17420 results for "fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins They are definitely a top seller..rG5l"

in 22.30 milliseconds.

• Drug Resistant Hypertension in African Americans' Exome

  Resistant hypertension is defined as blood pressure that remains above goal in spite of the concurrent use of 3 antihypertensive agents of different classes or the concurrent use of 4 or more antihypertensive agents regardless of control. Its diagnosis is important for the identification of patients who are at high risk of having reversible causes of hypertension and/or patients who, because of persistently high blood pressure levels, may benefit from special diagnostic and therapeutic considerations. Resistant hypertension represents an extreme phenotype, thus, it has been predicted that genetic factors could play a larger role than for the general hypertensive population. Genetic assessments of patients with resistant hypertension have been limited. The current study assayed the exome of 91 African American patients with treatment resistant hypertension.

  Study phs000442

• Bone Microarchitecture

  Osteoporosis affects more than 28 million people in the United States and the lifetime risk for osteoporosis-related morbidity is higher than a woman's combined risk for breast cancer, endometrial cancer and ovarian cancer. Health care expenditures for osteoporotic patients in this country are currently nearly 13 billion dollars per annum and are predicted to increase markedly in the next decades due the aging of the population; therefore, it is important to understand the factors that contribute to bone strength and fracture risk. With the advent of skeletal imaging modalities such as high resolution peripheral quantitative computed tomography (HR-pQCT), it is now possible to study the genetics of more highly refined peripheral skeletal microarchitecture phenotypes. Because these refined phenotypes have not been measured in many cohort studies, this project was a collaborative effort to include almost all the existing data on HR-pQCT of the radius and tibia, and genetics from around the world. Cohorts involved in the discovery included: 1) Framingham Osteoporosis Study, 2) Mayo Clinic cohort; 3) Geneva Retirees cohort; 4) OFELY cohort from Lyon France; 5) STRAMBO cohort from Lyon France; 6) Swedish Male cohorts. Replication cohorts undergoing de novo genotyping include: 1) QUALYOR cohort from Lyon France; 2) CaMOS cohort from Canada. Other than the Framingham cohort and the Swedish male cohorts, all discovery cohorts underwent genome wide genotyping with the Affymetrix Axiom Biobank array that had common variants along with exome content based on the early findings from the Exome Sequencing Project. All genotype data from the discovery cohorts were then imputed using the Haplotype Reference Consortium reference panel. Variants for replication genotyping using the Kasp technology were selected based on novelty compared with previously identified loci using DXA phenotypes, minor allele frequency, underlying LD structure within a locus, and likelihood of a variant being functional as assessed using various algorithms for coding and non-coding variants.    

  Study phs002102

• Xenodiagnosis of Lyme Disease

  Ixodes scapularis ticks are an important vector for at least six tick-borne human pathogens, including the predominant North American Lyme disease spirochete Borrelia burgdorferi. The ability for these ticks to survive in nature is credited, in part, to their ability to feed on a variety of hosts without excessive activation of the proinflammatory branch of the vertebrate immune system. While the ability for nymphal ticks to feed on a variety of hosts has been well-documented, the host-parasite interactions between larval I. scapularis and different vertebrate hosts is relatively unexplored. In our clinical trial, patients with prior Lyme disease who had completed antibiotic therapy were exposed to 25-30 laboratory-reared larval ticks. Skin biopsies were taken before tick placement and/or after ticks were allowed to feed to repletion and we examined the effects on the transcriptional profile of human skin after the larval tick bites. We note pronounced evidence of inflammation in humans.

  Study phs003314

• Submitter Portal

  Submitter Portal The Submitter Portal does not support array submissions! Please refer to the array documentationAny new objects registered in the Submitter Portal will not be available for use in an array submission For further information please check our Submission FAQs, submission quickguide as well as submission terms! The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. Submitter Portal Index Previous steps Access to Submitter Portal Start a Submission Take The Tour Tutorial Previous steps Create your EGA account To submit data, you first need to create your EGA user. Then, once your account has been verified by the Help Desk team, you will be able to request a submitter role and send the EGA Data Processing Agreement (DPA). In the case you already have an EGA account, or an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role and added your public key to your profile, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find relevant information in the DAC Portal Guide. Access to Submitter Portal 1. Request Submitter Role Once you have created your EGA user, request a Submitter Role and complete relevant information such as submission type and size. 2. Signature of the Data Processing Agreement The Data Processing Agreement (DPA) signed by CRG and EMBL-EBI (Joint Data Processors for the EGA) can be downloaded to the submitter for its signature. Further information related to the DPA can be in the Privacy Notice section. The DPA should be signed by a legal representative of the submitter with power of attorney/appointment duly authorised to sign contracts on behalf of the institution. The submitter will return a fully-executed copy of the DPA to us. Please note that due to the high volume of submissions to EGA the DPA is non-negotiable. Once you have completed all the information and attached the DPA signed, send your Submitter request and the EGA Helpdesk Team will validate it and send a confirmation to start submitting your metadata. Start a Submission The steps below will show you how to start a submission and are accompanied with a tutorial and the Take the tour of Submitter Portal. 1. Login Go to the Submitter Portal interface and log in using your EGA account credentials. 2. Create a submission The Submitter Portal interface will show you any already existing open submission. To start a new submission click on “Create a Submission”.In this phase you have the option to add any collaborator(s) as well as their permissions (“Read only” or “Read & Write”). If you want to invite all the collaborators from a previous submission, you can add them by selecting said submission.In the event that the submission has been closed, you will need to reopen it. To do this, you will need to modify one of the objects in the submission, for example, copy and paste the title. Once the submission is open, you can add a collaborator. Further information can be found in the Submission Tour 3. Create Study Click on add Study and complete the form with the relevant information. The fields with an asterisk (*) are mandatory. Further information can be found in the Submission Tour4. Create Sample Sample registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with information about the sequencing samples. Upload the samples.csv and the sample will be created.Add single sample: complete the mandatory fields with the metadata information of your sample.  Further information can be found in the Submission Tour5. Create Experiment Register an experiment with ​information about the sequencing methods, protocols and machines. Experiments generate the connection between samples and study. Further information can be found in the Submission Tour6. Create Run Samples, experiments and files are linked through runs. To register a run, you will be asked to select the appropriate experiment and the file format. Run registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with the sample - file linkage. Upload the run.csv and the runs will register.As the INBOX is a directory, bear in mind to include the file path (/). Example: /filename.c4gh. Add single run: select the file format, sample and experiment from the drop box. For re-using submitted samples, please use the EGA accession ID (EGANXXX). Please note that files must be uploaded in your inbox before linking your files and samples. Further information can be found in the Submission Tour7. Create Analysis Analysis should be only used for BAM/BAI or CRAM/CRAI pair, VCF and phenotype linkage to samples. The analysis is an EGA specific metadata object that links samples to files. This object also stores some metadata about your experiments, such as the experiment type, genome reference, or the platform used. **If only BAM or CRAM alignment files are submitted but not the original unaligned FASTQ files, then please make sure that the BAM or CRAM files also contain the unaligned reads. This is critical to enable primary re-analysis and re-alignment of the dataset using new tools or future genome assemblies.** Start by selecting the samples to be linked to the file, and then populate the required attribute fields. Please be aware of the existence of mandatory fields that must be populated.When populating the chromosome field (mandatory), please select the chromosomes from the checkbox. Please take in consideration that EGA allows for the re-use of any registered metadata. Therefore, a previously registered study or samples can be referenced for the analysis in the current data submission.Further information can be found in the Submission Tour 8. Create Dataset Dataset contains the collection of runs/analysis data files subjected to controlled access by being associated with a Policy. Complete the mandatory fields such as title, description, type and policy. Please, take in consideration that DAC and Policy must be registered in advance in the DAC Portal. Similar to other metadata objects, you can re-use previous runs or analyses, using their EGA accessions IDs (runs - EGAR, analyses - EGAZ). Further information can be found in the Submission Tour 9. Finalise submission Once the files are ingested please delete them from your SFTP INBOX before finalising your submission. This will prevent the files from reappearing in your Submitter Portal Inbox. Once you have completed your submission, click on the Finalise button, and schedule an estimated release date. Afterwards, your submission will be sent to Helpdesk for approval. Please note that once the Helpdesk has approved your submission, you will receive the identifiers for your data. See the Frequently Asked Questions (FAQ) for more information. 10. Update closed submission If you want to append more file to a closed submission, you will need to re-open the submission where the dataset was registered. Find the Submission: go to the Submitter Portal Menu -> Datasets section and find the submission id (EGA0XXX).  Reopen the submission where the dataset is located: to reopen a submission, you must edit any object within the submission. For example, you can copy and paste the title. Take The Tour The Submitter Portal Take The Tour is a visual guidance of all the steps described previously about how to start a submission. Tutorial In this tutorial we will show you how to use the Submitter Portal to register your metadata. Please note the video focuses on the run-based submission (for raw files - fastq - and aligned data - BAM/CRAM) and analysis-based submission (for your BAM/BAI pairs, variation -VCF - and phenotype files).

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal

• Detection of Genes Predisposing to Hematologic Malignancies

  We have been conducting genetic studies on families at high risk of different hematologic malignancies, in order to define the related tumors in the families, define precursor and other related conditions, and map and identify susceptibility genes. We have focused mainly on four types of lymphoid malignancies: chronic lymphocytic leukemia (CLL), Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and Waldenström macroglobulinemia (WM). A few families with a rare lymphoma subtype, hairy cell leukemia (HCL) are included. In addition, single large pedigrees with acute myeloid leukemia (AML), and juvenile myelomocytic leukemia (JMML) are included. Families are ascertained for having at least two patients with the same hematologic malignancy and are classified by the type of malignancy that predominates in the family. Multiple types of lymphoid malignancies are often found in the same family. Other data has shown that these conditions aggregate together in families. Verification of cancer diagnoses is obtained through medical records, pathology reports, and flow cytometry. Family members with precursor traits are also included, monoclonal B-cell lymphocytosis (MBL) in CLL families and IgM monoclonal gammopathy of undetermined significance (MGUS) in WM families.

  Study phs001219

• Therapeutic Genetics and Disease Modeling in LAMA2-CMD

  Merosin-deficient congenital muscular dystrophy (MDC1A) is an autosomal recessive disorder caused by mutations in the LAMA2 gene, resulting in a defective form of the extracellular matrix protein laminin-α2 (LAMA2). Individuals diagnosed with MDC1A exhibit progressive muscle wasting and declining neuromuscular functions. No treatments for this disorder are currently available. This study involves transcriptomic comparison analysis between MDC1A patient fibroblasts and healthy control fibroblasts to reveal changes in gene expression that contribute to LAMA2 congenital muscular dystrophy (LAMA2-CMD).

  Study phs003250

• Childhood Cancer Data Initiative (CCDI): CCDI Pediatric In Vivo Testing Program - Leukemia

  The goal of this study is to molecularly characterize a large panel of pediatric acute lymphoblastic leukemia (ALL) patient-derived xenografts (PDXs) previously established in immune-deficient mice. These PDXs are utilized as part of the NCI-funded Pediatric Preclinical In vivo Testing (PIVOT) program to identify novel agents and combinations. Biospecimen data include next-generation sequencing (RNAseq, whole exome sequencing, DNA copy number variation), whole-genome analysis of cytogenetic abnormalities, and DNA fingerprint for quality control.

  Study phs003164

• Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL)

  Enteropathy associated T cell lymphoma (EATL) is frequently preceded by a state of refractoriness to the gluten-free diet, called “refractory celiac disease” or RCD. We aim to study which mutations and copy number aberrations are already manifest in RCD and to identify differences between RCD patients that do, and do not, develop EATL. We have applied whole exome sequencing to detect mutations and copy number aberration predictive for progression from RCD to EATL.

  Study EGAS00001006669

• Increased mutation accumulation during fetal development in Down syndrome

  Children with Down syndrome (DS) show a high incidence of leukemia, which is preceded by transient myeloproliferative disorder (TMD) in neonates. TMD is characterized by mutations in GATA1 that accumulate during fetal development, indicating that additional mutagenesis is required for leukemogenesis. Abnormalities in chromosome numbers can result in a mutator phenotype. However, it is unknown whether a trisomy of chromosome 21 (T21) results in enhanced mutation accumulation during human development. Here, we determined the mutational consequences of a constitutive T21 in DS fetuses compared to disomy 21 cells (D21) of D21 fetuses. We found that D21 fetal HPSCs had a higher somatic mutation rate compared to healthy adults HSPCs. Moreover, we observed an increase in somatic mutation load in T21 cells of DS fetuses, which was already apparent during the first cell divisions of embryogenesis. The mutation load could be explained by processes that are active during normal fetal development and were similar to those observed in TMD blast cells. Our study shows that T21 causes an increase in somatic load in fetal cells of DS fetuses, which may contribute to leukemia development early in life.

  Study EGAS00001003982

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777