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• TIRE-seq_PDN

  TIRE-seq is a novel RNA sequencing method that integrates mRNA purification directly into library preparation, eliminating separate RNA extraction. The technique demonstrated utility across three biological applications, including capturing transcriptional changes in human T cells, identifying genes driving murine dendritic cell differentiation, and analyzing the dose-response effects of temozolomide on patient-derived neurospheres. With its simplified approach and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies.

  Dataset EGAD50000001261

• MethylScan data from tissue samples

  Raw data (fastq files) for tumor/normal paired samples (378 samples in total; 78, 58, 29, 24 pairs from liver, lung, ovary, and stomach cancer patients, respectively) profiled with the MethylScan assay, a low cost assay for profiling methylation. The MethylScan assay is designed for cfDNA methylome sequencing that enriches for the disease-associated DNA by depleting background signal. For solid tissues, the assay was performed without the MSRE digestion step.

  Dataset EGAD00001015685

• MYOSEQ project

  The MYOSEQ project focuses on the application of next generation sequencing, in particular whole exome sequencing (WES), in a large cohort of patients with unexplained limb‐girdle weakness (LGW). Focusing on undiagnosed patients with a clearly defined clinical phenotype enables increased diagnostic rates for known genes (in particular Pompe disease, GNE related pathologies and other known LGMD subtypes) in this cohort, while the use of WES provides scope both for new gene discovery and for additional research into disease modifiers and genotype‐phenotype correlation with substantial cost effectiveness. The LGW patient cohort was collated by Newcastle University in collaboration with clinical centers across Europe. The sequencing was performed at the Broad Institute and jointly analyzed with Newcastle University.

  Study EGAS00001002069

• Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia - Acute myeloid leukemia

  The advent of high-throughput next generation sequencing (NGS) technologies that are revolutionizing genomics and transcriptomics by providing a single base resolution tool for a unified deep analysis of diseases complexity allows a fast and cost-efficient fine-scale assessment of the genetic variability hidden within cohorts of patients affected by the same leukemia. That being so, by potentially highlighting inter-individual differences that may play a role in the differential success of diverse therapeutic interventions, they promise to be crucial for selecting the most appropriate medical treatments. The project aims at the identification of novel prognostic biomarkers for acute myeloid leukemia (AML) and studied the molecular differences between aneuploid and euploid AML.

  Study EGAS00001005464

• Discordant_Monozygotic_Twins_ALS (Epigenetics)

  We conducted a multi-omics study on a monozygotic twin pair discordant for amyotrophic lateral sclerosis. Data refers to 7 samples that are technical replicates from biological samples collected from the twins at two different time points (T1 and T2).

  Dataset EGAD00010002716

• Clinical and ctDNA data for IMpassion031

  Clinical and ctDNA data for IMpassion031, including survival, response, and ctDNA data from baseline through post-surgery time points. 222 samples run on Signatera assay. File type is csv.

  Dataset EGAD50000001420

• Longitudinal RNA-seq in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Dataset EGAD00001002068

• 5hmC enrichment in human monocyte differentiation

  This dataset consists of 5hmC capture-seq data from human monocytes, monocyte-derived dendritic cells. It includes two biological replicates and three time points. Including controls, the dataset comprises 10 samples in total.

  Dataset EGAD00001006603

• 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

• WES dataset of a TIL-ACT metastatic melanoma cohort

  Whole-exome sequencing (WES) data from 13 patients with metastatic melanoma in a TIL-ACT cohort, generated to characterize tumor genomics and neoantigen landscapes relevant to adoptive T cell therapy.

  Dataset EGAD50000001731

• alopecia areata

  exome sequencing files from 25 alopecia areata samples from spain.

  Dataset EGAD00001006370

• Longitudinal Transcriptomic Profiling of Endothelial Progenitor Cells in Post-COVID-19 Patients: Insights at 3 and 6-Months Post-SARS-CoV-2 Infection

  Bulk RNA-sequencing analysis of endothelial cells isolated from post-COVID patients at 3 and 6 months post-infection, alongside healthy controls. This study aims to identify differentially expressed genes in endothelial cells from post-COVID patients—at both 3- and 6-month time points—compared to those from healthy individuals. The objective is to uncover upregulated and downregulated pathways potentially associated with long-term consequences of SARS-CoV-2 infection.

  Study EGAS50000000993

• Impact of allogeneic umbilical-cord derived mesenchymal stromal cells on B-cell scRNAseq in patients with systemic lupus erythematosus

  The impact of MSC(UC) on peripheral B cells from Systemic Lupus Erythematosus (SLE) patients was studied by 10X scRNAseq. This scRNAseq study encompassed 3 SLE patients at 3 time points: before or after (1 month, and 3 months) MSC injection in order to analyze B cell subsets and their DEG. The aim of this study was to observe the potential changes of B cell subsets after MSC(UC) injection in SLE patients.

  Study EGAS50000000325

• The Jerusalem Perinatal Study (JPS) aimed to examine the developmental origins of cardiometabolic risk.

  The Jerusalem Perinatal Study (JPS) aimed to examine the developmental origins of cardiometabolic risk and explore the mechanisms underlying the associations between perinatal characteristics and the development of risk for adult chronic disease. In other words, the cohort has enabled the examination of associations between maternal and paternal characteristics with cardiometabolic risk variables in offspring at various points in the life course, as well as the effect of longitudinal changes in characteristics in both parents and offspring.

  Study EGAS00001004075

• COVID_19_Challenge_Project_Single_Cell_Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection

  Study EGAS00001005696

• Exome sequencing of samples taken at multipl time points to monitor therapy response in AML

  As part of our individualized systems medicine program, personalized treatment options are identified and administered to chemorefractory AML patients based on exome sequencing and ex-vivo drug sensitivity and resistance testing data. In this study, we developed this approach further to take into account clonal heterogeneity and analyzed responses of 13 AML patients to chemotherapy and six patients to targeted treatments by using exome and ultra-deep amplicon resequencing. The data submitted includes fastq files from exome sequencing of multiple time-point samples collected from the 13 patients. In this study we identified rare subclonal variants present at diagnosis or later relapse samples and developed a correlation-based method to compare subclonal responses in serial samples across multiple time-points. Significant subclone-specific responses were observed subsequent to chemotherapy and specifically to targeted therapy in five patients.

  Study EGAS00001001948

• Single-cell RNA sequence analysis of iPS cell-derived cardiomyocytes treated with S-RBD-sfGFP or GFP

  To determine the transcriptional response in human cardiomyocytes treated with SARS-CoV-2 spike receptor-binding domain (S-RBD-sfGFP), human cardiomyocytes differentiated from induced pluripotent stem cells (iPSC-CMs) were replated on day 21 after differentiation and treated with S-RBD-sfGFP or control-GFP for 48 hours on day 26-28. iPSC-CMs were dissociated and the single cell suspension was analyzed by single cell RNA-sequence.

  Study JGAS000620

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

  Deposited here are whole-genome sequencing data for 26 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence coverage is 118x for DCIS samples and 41x for matched-normals. Matched-normal samples are from blood. Sequencing was performed on an Illumina HiseqX. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002237

• RNA-Sequencing and Somatic Mutation Status of Adrenocortical Tumors: Novel Pathogenetic Insights

  To investigate the relationship between transcriptome profile and genetic background in a large series of adrenocortical tumors and to identify new potential pathogenetic mechanisms, we performed transcriptome profiling by high-throughput sequencing. We collected snap-frozen tissue from patients with adrenocortical tumors (n = 59) with known genetic background: 26 adenomas with Cushing syndrome, 17 adenomas with mild autonomous cortisol secretion, 9 endocrine-inactive adenomas, 7 adrenocortical carcinomas. Additionally, we sequenced 4 control samples.

  Study EGAS00001004533

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• Sequencing data for oesophageal and related samples - Abujudeh et al (WGS, fastSeq)

  Data supporting: "Low-cost and clinically applicable copy number profiling using repeat DNA." Abujudeh et al. DNA WGS (BAM files) DNA fastSeq (fastq files) Tumours, Barrett's, normals.

  Dataset EGAD00001004289

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): A Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI). Due to additional sharing restrictions, data from one site can be found in phs003094.

  Study phs003066

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): a Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study - for Samples Collected at Johns Hopkins

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI).The larger dataset for this study can be found in dbGaP study phs003066.

  Study phs003094

• Next Generation Mendelian Genetics: Malignant Hyperthermia

  Malignant hyperthermia (MH) is a genetic disorder that causes a profound metabolic derangement following exposure to certain anesthetics. While approximately half of all cases are associated with ryanodine receptor-1 gene (RYR1) mutations, many cases have an unknown genetic cause. We sought to identify rare variants in novel MH candidate genes by sequencing the protein-coding regions of the genomes of individuals whose disease was either ruled in or out by the gold-standard diagnostic test. We also carefully selected individuals from well-characterized families to use gene-sharing information and maximize efficiency in the study design. Exome sequencing has helped identify the causes of over a dozen Mendelian disorders, has high power at low sample sizes, and is cost-efficient compared to whole-genome sequencing.

  Study phs000405