least partially be explained by genetic differences. The Genetic and Environmental Determinants of Warfarin Response (GEDWR) and the Pharmacogenetic Optimization of Anticoagulation Therapy (POAT) are prospective cohort study aimed at defining the influence of CYP2C9, VKORC1 and other genes. All patients were followed at monthly intervals from initiation of therapy. At each visit factors influencing warfarin response such as warfarin dose, INR, concurrent medications, etc. were documented. Information on concurrent medications was updated at every clinic visit by self-report and verified by medical record review. Concomitant use of drugs such as drugs that alter warfarin pharmacokinetics, including CYP2C9 inhibitors (e.g., amiodarone), and pharmacodynamics such as antiplatelet agents (e.g. aspirin). Although the a priori hypothesis focused on the candidate-gene approach, with the recognition that the candidate-gene approach is bound by the assumption that our knowledge of genetic influences on warfarin response is complete. Among African Americans known variation in candidate genes (CYP2C9 and VKORC1) explain substantially less variability in warfarin dose requirements. Therefore a genome-wide association study (GWAS) was conducted on African American patients to identify novel variants associated with warfarin dose requirements.

  Study phs000708

• Analysis of cell type contributions to cell free DNA in health and disease.

  This study looks at cell type contributions to cell free DNA in health and disease.

  Study EGAS50000000178

• Chromatin accessibility in human monocyte differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 26 samples.

  Dataset EGAD00001006601

• ICGC PCAWG Dataset: ORCA-IN_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ORCA-IN.

  Dataset EGAD00001002120

• Data files for PCGP SJACT RNASEQ

  This dataset contains RNA-Seq files for the SJACT cohort associated with the paper "Genetic landscape of pediatric Adrenocortical Tumor". In this paper, we analyse 37 adrenocortical tumours (ACTs) by whole-genome, whole-exome and/or transcriptome sequencing.

  Dataset EGAD00001002680

• Large Cancer Fingerprint Screening for Detection of Minimal Residual Disease.

  We describe an approach for large cancer fingerprint screening and its application to cell-free DNA from patients with cancer. Our approach involves tracking somatic mutations identified from patients' tumor biopsies, in the cell-free DNA from a blood draw.

  Study phs001977

• Methylation sequencing of CSF-derived cell free DNA

  We sequenced and enzymatically converted cell free DNA from 268 samples from 157 patients with brain tumors and 58 control CSF patients.

  Study EGAS50000001365

• Sequencing of cell-free DNA from breast cancer patients

  To assess the utility of high coverage whole genome sequencing analysis of cell-free DNA to detect tumour-specific genomic changes

  Study EGAS00001004960

• Exome Sequencing of a family with thrombocytopenia, red cell macrocytosis, and lymphoblastic leukemia predisposition

  A family with a history of bleeding, variable thrombocytopenia, red cell macrocytosis and two cases of pre B-cell acute lymphoblastic leukemia was studied in a single visit. The family was assessed for bleeding history using a bleeding questionnaire. Additionally, complete blood counts were measured and whole blood was collected from five affected individuals and three unaffected individuals for DNA extraction and whole exome sequencing. The goal of this study is to determine the genetic cause of thrombocytopenia, red cell macrocytosis, and predisposition to leukemia in a family. It is hoped that the information obtained from this study will help researchers understand the genetic and molecular basis of platelet and red cell production, as well as leukemia predisposition.

  Study phs000873

• The Cancer Dependency Map (DepMap)

  The Cancer Dependency Map (DepMap) aims to accelerate precision cancer medicine by creating a comprehensive map of tumor vulnerabilities. The DepMap project genomically profiles a wide range of cancer models and characterizes them for their sensitivity to genetic and compound perturbations. The data is computationally analyzed to create a systematic overview of the genetic dependencies and compound sensitivities of cancer types and the predictive biomarkers that point to patient populations most likely to benefit from targeting of these vulnerabilities. The DepMap public portal has become a comprehensive resource to identify cancer vulnerabilities by providing datasets at scale, cutting-edge computational tools, and sophisticated visualization tools that together have accelerated the discovery of novel targets and biomarkers. Please visit Depmap.org to access the public portal.

  Study phs003444

• Methylation and nucleosome occupancy studies on cell-free DNA using enzymatic cytosine conversion

  Raw sequencing data (PE, fastq.gz) from NovaSeq 6000 sequencing runs of: 1. Blood-derived cell-free DNA from six healthy controls, enzymatic cytosine conversion (between 1 and 3 replicates each) 2. Urine-derived cell-free DNA from three healthy controls, enzymatic cytosine conversion (between 1 and 3 replicates each) 3. Blood-derived cell-free DNA from six patients with acute or chronic kidney disease with/without other relevant organ dysfunction, enzymatic cytosine conversion (between 1 and 3 replicates each) 4. Urine-derived cell-free DNA from three patients with acute kidney disease, enzymatic cytosine conversion (between 1 and 3 replicates each) 5. Blood-derived cell-free DNA from three healthy controls, bisulfite cytosine conversion (single datasets) 6. Conventional whole-genome sequencing on genomic DNA of two healthy kidney donors for two of the studied patients (single datasets).

  Dataset EGAD00001006072

• RNA sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  RNA-seq for 26 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study, and 32 samples from a previously uploaded dataset.

  Dataset EGAD50000001365

• Neuroblastoma_MP-PCR_MultiplexPCR_TargetedSequencing_BAMs

  This dataset contains raw sequencing data (BAM/BAI files) generated from human neuroblastoma patient samples. The data were produced using targeted high-throughput next-generation sequencing and are intended to support genomic analyses of tumor-associated alterations. All files are provided under controlled access in accordance with EGA data protection requirements.

  Dataset EGAD50000002260

• Mutation analysis of 17 genes in plasma DNA of CRC patients using the AVENIO ctDNA Targeted Kit

  Mutation analysis of 17 genes (ALK, APC, BRAF, BRCA1, BRCA2, DPYD, EGFR, ERBB2, KIT, KRAS, MET, NRAS, PDGFRA, RET, ROS1, TP53, UGT1A1) in plasma DNA of CRC patients using the AVENIO ctDNA Targeted Kit.

  Dataset EGAD00001006103

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• Verification of BCR reconstruction from single-cell RNA-seq using BraCeR

  This dataset was made to verify the computational reconstruction of B cell reseptors from single-cell RNA-seq using BraCeR. The dataset contains BCR-derived reads from single-cell RNA-seq from 13 cells using the Smart-seq2 protocol, as well as targeted BCR-sequencing data from the same cells.

  Dataset EGAD00001004199

• Dedifferentiated Melanoma (2021-02-02)

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006931

• Targeted sequencing of cell free DNA samples from oligometastatic colorectal cancer patients

  In order to discover specific mutations that correlate with prognosis, target sequencing was performed using cell-free DNA samples from oligometastatic colorectal cancer patients.

  Study JGAS000196

• Pomalidomide for the Treatment of Bleeding in HHT (PATH-HHT)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine efficacy (reduction in severity of epistaxis), tolerability, and improvement in quality of life of pomalidomide compared to placebo after 24 weeks of treatment.Background: This study addresses the efficacy of pomalidomide in the treatment of epistaxis in patients with Hereditary Hemorrhagic Telangiectasia (HHT) who have anemia and/or require blood transfusion or iron infusion for treatment of bleeding-induced anemia and iron deficiency. HHT (also known as Osler-Weber-Rendu disease) is an inherited bleeding disorder. Over 95% of patients develop recurrent epistaxis, which may be severe and result in chronic anemia, need for iron infusions and blood transfusions, substantial psychiatric comorbidity (including depression and post-traumatic stress disorder) and reduction in health-related quality of life (HRQoL). HHT is clinically diagnosed using the Curacao criteria, which consists of 1) spontaneous and recurrent epistaxis, 2) telangiectasias at characteristic sites, 3) visceral arteriovenous malformations (AVMs) or telangiectasias, and 4) a first degree relative with HHT (inheritance is usually autosomal dominant). Patients with three criteria are considered to have definite HHT, and those with 2 criteria probable HHT. HHT affects approximately 1 in 3,800 individuals. Significant manifestations of HHT often do not appear until the third or fourth decades, sometimes later.Participants: 144 patients from 11 clinical centers were enrolled.Design: This is a multi-center, double blind, randomized placebo-controlled trial that investigated the efficacy and safety of pomalidomide in patients with HHT and chronic epistaxis leading to iron-deficiency anemia or requiring intravenous iron infusions or blood transfusion.Screening evaluation included the Epistaxis Severity Score (ESS) with three-month recall, which reflected the patient's history of epistaxis and bleeding over the prior three months, as well as detailed review of iron infusion and red cell transfusion over the preceding six months. Eligible patients were provided a diary to record the duration of each epistaxis event that occurred during the 4 weeks prior to the baseline visit, and then returned for the baseline randomization visit, at which time patients underwent genetic testing, if this had not been previously performed, and completed an ESS with 4-week recall and quality of life assessments. Patients were randomized 2:1, stratified by study site, to either pomalidomide 4 mg/day or matching placebo during each of six 28 day cycles (24 weeks). Patients were seen every four weeks during treatment, and at a 4-week post-treatment follow-up visit to measure the ESS (with 4-week recall), laboratory assessments including iron stores and need for iron infusion, CBC, and metabolic profile. Patients were assessed for adverse events (AE) throughout the study. Treatment dosage could be reduced, or temporarily or permanently discontinued following AE-specific guidelines related to fatigue, cytopenias or other toxicities.Quality of life assessments were completed at baseline, and the 12- and 24-week visits, and the 4-week post-treatment follow-up visit using validated NIH instruments of 1) Neuro-QOL satisfaction with social roles and activities, 2) PROMIS emotional distress – depression, and 3) PROMIS fatigue, and the HHT-specific quality of life instrument developed specifically for this study. The effect of pomalidomide on duration of epistaxis was assessed via diary between weeks 8-12, 20-24 and the 4-week post-treatment period.Conclusions: Among patients with HHT, pomalidomide treatment resulted in a significant, clinically relevant reduction in epistaxis severity. No unexpected safety signals were identified (Al-Samkari et al., 2024; PMID: 39292928)

  Study phs003948

• Long-read sequencing for cell-free DNA analysis (human)

  In this study, we compared the two long-read sequencing platforms, namely the single-molecule real-time sequencing by Pacific Biosciences and nanopore sequencing by Oxford Nanopore Technologies, for the analysis of cell-free DNA from plasma. Cell-free DNA from plasma samples of 31 pregnant women at different trimesters, 6 hepatitis B carriers, and 8 patients with hepatocellular carcinoma were sequenced with the two platforms.

  Study EGAS00001006328

• Characterization of the molecular signature of human monocytes in aging and myelodysplastic syndrome

  Deep immunophenotypic profiling of peripheral blood immune cells from young and older control subjects as well as patients with MDS was initially performed, using mass cytometry to identify monocyte subpopulations. Abundance of monocyte subpopulations separated the samples from patients with MDS from elderly control subjects was identified. Therefore, targeted immunophenotyping of monocytes was also performed with flow cytometry and RNA sequencing from isolated CD14+ peripheral blood longitudinally in 26 subjects, six young healthy individuals, nine older healthy individuals and eleven patients with MDS.

  Study EGAS00001007676

• Datasets of RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  RNA-seq analyses were performed on tumor tissue samples of 115 advanced clear cell renal cell carcinoma patients who participated in the NIVOREN GETUG-AFU-26 trial. The samples were obtained prior to treatment initiation. RNA-seq was performed to evaluate previously published gene expression signatures. These included: the IMmotion T effector (CD8A, EOMES, PRF1, IFNG and CD274) and the IMmotion Myeloid (IL-6, CXCL1, CXCL2, CXCL3, CXCL8, and PTGS2) gene signatures represent gene expression patterns associated with T effector cells and myeloid cells, respectively, while JAVELIN Renal 101 Immuno (T-cell receptor signaling: CD3G, CD3E, CD8B, THEMIS, TRAT1, GRAP2, CD247; T-cell activation, proliferation, and differentiation: CD2, CD96, PRF1, CD6, IL7R, ITK, GPR18, EOMES, SIT1, NLRC3; Natural killer cell mediated cytotoxicity: D2, CD96, PRF1, CD244, KLRD1, SH2D1A; Chemokine: CCL5, XCL2; and Other immune response genes: CST7, GFI1, KCNA3, PSTPIP1) represents gene expression patterns associated with both innate and adaptive immune response.

  Dataset EGAD50000001541

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The current study investigates biomarkers of response to anti-EGFR therapies in gastro-esophageal cancer. Whole exome sequencing was performed on 26 tumors to explore potential factors influencing treatment outcomes. As part of the analysis, somatic mutations in EGFR, ERBB2, and key downstream signaling genes (KRAS and PIK3CA) were examined to exclude the presence of known mutations conferring sensitivity/resistance. The study aims to contribute to the identification of patients who may benefit from lower-toxicity regimens, improving treatment personalization and minimizing adverse effects.

  Study EGAS50000000966

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• Tumor-associated preferred end coordinates and somatic variants as signatures of circulating tumor DNA

  Cell-free DNA fragmentation is a nonrandom process. We showed that cell-free DNA fragments with ends at certain genomic coordinates had higher likelihoods of being derived from hepatocellular carcinoma. Other coordinates were associated with cell-free DNA molecules originating from the liver. Quantitative assessment of cell-free DNA molecules bearing these respective groups of end signatures correlated with the amounts of tumor-derived or liver-derived DNA in plasma. There were millions of tumor-associated plasma DNA end coordinates across the genome. Due to their high prevalence, they were more readily detectable than somatic mutations as a cancer signature in plasma. Hence, detection of tumor-associated plasma DNA ends may offer a cost-effective means of capturing evidence for the presence of cancer through liquid biopsy assessment.

  Study EGAS00001003160

• 36 mouse plasma cell-free DNA cases

  36 mouse plasma cell-free DNA cases

  Dataset EGAD00001008810

• PyEGA3 download client

  PyEGA3 Checks prior to download - Is the dataset available for download? Most datasets are available using the PyEGA3 Download client, except for specific legacy datasets. For these ones, refer to Live Outbox distribution, an alternative way to download these datasets.If the dataset you've been granted access to begins with the ID EGAD5XXXXXXX, please refer to the Live Outbox distribution. If the dataset you have been granted access to contains encrypted data (filename ending in .gpg), contact EGA Helpdesk for detailed information on how to download these files.General Information The PyEGA3 download client is available at its GitHub repository. In its README you will find a step by step guide on how to use it to download files you have been granted access to. PyEGA3 implements the GA4GH-compliant HTSGET protocol supporting requests over genomic ranges. This enables the download of specific regions of interest rather than the entire file. HTSGET is not possible for all the files held by EGA: if the dataset does not contain index files (e.g. filename ending in *.crai), then genomic range requests cannot be performed. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Check out our video tutorial! Frequently Asked Questions General questions How do I download the datasets to which I have been granted access? After setting up your EGA download account, you can proceed to download using the EGA download client – PyEGA3. The pyEGA3 download client is a python-based tool for viewing and downloading files from authorised EGA datasets. This download client is continuously being developed for more user-friendly download experiences. Can I download the dataset’s metadata via the download client? No, the download client cannot be used to download metadata. Registered EGA users can download metadata of an authorised dataset by logging into the EGA webpage and navigating to the dataset of choice. Approximately two thirds down the page you will find the option to download the metadata as a zip file. How do I download large datasets as quickly as possible? The main EGA download client is pyEGA3 download client, a python-based tool for viewing and downloading files from authorised EGA datasets.We could exceptionally consider the option of an Aspera download for users experiencing very slow download rates or facing particular issues.Contact the EGA Helpdesk for further information. Pre-requirement and Installation What are the major requirements for the PyEGA3 download client installation and usage? The PyEGA3 client is compatible with any OS with Python 3.6+ installed. The client requires a connection to the internet, sufficient space on the destination drive, and the EGA download account credentials. Where can I find the PyEGA3 download client installation and download instructions? We strongly recommend checking our video tutorial demonstrating the usage of PyEGA3 from installation to file download. More detailed information is available at PyEGA3 GitHub. What ports are required for the PyEGA3 download client to function? PyEGA3 makes HTTPS calls to the EGA Data API (https://ega.ebi.ac.uk:8443). This port 8443 must be reachable from the location where PyEGA3 is executed to avoid timeouts. PyEGA3 download client How to update the PyEGA3 download client to be on the latest version? Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 --upgrade I do not have an active EGA account. Can I test the download with the PyEGA3 download client? An EGA download test account (ega-test-data@ebi.ac.uk) has been created for troubleshooting and training purposes. The test account does not require an EGA username and password because it contains publicly accessible files from the 1000 Genomes Project. More information about the use of this account and log in details are available at pyEGA3. I lost my connection while the download was in progress. Does this mean that I have to download the file again from the start? The PyEGA3 download client supports automatic resumption of downloads. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the resume feature, downloads will automatically resume if you encounter any errors or if the connection is interrupted. How can I improve the overall download speed of the PyEGA3 download client? Download speeds can be optimised using the --connections parameter which will parallelise download at the file level. If the --connections parameter is provided, all files >100Mb will be downloaded using the specified number of parallel connections. It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Why is my file taking a long time to be saved? Please note that when a file is being saved, it goes through two processes. First, the downloaded file "chunks" are pieced back together to reconstruct the original file. Secondly, PyEGA3 calculates the checksum of the file to confirm that the file was downloaded successfully. Larger files will take more time to reconstruct and validate the checksum. Why is the HTSGET protocol not working with my dataset of interest? PyEGA3 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file, saving both time and storage space. Please note that in order for the genomic range requests to work for a BAM, CRAM or VCF file there must be an associated BAI, CRAI or TBI file, respectively. If the dataset does not contain these index files then genomic range requests cannot be performed. After download Do I need to decrypt data files downloaded through the pyEGA3 download client? Files are transferred over secure HTTPS connections and received unencrypted, thus there is no need for decryption after data download. What is the purpose of an MD5 file? After the download completes, file integrity is verified using checksums. The PyEGA3 download client automatically verifies each file’s unencrypted md5 after download to ensure that the file was downloaded correctly from the EGA. Errors Why do I get a “400 Client Error” while trying to access the download client? Ensure that your credentials are formatted correctly. Please contact the EGA Helpdesk if you are unsure about your account’s username (i.e. your email address). Why do I get a “500 Server Error”? It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Otherwise, 500 server errors are internal server errors from EGA’s end. Retry after some time and, if the 500 error persists: check our homepage or Twitter for any outage information or report it to EGA Helpdesk. Why do I get a “slice error”? This type of error occurs when one slice download was prematurely interrupted. Please re-start the same download. The download client will pick up any partial download and download any missing slices. Why do I get the error “Dataset' EGADXXXXXXXXXXX' is not in the list of your authorised datasets”? Please note that the data access was given to the email (username) provided to the Data Access Committee (DAC) in your official request. Therefore, you shall check that the account that you are using is the same one that you sent to the DAC. Why do I get “ERROR:root:Failed to obtain IP address”? This might mean that the connection ports are blocked. Check that the port 8443 is reachable.In case the port is reachable and the error persists, please try to modify the file pyega3.py on line 44 in the python module installation: Replace endpoint = 'https://ipinfo.io/json' with endpoint = 'https://api.myip.com' Why do I get the error “Invalid username, password or secret key - please check and retry”? Make sure that you are using the correct credentials (username and password) and there is no typo. Contact EGA Helpdesk if the problem persists.

  Documentation access/download/files/pyega3

• DAC-2020-03-26-Lemola (DAC-039))

  This is only the location. For the raw data and any check if the dataset may be relevant please refer to the Harvard Dataverse (https://dataverse.harvard.edu/dataverse/lemola).

  Study EGAS50000000635

• Frequent germline mutations of HAVCR2 in sporadic subcutaneous panniculitis-like T-cell lymphoma.

  Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of peripheral T-cell lymphoma affecting younger cases and associated with hemophagocytic lymphohistiocytosis. To clarify the molecular pathogenesis of SPTCL, we analyzed paired tumor and germline DNAs from 13 patients by whole exome sequencing.

  Dataset EGAD00001004795

• Single cell RNA sequencing of colorectal cancer patients (KUL5)

  All libraries were sequenced on Illumina NextSeq or NovaSeq6000 until sufficient saturation was reached.

  Dataset EGAD00001008585

• Clinical utility of combined low-pass whole genome and targeted sequencing in liquid biopsies for diagnosis and monitoring of pediatric solid tumors

  Low-pass whole genome sequencing samples from pediatric solid tumor patients who are deceased

  Dataset EGAD00001009972

• Whole Exome and Target Sequencing Data in 75 Samples from 5 Hepatocellular Carcinoma Patients.

  Whole Exome and Target Sequencing Data in 75 Samples from 5 Hepatocellular Carcinoma Patients. The sequencing was performed by Illumina HiSeq 4000. Background and aims: Intratumoral heterogeneity (ITH) challenges identifying mutations with target therapy potential whereas circulating cell-free DNAs (cfDNAs) could reflect nearly the entire mutation spectrum in given tumors. We investigated how to minimize the limit of ITH for profiling hepatocellular carcinoma (HCC).Methods: Thirty-two multi-regional HCC samples from five patients were subjected to whole exome sequencing (WES) and targeted deep sequencing (TDS). ITH extent was measured by the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Matched cfDNAs were also analyzed by WES and TDS. Profiling efficiencies of single tumor specimen and cfDNA were compared and the one better depicted mutational landscape was selected to screen therapeutic targets.Results: We found variable extents of ITH in HCCs and observed branched and parallel evolution patterns. ITH level decreased at higher sequencing depth of TDS than that measured by WES (28.1% vs 34.9%, P < 0.01) but it remained unchanged upon additional samples analyzed. TDS of single tumor specimen detected an average of 70% the total mutations in HCC. Although more mutations were detected in cfDNA under TDS than WES, an average of 47.2% total HCC mutations uncovered by cfDNA suggested tissue outperform cfDNA and the latter may serve as alternative in profiling HCC genome. Consequently, TDS of single tumor tissue in 66 patients and cfDNAs in four unresectable HCCs identified 38.6% (26/66 and 1/4) patients bearing therapeutic targets.Conclusions: TDS of single tumor specimen could largely circumvent ITH to uncover mutations indicative of target therapy in HCC.

  Dataset EGAD00001003278

• 5 human plasma cell-free DNA cases (BS-seq)

  5 human plasma cell-free DNA cases (BS-seq)

  Dataset EGAD00001008809

• Longitudinal Study of Urea Cycle Disorders

  Individuals with Urea Cycle Disorders (UCD) cannot remove ammonia, a waste product, from the blood. The purpose of this study is to conduct a longitudinal investigation of the natural history, morbidity, and mortality in people with UCD. This study will look at how people with a UCD grow and develop over time and how often they get sick. The research questions are: What is the prevalence of specific morbid indicators of disease severity, including hyperammonemia, developmental disabilities, and various long-term kidney and liver effects? What is the fatality rate associated with the various forms of UCD? What are the correlations between various biomarkers and disease severity and progression? What is the safety and efficacy of currently used and new UCD therapies? This is a longitudinal study of individuals with urea cycle disorders. Those participating in this study will be evaluated every three to twelve months, depending age and time of diagnosis. Participants two years of age and younger that were diagnosed with UCD within the first four weeks of life will be evaluated every three months. Those who are over two years of age or were diagnosed after four weeks of age will be evaluated every six months. Participants older than 18 years of age will be evaluated once every year.

  Study phs000577

• Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA.

  3784 whole genome sequencing bam files were generated from plasma cell-free DNA of healthy individuals and patients with cancer. Paired reads were mapped to hg19 human reference genome.

  Study EGAS00001006553