14423 results for ""Pennsylvania+German"+ACS+study+'Socius'+open+access"

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• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Study EGAS00001006935

• Whole Genome Sequence and RNASeq Samples for Lung Cancer

  Short Read Whole Genome Sequence and RNASeq Samples for Lung Cancer

  Study EGAS00001007832

• RNAseq sample

  RNAseq sample used in study titled "Immune-awakening revealed by peripheral T cell dynamics after one cycle of immunotherapy".

  Dataset EGAD00001005747

• Reference epigenome Fat-adipocyte04 mRNA-Seq data generated from KEP study

  Fat-adipocyte04 mRNA-Seq paired end data

  Dataset EGAD00001007158

• Reference epigenome Pancreas-Islet08 mRNA-Seq data generated from KEP study

  Pancreas-Islet08 mRNA-Seq paired end data

  Dataset EGAD00001007168

• Reference epigenome Islet-derived-iPSC01 WGBS data generated from KEP study

  Islet-derived-iPSC01 WGBS paired end data

  Dataset EGAD00001007144

• Reference epigenome Islet-derived-iPSC02 WGBS data generated from KEP study

  Islet-derived-iPSC02 WGBS paired end data

  Dataset EGAD00001007145

• Reference epigenome Fat-adipocyte03 mRNA-Seq data generated from KEP study

  Fat-adipocyte03 mRNA-Seq paired end data

  Dataset EGAD00001007157

• Reference epigenome Fat-adipocyte05 mRNA-Seq data generated from KEP study

  Fat-adipocyte05 mRNA-Seq paired end data

  Dataset EGAD00001007159

• Reference epigenome Islet-derived-MSC04 WGBS data generated from KEP study

  Islet-derived-MSC04 WGBS paired end data

  Dataset EGAD00001007143

• Reference epigenome Islet-derived_MSC06 mRNA-Seq data generated from KEP study

  Islet-derived_MSC06 mRNA-Seq paired end data

  Dataset EGAD00001007878

• Reference epigenome Islet-derived-MSC01 WGBS data generated from KEP study

  Islet-derived-MSC01 WGBS paired end data

  Dataset EGAD00001007140

• Reference epigenome SMC05 h3k9me3 ChIP-Seq data generated from KEP study

  SMC05 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007336

• Reference epigenome Islet-derived-MSC02 WGBS data generated from KEP study

  Islet-derived-MSC02 WGBS paired end data

  Dataset EGAD00001007141

• Reference epigenome Pancreas-Islet07 mRNA-Seq data generated from KEP study

  Pancreas-Islet07 mRNA-Seq paired end data

  Dataset EGAD00001007167

• Reference epigenome Pancreas-Islet06 mRNA-Seq data generated from KEP study

  Pancreas-Islet06 mRNA-Seq paired end data

  Dataset EGAD00001007166

• Reference epigenome SMC01 h3k4me3 ChIP-Seq data generated from KEP study

  SMC01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007311

• PRDM13 exome sequencing set

  Exome sequencing study on 4 individuals from a pedigree with CHH and cerebellar hypoplasia.

  Dataset EGAD00001008420

• Reference epigenome OB56_N_PreA_smRNA-Seq data generated from KEP study

  A OB56_N_PreA_smRNA-Seq single end data for Preadipocytes(fat)

  Dataset EGAD00001003495

• Reference epigenome IPS02_N_NPC_WGBS data generated from KEP study

  A IPS02_N_NPC_WGBS paired end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003474

• Reference epigenome IPS03_N_ENeuron_WGBS data generated from KEP study

  A IPS03_N_ENeuron_WGBS paired end data for Early neuron cells(Tuj1)

  Dataset EGAD00001003475

• Reference epigenome OB57_D_PreA_mRNA-Seq data generated from KEP study

  A OB57_D_PreA_mRNA-Seq paired end data for Preadipocyte(fat)

  Dataset EGAD00001003487

• Reference epigenome CKD25_C_Podo_smRNA-Seq data generated from KEP study

  A CKD25_C_Podo_smRNA-Seq single end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003499

• Reference epigenome CKD25_C_Podo_mRNA-Seq data generated from KEP study

  A CKD25_C_Podo_mRNA-Seq paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003483

• RNA sequencing data to study "A biobank of patient-derived pediatric braintumor models"

  RNA sequencing data for the PDOX model EPD-613FH

  Dataset EGAD00001003573

• Pancreatic organoid - case samples

  This dataset contains 31 pancreatic organoid samples used in the 'organoid data of pancreatic cancers ' study

  Dataset EGAD00001004528

• SFHS pedigrees

  Deep (>25x mean coverage) whole genome sequencing on 5-10 families drawn from the Scottish Family Health Study with four or more children.

  Dataset EGAD00001001214

• Reference epigenome CKD24_C_Podo_mRNA-Seq data generated from KEP study

  A CKD24_C_Podo_mRNA-Seq paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003482

• STREP GENE Study Genome-wide Genotyping by Illumina Array

  Genotyping of 43 cases of invasive GAS infection by Illumina HumanCore-24 array and Illumina Global Screening Array.

  Dataset EGAD00001004558

• Reference epigenome OB57_D_PreA_smRNA-Seq data generated from KEP study

  A OB57_D_PreA_smRNA-Seq single end data for Preadipocyte(fat)

  Dataset EGAD00001003496

• Reference epigenome CKD24_C_Podo_smRNA-Seq data generated from KEP study

  A CKD24_C_Podo_smRNA-Seq single end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003498

• SFHS pedigrees_X10

  Deep (>25x mean coverage) whole genome sequencing on 5-10 families drawn from the Scottish Family Health Study with four or more children.

  Dataset EGAD00001003211

• Reference epigenome Islet-derived-MSC03 WGBS data generated from KEP study

  Islet-derived-MSC03 WGBS paired end data

  Dataset EGAD00001007142

• Reference epigenome ADMSC05 h3k27me3 ChIP-Seq data generated from KEP study

  ADMSC05 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007375

• Center for Common Disease Genomics [CCDG] - Cardiovascular: SWISS-AF/SWISS-AF-PVI/BEAT-AF

  This study is a part of NHGRI's Centers for Common Disease Genomics (CCDG), which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation (AF), congestive heart failure and type 2 diabetes. AF will affect between 6-12 million individuals in the US by 2050. AF is also associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules. Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdf Three collections were brought together to form Swiss atrial fibrillation cases: SWISS-AF, SWISS-AF-PVI, and BEAT-AF. SWISS-AF is a prospective observational, multicentric cohort study in Switzerland to increase our knowledge on structural brain damage and its changes over time in patients with atrial fibrillation. Overall, 2400 patients with documented atrial fibrillation aged >65 years will be included and followed on a yearly basis. SWISS-AF-PVI is a registry of patients with atrial fibrillation undergoing catheter-based ablation of atrial fibrillation (pulmonary vein isolation) to determine long-term success rates of catheter-based ablation of atrial fibrillation (pulmonary vein isolation) and to evaluate factors associated with long-term success of catheter-based ablation of atrial fibrillation (pulmonary vein isolation). BEAT-AF is a prospective observational, multicenter cohort study in Switzerland. Overall, 1550 patients with documented atrial fibrillation were enrolled in seven study centers. The main aim of this study is to investigate the therapy and the medical consequences of patients with atrial fibrillation. Samples from all three collections were sent to The Broad Institute of MIT and Harvard to generate genetic data using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all cases with atrial fibrillation.

  Study phs002242

• Immunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays

  IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) is a prospective longitudinal cohort study (NCT04378777) launched in May 2020 in response to the worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institute of Health (NIH). Patient enrollment and sample analysis involved 20 hospitals associated with 15 U.S. biomedical research centers and 11 centralized Core immunoassay laboratories.The study aimed to enable the identification of potential biomarkers and inform future therapeutic interventions using a longitudinal approach encompassing the whole disease course for a comprehensive understanding of the contributions of the pathogen and host immune response in modulating the manifestations, severity, and post-acute sequelae of the infection. IMPACC enrolled close to 1200 adult symptomatic, molecularly confirmed hospitalized COVID-19 patients in the study within 48 hours of their hospital admission. Clinical data and biological samples (blood, mid-turbinate nasal swabs, and esophageal aspirant) were collected according to minimal risk guidelines at enrollment and on days 4, 7, 14, 21, and 28. Biological samples were collected at 3-month intervals up to 12 months after hospital discharge to assess functional and immunologic recovery measures. Sample collection, processing, and storage procedures were standardized across sites, and samples were transported to centralized assay-specific core laboratories (Core Labs) in batches for testing and analysis. The description of outcome severity was not limited to survival versus death but encompassed a clinical trajectory approach using 5 groups leveraging longitudinal data based on time in the hospital, disease severity by ordinal scale based on the degree of respiratory illness, and presence or absence of limitations at discharge. Disease severity was assessed based on the degree of respiratory illness using a 7-point ordinal scale adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. DNA for genetic analyses was collected from whole blood at a single time point. To identify any genomic determinants of severe COVID-19 disease, single-nucleotide polymorphism (SNP) genotyping and exome sequencing were conducted to assess genetic variants associated with individual susceptibility to severe disease. In addition, IMPACC included bulk transcriptomic analysis of upper airway (nasal swaps) samples, lower airway (esophageal aspirant) samples, and peripheral blood mononuclear cells (PBMCs) to evaluate dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome. Additional information for the IMPACC study has been submitted to The Immunology Database and Analysis Portal (ImmPort) under study accession SDY1760. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Steven Kleinstein (steven.kleinstein@yale.edu).

  Study phs002686

• Capturing sex-specific and infertility-linked effects of assisted reproductive technologies on the cord blood DNA methylome

  Background: Children conceived through assisted reproduction are at an increased risk for growth and genomic imprinting disorders, often linked to DNA methylation defects. It has been suggested that assisted reproductive technologies (ART) and the underlying parental infertility can induce epigenetic instability, specifically interfering with DNA methylation reprogramming events during germ cell and preimplantation development. To date, human studies exploring the association between ART and DNA methylation defects report inconsistent or inconclusive results, likely due to population heterogeneity and the use of technologies with limited coverage of the epigenome. In our study, we explore the epigenetic risk of ART by comprehensively profiling the DNA methylome of 73 human cord blood samples from singleton pregnancies (n=36 control group, n=37 ART/infertility group) from a human prospective longitudinal birth cohort, the Design, Develop, Discover (3D) Study using a high resolution sequencing based custom capture panel that interrogates over 2.4 million autosomal CpGs in the genome. Results: the main findings We identified striking sex-specific effects of ART on cord blood DNA methylation patterning both genome-wide and for imprinted genes. When compared to less invasive procedures such as in utero insemination, more invasive ARTs (IVF, ICSI, embryo culture) resulted in more marked and distinct effects on the cord blood DNA methylome, including targeting of loci involved in development. Background: Children conceived through assisted reproduction are at an increased risk for growth and genomic imprinting disorders, often linked to DNA methylation defects. It has been suggested that assisted reproductive technologies (ART) and the underlying parental infertility can induce epigenetic instability, specifically interfering with DNA methylation reprogramming events during germ cell and preimplantation development. To date, human studies exploring the association between ART and DNA methylation defects report inconsistent or inconclusive results, likely due to population heterogeneity and the use of technologies with limited coverage of the epigenome. In our study, we explore the epigenetic risk of ART by comprehensively profiling the DNA methylome of 73 human cord blood samples from singleton pregnancies (n=36 control group, n=37 ART/infertility group) from a human prospective longitudinal birth cohort, the Design, Develop, Discover (3D) Study, using a high resolution sequencing based custom capture panel that interrogates over 2.4 million autosomal CpGs in the genome. Results: We identified striking sex-specific effects of ART on cord blood DNA methylation patterning both genome-wide and for imprinted genes. When compared to less invasive procedures such as in utero insemination, more invasive ARTs (in vitro fertilization (IVF), intracytoplasmic sperm injection (ICSI), embryo culture) resulted in more marked and distinct effects on the cord blood DNA methylome, including targeting of loci involved in development. Conclusions: Our study highlights the ability of a sensitive, targeted, sequencing based approach to uncover DNA methylation perturbations in cord blood associated with infertility and ART and influenced by offspring sex and ART technique invasiveness.

  Study EGAS00001006643

• ParityImmune

  Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC)

  Dataset EGAD00010001412

• Duplex sequencing

  A total of 387 buccal swab samples were subjected to error-corrected sequencing (duplex sequencing).

  Study EGAS50000000054

• Mutant p53 confers gain-of-function transcriptional activity in liver cancer

  Mutant p53 confers gain-of-function transcriptional activity in liver cancer

  Study EGAS00001005779

• DAC for TFHL single-cell analysis project at Department of Hematology, University of Tsukuba

  DAC for study of tumor heterogeneity and immune-evasive microenvironment in T follicular helper cell lymphomas

  Dac EGAC50000000201

• Chromatin immunoprecipitation followed by sequencing combined with transcription factor (TF) motif identification and transcriptome analyses revealed different patterns of REST binding and its proximal TF motifs in IDH wild-type and mutant gliomas

  Study EGAS00001006366

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Total RNA was extracted from the PaxFPE biopsy specimens (n = 116)

  Study EGAS50000000337

• Breast Cancer bulk RNA-Seq Dataset

  Bulk RNA-Sequencing of 18 primary breast cancers from Wu et al. (2021) study.

  Dataset EGAD50000000649

• Nanopore whole genome sequencing data of human PGT samples

  Data generated from embryo trophectoderm biopsies and corresponding parental blood samples

  Study EGAS50000000553

• WGS of constitutional MLH1 epimutation carriers and non-carrier relatives

  WGS of constitutional MLH1 epimutation carriers and non-carrier relatives

  Study EGAS50000000500

• H3Africa KDRN Phenotype

  The phenotypic data for 6431 samples of the KDRN Study from Ghana and Nigeria.

  Dataset EGAD00001009333

• DETECT-A protein data

  This dataset includes all protein biomarker measurements from the DETECT-A study. All protein biomarkers were evaluated with Luminex bead-based immunoassays obtained from Millipore.

  Dataset EGAD50000000444

• Whole Transcriptome Profiling of prDLBCL

  Gene expression profiling using RNA-seq was performed using material from 30 patients.

  Study EGAS50000000402

• COMPASS Next Generation Sequencing WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples from the COMPASS clinical trial

  Study EGAS50000001091