13393 results for ""pdc"+"heritage+language"+census+study"

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• Reference epigenome Kidney-mesangial02 h3k4me3 ChIP-Seq data generated from KEP study

  Kidney-mesangial02 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007260

• Reference epigenome Kidney-mesangial02 h3k9me3 ChIP-Seq data generated from KEP study

  Kidney-mesangial02 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007261

• Reference epigenome Kidney-mesangial02 input ChIP-Seq data generated from KEP study

  Kidney-mesangial02 input ChIP-Seq paired end data

  Dataset EGAD00001007262

• Reference epigenome IPS-Fibroblast01 h3k27ac ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007263

• Reference epigenome IPS-Fibroblast01 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007264

• Reference epigenome IPS-Fibroblast01 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007265

• Reference epigenome IPS-Fibroblast01 h3k4me1 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007266

• Reference epigenome IPS-Fibroblast01 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007267

• Reference epigenome IPS-Fibroblast01 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007268

• Reference epigenome IPS-Fibroblast01 input ChIP-Seq data generated from KEP study

  IPS-Fibroblast01 input ChIP-Seq paired end data

  Dataset EGAD00001007269

• Reference epigenome IPS-Fibroblast02 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007271

• Reference epigenome IPS-Fibroblast02 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007272

• Reference epigenome IPS-Fibroblast02 h3k4me1 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007273

• Reference epigenome IPS-Fibroblast02 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007274

• Reference epigenome IPS-Fibroblast02 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007275

• Reference epigenome IPS-NPC01 h3k27ac ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007277

• Reference epigenome IPS-NPC01 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007278

• Reference epigenome IPS-NPC01 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007279

• Reference epigenome IPS-NPC01 h3k4me1 ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007280

• Reference epigenome IPS-NPC01 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007281

• Reference epigenome IPS-NPC01 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-NPC01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007282

• Reference epigenome IPS-NPC01 input ChIP-Seq data generated from KEP study

  IPS-NPC01 input ChIP-Seq paired end data

  Dataset EGAD00001007283

• Reference epigenome IPS-NPC02 h3k27ac ChIP-Seq data generated from KEP study

  IPS-NPC02 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007284

• Reference epigenome IPS-NPC02 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-NPC02 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007285

• Remaining WGS files for Klco RPAML data

  Remaining WGS files for study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008446

• MSAT dataset

  Muscle SATellite cell study (MSAT) dataset comprises 39 samples of paired-end RNA-Seq sequences in fastq format.

  Dataset EGAD00001008984

• Targeted_EMSeq___Development

  Development of a targeted methylation assay to determine the cell-type composition of a sample.

  Study EGAS00001007202

• DAC policy The Kids Research Institute Australia

  DAC policy related to the study: Visium CytAssist Spatial Gene Expression analysis for FFPE glioblastoma samples. Committee: Raelene Endersby raelene.endersby@thekids.org.au Anya Jones anya.jones@thekids.org.au Emma Stone emma.stone@thekids.org.au

  Dac EGAC50000000734

• Genetic Analysis of Limb Malformation Disorders: Freeman Sheldon Syndrome Exome Sequencing Study (LMD-FSS)

  The overall goal of this project is to investigate the etiology and pathogenesis of malformations (i.e., birth defects) of the limb, concentrating on abnormalities of limb patterning such as limb deficiency/duplications and multiple congenital contractures. The exome sequences of four unrelated individuals were obtained by massively parallel DNA sequencing. The three individuals were affected with Freeman Sheldon syndrome (OMIM: 193700).

  Study phs000204

• GWA Study of Oral Cavity, Pharynx and Larynx Cancers in European, and North and South American Populations - CIDR

  There is striking geographical variation in head and neck cancer (HNC) incidence globally. Some of the highest incidence rates have been observed in Southern and Eastern Europe and South America. The goal of this project is to assess susceptibility loci across and within ancestral backgrounds, using the All of Us array. Ten studies have come together in this initiative.

  Study phs002503

• Canadian prostate cancer samples (CPC-GENE) for PanProstate study

  CPC-GENE has sequenced the genomes of 350 intermediate risk prostate cancers to identify genetic signatures that differ in cancers that responded well to treatment compared with those that did not. CPC-GENE also has sequenced multiple regions of prostate cancer from the same gland to determine if and how the genetic make-up of prostate cancer varies within an individual man’s prostate

  Study EGAS00001003037

• Study of wound response like states in glioblastoma

  In order to investigate wound reponse-like states in glioblastoma, we carried out experiments on primary tissue as well as organoids. Single cell RNA sequencing was performed on core and periphery of three human glioblastoma. Bulk RNA sequencing was performed on glioblastoma-derived organoids subject to treatment for 72h with plasma, hypoxia, or both, and analyzed at 0, 24, 72, and 144h.

  Study EGAS50000001442

• Bevacizumab plus erlotinib in advanced solid cancers with Krebs cycle gene mutations: A multicenter phase II study

  Targeting aberrant metabolism in tumors with alterations in genes encoding Krebs cycle enzymes, a central component of glucose metabolism, is a promising therapeutic strategy. These tumors rely on aerobic glycolysis and promote VEGF-dependent angiogenesis; furthermore, EGFR signaling enhances aerobic glycolysis. This phase 2 trial evaluated bevacizumab and erlotinib in patients with solid tumors harboring Krebs cycle gene mutations.

  Study EGAS50000001243

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of 10x Genomics 5'prime single-cell RNA sequencing of 40 tumor biopsy samples or triple negative breast cancer. Samples are taken before and after immuno checkpoint blockade treatment. Processed according the 10X genomics protocol, sequenced on Immumina NovaSeq6000. Raw sequencing reads are further processed with Cellranger 3.0 to get gene-expression matrices.

  Study EGAS50000000527

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• HiDEF-seq single-molecule sequencing of single-strand mismatches and damage

  Our study sought to resolve, with single-molecule fidelity, the mismatches and damage events that precede DNA mutations. Using a novel single-molecule, long-read sequencing method (HiDEF-seq) we detect base substitutions when present in either one or both DNA strands. We also detect cytosine deamination, a common type of DNA damage, with single-molecule fidelity. This study profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes. These samples revealed single-strand mismatch and damage signatures. Since double-strand DNA mutations are only the endpoint of the mutation process, our approach enables new studies of how mutations arise in a variety of contexts, especially in cancer and aging.

  Dataset EGAD50000000460

• Leeds Melanoma Cohort (LMC) gene expression study

  Array-based profiling (whole genome DASL HT12.4, Illumina Inc) in over 700 FFPE tumour blocks from the population-based Leeds Melanoma cohort recruited in the North of England, with a long follow up. Data used in tumour immune micro-environment investigation (Nsengimana et al 2018, J Clin Invest doi: 10.1172/JCI95351).

  Study EGAS00001002922

• ScRNA-seq of PBMC and whole blood samples reveales a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Dataset EGAD00001006550

• Melanoma-Til Study RNAseq

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Dataset EGAD00001000325

• GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes

  The GoT2D study includes ~2800 samples, half T2D cases and half T2D controls, of Northern European ancestry sequenced over 3 three technologies: deep whole exome sequencing, low-pass (4x) whole genome sequencing, and OMNI 2.5M genotyping. Samples were ascertained to be phenotypically "extreme" (e.g. leaner, younger cases and older, more obese controls). Genotypes (SNVs, INDELs, and SVs) were called separately for each technology and then integrated via genotype refinement into a single phased reference panel; samples and variants were then excluded based on QC procedures described in Fuchsberger et al. Please note that 2 of the samples in the GoT2D vcf do not have phenotype data.

  Dataset EGAD00001002247

• Cell-Free DNA Fragmentation Distinguish Immunotherapy Responders from Non- Responders in Head and Neck Cancer: A Multi-Institute Prospective Study

  We performed whole-genome sequencing of 185 plasma cfDNA samples from 68 patients with head and neck squamous cell carcinoma (HNSCC) enrolled in a phase II clinical trial of neoadjuvant and adjuvant pembrolizumab. Using these data, we developed the regional motif diversity score (rMDS), a novel fragmentomic biomarker that predicts immunotherapy response and outperforms established cfDNA metrics.

  Study EGAS50000001286

• Whole Exome PC9 and A375 (2019-04-03)

  Drug resistant population of PC9(human non-small cell lung cancer) or A375 (human melanoma) cell lines were used for this study. By exome sequencing, we will analyse mutations of cells in drug tolerent state and after drug holiday. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004891

• Lymphocyte Gut WGS H38 (2021-02-02)

  We study lymphocyte somatic evolution through the sequencing of normal healthy lymphocytes. We perform whole-genome sequencing of single-cell derived T and B cell colonies to identify somatic mutations, and perform targeted deep-sequencing of these mutations. The lineages of T and B cells, and the frequencies of these mutations reveals the neutral and non-neutral evolutionary processes underlying lymphocyte growth and function. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006934

• Lymphocyte PanBody WGS H38 (2021-02-02)

  We study lymphocyte somatic evolution through the sequencing of normal healthy lymphocytes. We perform whole-genome sequencing of single-cell derived T and B cell colonies to identify somatic mutations, and perform targeted deep-sequencing of these mutations. The lineages of T and B cells, and the frequencies of these mutations reveals the neutral and non-neutral evolutionary processes underlying lymphocyte growth and function. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006935

• The BEACCON study: tumour sequencing

  This dataset consists of paired-end DNA sequencing (whole exome and targeted-capture) of tumours for the BEACCON study. There are 240 unique samples consisting of 92 matched tumour-germline pairs and 56 unmatched tumours totalling 148 patients. There are 33 paired and 6 unpaired tumours sequenced using the Agilent SureSelect All Human Exon v6 libraries, 1 paired and 8 unpaired tumours sequenced using Agilent SureSelect All Human Exon v7 libraries and 48 paired and 3 unpaired tumours sequenced using Twist Bioscience Comprehensive Human Exome v1 libraries totalling 176 whole exome samples. There are 3 paired and 58 unpaired tumours sequenced using a custom Agilent SureSelectXT library totalling 64 targeted capture samples.

  Dataset EGAD00001009299

• Alcohol Dependence GWAS in European- and African Americans

  This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1889 African-American (AA) subjects and 1020 European-American (EA) subjects. Among the AAs, 1397 meet DSM-IV criteria for alcohol dependence and 491 are controls. Among the EAs, 1010 meet the criteria for alcohol dependence and 9 are controls. (One in each population meets criteria for alcohol abuse and not dependence, and is therefore counted in neither category.) Although alcohol dependence is the major focus, the sample is informative also for cocaine, nicotine, and opioid dependence.

  Study phs000425

• Epigenomics Studies in Acute Myeloid Leukemia (AML)

  Acute Myeloid Leukemia (AML) remains a clinical challenge since most patients diagnosed with AML will die from the disease. Some patients harbor treatment-refractory disease and many others relapse with disease that in many cases is resistant to treatments. Our study was designed to understand the molecular basis of disease progression in AML through assessing genomics signatures in patient specimens collected through an international collaboration which assembled samples from 138 AML patients which experienced disease relapse and normal hematopoietic cells (n=15). It is hoped that this resource will help researchers understand mechanisms of disease relapse in AML and contribute to the general pool of data available for analyses for this disease and general research use.

  Study phs001027

• Phase I Clinical Trial Describing the Pharmacogenomics of Aspirin

  The study protocol for both cohorts has been previously described (Journal of Thrombosis and Thrombolysis 2012:1-12). HV1 cohort: Briefly 50 healthy volunteers were exposed to two weeks of 325mg/day aspirin after which whole blood RNA was collected in PAXgene tubes and profiled by microarray before and after aspirin exposure. The pre-aspirin samples were profiled on the U133A 2.0 array and the post-aspirin samples were profiled on the U1333plus 2.0 array. HV2 cohort: Briefly 53 healthy volunteers were exposed to four weeks of 325mg/day aspirin after which whole blood RNA was collected in PAXgene tubes and profiled by U133plus 2.0 array before and after aspirin exposure.

  Study phs000548

• GnRH Agonist-Induced Ovarian Suppression and Ovarian Steroids in PMDD and Controls

  In this study, lymphoblastoid cell line cultures (LCLs) from women with premenstrual dysphoric disorder (PMDD) and asymptomatic controls were compared via whole-transcriptome sequencing (RNA-seq) during untreated (ovarian steroid-free) conditions and after estradiol and progesterone treatment. In untreated LCLs, pathway analysis of the LCL transcriptome revealed, among others, over-expression of ESC/E(Z) complex genes (an ovarian steroid-regulated gene silencing complex) with significant overexpression of MTF2, PHF19, and SIRT1 (P<0.05) in cells from women with PMDD compared with controls. Finally, mRNA expression of several ESC/E(Z) complex genes were increased by progesterone in controls only, and decreased by estradiol in PMDD LCLs.

  Study phs001344