13423 results for ""60+mice"+"6+weeks"+diet+study+2014+2017+DOI"

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• 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

• 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

• 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

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001000825

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (WG) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastectomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005922

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - RNA

  RNA sequencing data from cancer patient-derived organoids. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015470

• PCGP Germline Study Whole Genome Sequencing

  PCGP Germline Study Whole Genome Sequencing

  Dataset EGAD00001001432

• High Density SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation

  This research builds upon an extensive resource of melanoma cases and hospital based controls collected over several years at the U.T. M.D. Anderson Cancer Center. The goal of this research is to identify novel susceptibility and outcome-related genes for melanoma using a systematic genome-wide association-based approach. Our goal is to conduct high-density SNP association and outcome studies. This dbGaP study contains samples from 2000 European ancestry cases and 1000 European ancestry controls using the Illumina OMNI1-Quad SNP chip. As a part of an ongoing R01 project, we have epidemiological data together with candidate gene results for 1000 of the melanoma cases and the controls. With regard to the outcome aspect of our design, as part of our melanoma Specialized Program of Research Excellence (SPORE) grant, our MelCore database contains comprehensive, prospectively maintained clinical information from all melanoma patients included in the study cohort, including primary tumor histopathology and staging information, standard and investigational blood tumor markers, details of surgical and systemic therapies, and extensive follow-up information, including time to relapse or recurrence, pattern of recurrence and survival duration. Finally, we intend to collaborate with the GenoMEL collaboration so we can jointly evaluate each other's findings. The goal of our analysis will be to identify novel genetic factors predisposing the development of melanoma, as well as genetic factors controlling melanoma stage at presentation, recurrence and progression. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to melanoma through large-scale genome-wide association studies of 2000 European ancestry cases and 1000 European ancestry controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000187

• NINDS-Genome-Wide Genotyping in Parkinson's Disease: First Stage Analysis and Public Release of Data

  Epidemiological studies have estimated a cumulative prevalence of PD of greater than 1 per thousand. When prevalence is limited to senior populations, this proportion increases nearly 10-fold. The estimated genetic risk ratio for PD is approximately 1.7 (70% increased risk for PD if a sibling has PD) for all ages, and increases over 7-fold for those under age 66 years. The role for genes contributing to the risk of PD is therefore significant. This study utilized the well characterized collection of North American Caucasians with Parkinson's disease, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis. Genome-wide, single nucleotide polymorphism (SNP) genotyping of these publicly available samples was originally done in 267 Parkinson's disease patients and 270 controls, and this has been extended to include genome wide genotyping in 939 Parkinson's disease cases and 802 controls. The NINDS repository was established in 10-2001 towards the goal of developing standardized, broadly useful diagnostic and other clinical data and a collection of DNA and cell line samples to further advances in gene discovery of neurological disorders. All samples, phenotypic, and genotypic data are available to the research community including to academics and industry scientists. In addition, well characterized neurologically normal control subjects are a part of the collection. This collection formed the basis of this first stage study by Fung et al., and the expanded study by Simon-Sanchez et al. The genotyping data was generated and provided by the laboratory of Dr. Andrew Singleton NIA, and Dr. John Hardy NIA (NIH Intramural, funding from NIA and NINDS). Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ

  Study phs000089