6260 results for "fc 26 ultimate team coins buy Buyfc26coins.com is FC 26 coins official site..E4Pd"

in 17.58 milliseconds.

• The Human Pancreas Analysis Program (HPAP)

  The past decade has seen a dramatic improvement in our ability to phenotype and molecularly profile human tissues with unprecedented resolution at the genomic, epigenomic, protein, and functional levels. The Human Pancreas Analysis Program (HPAP), part of the Human Islet Research Network and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) through multiple NIH grants, is performing deep phenotyping of the human endocrine pancreas to better understand the cellular and molecular events that precede and lead to beta-cell loss and/or dysfunction in type 1 diabetes (T1D) and type 2 diabetes (T2D) as well as to accumulate, analyze, and distribute high-value data sets to the diabetes research community through the HPAP PANC-DB database (and additional details provided at that site). To this end, HPAP employs state-of-the-art technologies to perform comprehensive analyses of pancreas biology as it pertains to organ donors with T1D, autoantibody-positive donors without diabetes, donors with T2D, and control donors. Pancreas procurement and analyses take advantage of the expertise and extensive network of Organ Procurement Organizations (OPOs) and autoantibody screening centers established through the JDRF/The Lenona M. and Harry B. Helmsley Charitable Trust (HCT) – funded nPOD program. In contrast to nPOD, the major product provided by HPAP is not archived biomaterial subject to broad distribution, but rather, the delivery of extensive and high-quality molecular data sets to the diabetes research community in order to facilitate further discovery. Together, nPOD and HPAP are complementary programs that assist the diabetes community and afford the maximal opportunity for advancing knowledge about the pathogenesis of T1D and T2D.

  Study phs002465

• CPTAC Proteogenomic Study

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.) The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein=protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the third phase of the CPTC initiative in September 2016. As the Clinical Proteomic Tumor Analysis Consortium, CPTAC continues to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach was to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. In this third phase of CPTAC, the program aims to expand on CPTAC II and genomically and proteomically characterize over 2000 samples from 10 cancer types (Lung Adenocarcinoma, Pancreatic Ductal Adenocarcinoma, Glioblastoma Multiforme, Acute Myeloid Leukemia, Clear cell renal Carcinoma, Head and Neck Squamous Cell Carcinoma, Cutaneous Melanoma, Sarcoma, Lung Squamous Cell Carcinoma, Uterine Corpus Endometrial Carcinoma) .Germline DNA is obtained from blood and Normal control samples for proteomics varied by organ site. All cancer samples were derived from primary and untreated tumor.

  Study phs001287

• Genetic Analysis of Normal Human Facial Variation

  The purpose of this project is to identify genes associated with normal human quantitative facial variation. The motivation for this project stems from the fact that very little is known about how variation in specific genes relates to the diversity of facial forms commonly observed in humans. Viable candidates for these morphogenes originate from a number of sources: tissue expression studies, animal models with targeted or spontaneous mutations, and genetic syndromes with craniofacial manifestations. Importantly, understanding the genetic basis for normal facial variation also has important implications for health-related research. For example, this work has the potential to shed light on the factors influencing liability to common craniofacial anomalies such as orofacial clefts. There is now ample evidence that certain facial features (e.g., increased midfacial retrusion) characterize individuals genetically at-risk for orofacial clefts (e.g., biological relatives of affected cases). While these predisposing facial features are statistically over-represented in at-risk groups, they are also common in the general population. Since many of the current candidate genes for clefting are thought to play a critical role in facial morphogenesis, variation in these genes may also underlie normal variation in these facial features. These candidate genes, however, probably represent only a small fraction of the total number of loci influencing normal human facial variation. Phenotypes for this project were obtained from over 3000 healthy Caucasian subjects recruited through three separate studies. The majority of the subjects were recruited as part of the 3D Facial Norms Project, which is described in extensive detail here: (https://www.facebase.org/facial_norms/notes). The provided dbGaP phenotypes include a series of anthropometric craniofacial measurements (linear distances) primarily derived from 3D photographic facial surface scans (see previous hyperlink). The specific genotyping requested is described elsewhere in this document. Our analysis team is pursuing a variety of different analytic approaches to derive genetically informative phenotypes, including various shape-based morphometric methods. For those interested in pursuing more advanced phenotypic approaches, the original 3D surface scans and additional phenotypic traits are available to researchers through the FaceBase Consortium. This dataset has the potential to facilitate the discovery of new genetic loci with an important role in both normal and abnormal facial development. It may also serve as a dataset to test hypotheses regarding specific SNP associations (e.g. as a replication dataset) or as part of a larger meta-analysis.

  Study phs000949

• Cross-Sectional Characterization of Idiopathic Bronchiectasis

  This GDMCC protocol will study adult patients with non-CF, idiopathic bronchiectasis, whose genetic etiologies are not known. Idiopathic bronchiectasis is reportedly more common in females with certain tall, thin body types and associated with environmental organisms, such as nontuberculous mycobacterium (NTM). The other susceptibility factors predisposing to bronchiectasis or acquisition of NTM are unclear. The study will attempt to broaden the understanding of this disease by comparing gender-associated factors and NTM status. A relatively equal number of both females/males and NTM/non-NTM infected subjects will be enrolled. Approximately 300 people may be screened to find 260 eligible subjects, since a small number (e.g., 40 patients) may be diagnosed with PCD, vCF, or other known etiology as an explanation for the bronchiectasis. This single-visit protocol will use a systematic approach to characterize the physical features, radiographic patterns, and associated lower airway microbial flora. There is no natural history of disease course follow-up component to this protocol. Participants will have one outpatient clinic visit for evaluation with a physical examination including detailed body size measurements, medical history, collection of blood samples for routine lab tests and genetic analyses, and a chest X-ray if no recent one is available. Participants will also have tests of lung function, and measurement of a gas called nitric oxide in the nose. Participants whose initial tests show abnormal results may also be asked to have a nasal scrape to collect cell samples and/or a skin sweat test to measure salt concentrations. Participants will also have a sputum specimen collected during the visit and will be asked to collect two additional early morning sputum samples and a mouth rinse at home within 2 weeks of the clinic visit, and mail the sample collection materials to the research team. Careful evaluation and characterization of the physical and clinical characteristics will guide the genetic characterization of idiopathic bronchiectasis, and likely lead to an improved diagnostic approach. Identification of disease causing genes may provide new therapeutic targets.

  Study phs001279

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000283

• Polycystic Ovary Syndrome (PCOS) Genetics

  PCOS is a complex genetic disease reflecting the interplay of susceptibility genes and environmental factors. The cardinal reproductive feature of the syndrome, hyperandrogenemia, appears to play a direct role in the pathogenesis of the associated metabolic abnormalities. Male as well as female first-degree relatives have reproductive and metabolic phenotypes including increased prevalence rates of type 2 diabetes (T2D), metabolic syndrome (MBS) and other risk factors for cardiovascular disease (CVD). Northwestern University (NU) investigators lead a team that has extensive experience in phenotyping PCOS and in the genetic analysis of complex diseases including genome-wide association study (GWAS). Together with an expert group of collaborators from the Hershey Medical Center, and The University of Chicago, we have conducted a GWAS to identify PCOS susceptibility alleles using a large cohort of extensively and consistently phenotyped PCOS cases. Population controls for this study come from the NUgene project described below. NUgene project: In 2002, Northwestern committed to the development of a DNA repository to serve as a platform for the identification and validation of genotype-phenotype associations that will impact healthcare. The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators.

  Study phs000368

• Test dataset: Sequence and variant data from public 1000 Genomes Project

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 2508 samples from the 1000 Genomes Project (https://www.nature.com/articles/nature15393). Samples' (e.g. NA18534) data can be accessed through the IGSR portal (e.g. https://www.internationalgenome.org/data-portal/sample/NA18534) or their corresponding folder at the 1000 Genomes' FTP site (e.g. http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/data/CHB/NA18534/exome_alignment/). There are several different types of data this dataset encompasses: Variant Calling Format (VCF, or its binary counterparts BCF) files, both joint (e.g. ALL_chr22_20130502_2504Individuals.vcf.gz) and split (HG01775.chrY.vcf.gz); exome sequencing CRAM files (e.g. NA18534.GRCh38DH.exome.cram); whole genome sequencing CRAM/BAM files (e.g. NA19239.cram). Additionally, there are multiple files that were sliced to create shorter files, which allows for a quick download, formated as "{FILE-INFO}__{NUMBER-OF-READS}r__{CHR}.{START-COORDINATE}-{END-COORDINATE}.{FILETYPE}" (e.g. "HG01500.GRCh38DH__90r__3.10000-10500__4.10000-10500.cram"). These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client).

  Dataset EGAD00001003338

• Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

  This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

  Dataset EGAD50000000559

• Patient Registry for Primary Pulmonary Hypertension (PPH Registry-BioLINCC)

  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 Establish a patient registry to evaluate the natural history, etiology, pathogenesis and treatment of primary pulmonary hypertension. Specific aims included the characterization of the demographic, medical history, family history, physical and laboratory findings of patients at time of diagnosis, and to characterize the survival duration of patients by traits evaluated at diagnosis and by medical interventions. Background There are several known causes of pulmonary hypertension: chronic obstructive pulmonary disease, congenital heart disease, mitral stenosis, left ventricular dysfunction and recurrent pulmonary emboli. Primary Pulmonary Hypertension is a disorder of unknown etiology which is diagnosed only after the known causes of pulmonary hypertension have been eliminated. Prior to the PPH registry, little was known regarding the epidemiology, etiology, natural history or ultimate survival among patients with PPH. In 1973, the WHO met to review the current state of knowledge on PPH and proposed the establishment of a multicenter collaborative study. The NHLBI PPH registry enrolled patients in the registry from 1981 to 1985. Participants Participants were enrolled into the registry from 32 medical centers throughout the US. Pulmonary hypertension was defined as a mean pulmonary arterial pressure of >25 mmHg at rest or 30 mmHg with exercise at catheterization. The diagnosis of primary pulmonary hypertension was only accepted after the following secondary causes of pulmonary hypertension had been excluded: pulmonary hypertension within the first year of life, congenital abnormalities of the heart, lungs, or diaphragm, pulmonary thromboembolic disease, diagnosis of sickle cell anemia, history of intravenous drug abuse, obstructive lung disease, interstitial lung disease, arterial hypoxemia, collagen vascular disease, parasitic disease affecting the lungs, pulmonary artery or valve stenosis, or pulmonary venous hypertension. Baseline and follow-up data collected on participants include demographic characteristics, chest radiograph, pulmonary function tests, lung perfusion scan or pulmonary angiogram, intracardiac left-to-right shunt, pulmonary hemodynamics, as well as a history, physical findings and other laboratory measurements. Participants were followed for approximately 5 years. Conclusions There were 1.7 females for each male in the registry, and females tended to present with more severe symptoms. The mean time from onset of symptoms to diagnosis was 2 years. Right ventricular hypertrophy was found in 87% of participants and right atrial pressure was elevated in 72% of participants. The estimated median survival was 2.8 years with single year survival rates of: 1 year, 68%; 3 years, 48%; and 5 years, 34%. (Ann Intern Med, 1987; 107:216-23, Ann Intern Med, 1991; 115:343-49).

  Study phs004275

• PE-CGS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies

  Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos (H/L) are the largest and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US. Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group. For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting, demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594 cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices may not be investigated to identify best practices for accruing and consenting patients into clinical translational biomedical research studies. This concept of Participant Engagement is critically important for both the patients and the translational cancer research community. Optimizing and improving our approaches for directly engaging patients at initial contact, throughout the course of a translational genomic study, and during the time of return of results is likely to lead to stronger relationships between the medical community and patients, but could also lead to significant improvement in outcomes for patients and for the cancer care community as a whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in all relevant areas of research for genomic characterization, participant engagement, and engagement optimization. We have an established platform for consenting patients into cancer genomics studies that will serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement optimization and CRC genomic research that will be shared with the broader community to distribute best practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.

  Study phs003985