6176 results for "get fc 26 coins Buyfc26coins.com is FC 26 coins official site..4xt1"

in 52.69 milliseconds.

• Total RNAseq in the sporadic ALS and healthy control motor cortex

  Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the degeneration of upper and lower motor neurons leading to progressive muscle weakness, wasting and paralysis that result in death within a few years from disease onset. In order to characterize RNA alterations in ALS, total RNAseq was performed in the ALS motor cortex, which is an early and vulnerable region in ALS.

  Study EGAS00001004286

• De_novo_mutations_in_cell_free_foetal_DNA__cffDNA_

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women.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 EGAS00001000322

• Renal_Follow_Up_Series

  This study's purpose is to use data generated in Renal whole genome and exome Cancer sequencing to target specific areas in multiple other Renal Cancer samples. These areas will then be subjected to bespoke pull downs, tagged and then pool the resultant amplicons. These amplicons will then be sequenced. This is hoped to show the prevalence of previous findings in multiple individuals in a high throughput method.

  Study EGAS00001000095

• PAH sequencing study

  The Cohort study of idiopathic and heritable PAH is an observational, prospective and longitudinal study of patients with idiopathic and heritable PAH. Follow-up information is collected as a part of routine clinical care every six months. The study allows recruitment of both incident and prevalent cases. Patients consented to the study agreed to have blood taken for next-generation sequencing and other omics studies.

  Study EGAS00001005532

• Microenvironment subtypes and association with tumor cell mutations and antigen expression in follicular lymphoma

  Follicular lymphoma (FL) is a B-cell lymphoma with a complex tumor microenvironment that is rich in non-malignant immune cells. We applied single-cell RNA-sequencing to characterize the immune microenvironment of FL. This provides a classification framework of the FL microenvironment, their association with FL genotypes and antigen presentation, and informs different potential immunotherapeutic strategies.

  Study EGAS00001006052

• Germline and somatic variants in myelodysplastic syndrome and therapy-related myeloid neoplasms

  Somatic mutation frequencies in patients with therapy-related myeloid neoplasms (129 patients, 181 samples including bone marrow, mesenchymal stromal cells and hair DNA) and primary myelodysplastic syndrome (108 patients, 215 samples including bone marrow, mesenchymal stromal cells and hair DNA) is assessed by deep sequencing of selected genes, using a Fluidigm Access Array, a Nimblegen capture panel and an Ion AmpliSeq panel. The dataset consists of paired fastq files obtained by either Hiseq (2x101bp) or Nextseq (2x150bp) Illumina sequencing. The mutational burden is found to be similar in both, however the distribution of variants is different. Correlation of the mutational spectrum with prognosis is also observed.

  Dataset EGAD00001004861

• FEGA Sweden Helpdesk

  FEGA Sweden is an archive for storing and sharing all kinds of data resulting from biomedical research projects. As a national node of the Federated European Genome-phenome Archive (FEGA), we enable researchers to store their data in Sweden in a way that meets the requirements of the General Data Protection Regulation (GDPR). Any data submitted to the archive is subject to controlled access, meaning access to the data only will be granted after a formal application procedure. Using FEGA Sweden for storing and sharing data is free of charge for academic users affiliated with a Swedish university. However, the university must have a signed Data Processing Agreement (DPA) with Uppsala University. The current list of universities with a signed DPA can be found here: https://fega.nbis.se/submission/complying-with-gdpr.html. FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. Contact the FEGA Sweden Helpdesk at fega-sweden@nbis.se for further questions.

  Dac EGAC50000000077

• Transcriptomic profiles of early and late passage metastatic colorectal cancer (mCRC) tumoroids

  The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. This specific dataset is focused on a comparison of early and late passage tumoroids transcriptomes.

  Study EGAS50000000108

• 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

• Coenzyme Q10 (CoQ) in Huntington's Disease (HD) (2CARE)

  This is a multi-center, randomized, double-blind, placebo-controlled trial of CoQ involving 609 ambulatory subjects with HD who are not requiring skilled care or institutionalization. Eligible subjects were randomized to receive either CoQ 2400 mg/day or matching placebo. Subjects were followed prospectively and systematically for 60 months of double-blind observation. The primary outcome variable is a combination of time to death (for subjects who die) and the change from baseline to Month 60 in Total Functional Capacity (TFC) score (for subjects who survive). The primary hypothesis of the study is that chronic treatment of early-stage HD subjects with high-dosage CoQ will slow the progressive functional decline of HD.

  Study phs001065

• Genetics of diffuse large B-cell lymphoma in Japan

  Diffuse large B-cell lymphoma (DLBCL) is a common hematological malignancy. Treatment with standard chemotherapy results in long-term remission in approximately 60% of patients. Whole-exome sequencing studies of large DLBCL cohorts revealed the biological diversity of tumors and facilitated the identification of genetic subtypes based on genetic alterations. Despite the progress facilitated by NGS, genetic classification is difficult to apply in clinical practice because of the complexity of the clustering algorithm. Furthermore, only a few reports included large Asian cohorts. Thus, a genetic overview of Japanese patients with DLBCL is still needed. Thus, in this study, we aimed to establish the clinical application of our simplified genetic classification algorithm in Japanese DLBCL.

  Study JGAS000307

• Star2xml: metadata converter into XML

  Star2xml: metadata converter into XML Welcome to the landing page for star2xml - a tool developed by the European Genome-phenome Archive (EGA) that enables users to convert metadata into XML format that is compliant with EGA's programmatic submission system. For starters, if you are not sure what metadata is in this context, you may want to explore our brief metadata introduction. . Star2xml is useful for users who have already submitted their data to the EGA and want to also submit their metadata programmatically without having to create the XML files manually. The need for these XMLs containing metadata is explained in the EGA's metadata schemas and programmatic submission guidelines. In summary, star2xml allows for users to deposit metadata in a tabular format (e.g. excel spreadsheet) and transform it into a compliant XML format. This saves time in large submissions, where the sheer size of metadata makes it difficult to manage. For smaller submissions, it is recommended to use EGA's Submitter Portal (SP) instead. The installation of the tool is straightforward, and it contains detailed documentation on how to use it in its GitHub repository . While star2xml can help users convert metadata formats, it does not validate the resulting metadata against EGA's schemas. Therefore, after creating your XMLs, you should still validate your metadata before submitting it to EGA, as described in the documentation for programmatic metadata validation.

  Documentation tools/star2xml

• EGA submission account terms

  Submission account terms Each EGA submission account has a dedicated submission box. To ensure continued service to all submitters EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. Those that are near to or exceeding this value will be monitored on a weekly basis by the helpdesk team and the submitter will be contacted and guidance provided accordingly on completing their metadata registration. You will be able to register your metadata associated with the files in your submission account via EGA Submitter Portal, Webin or the EGA REST API. EGA also requests that metadata is submitted within 60 days of upload data to a submission box. When we detect files that are over 60 days old in a submission box we will notify the submitter requesting that metadata be submitted or the files removed from the submission box. It is important to note that data is not archived at the EGA until the metadata describing the files has been associated and the archival process has completed. It is only when associated metadata has been submitted that the archival process into EGA is fully triggered. EGA removes files from the submission box once they have been successfully archived, so no action is required by a submitter to remove successfully archived files. Files over 90 days old will be deleted from the submission box unless EGA Helpdesk has been contacted and confirmed an exemption with the submitter.

  Documentation submission/terms

• ESGI_Identification_of_novel_genes_and_mechanisms_leading_to_Primary_Ciliary_Dyskinesia

  Approximately 80% of clinically clearly diagnosed patients suffering from primary ciliary dyskinesia (PCD) cannot be assigned to a specific gene defect. Despite extensive research on PCD and despite the increasing number of PCD genes and knowledge about their sites of action as e.g structural component or cytoplasmic pre-assembly factor, the biology of motile cilia and the pathomechanism leading to PCD is largely unknown. The aim of this study is to identify novel PCD related genes and processes relevant for motile cilia function.We will perform exome sequencing, aiming on the analysis of family trios. In these families, the diagnosis of PCD is secured, but the underlying gene defects has so far not been identified.

  Study EGAS00001000523

• ICGC Oesophageal adenocarcinoma - pilot samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett's oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000559

• ICGC Oesophageal adenocarcinoma - Barrett's samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett’s oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000726

• Deregulation of DUX4 and ERG in acute lymphoblastic leukemia

  Chromosomal rearrangements deregulating hematopoietic transcription factors are common leukemia-initiating lesions in acute lymphoblastic leukemia (ALL). Here, we show that deregulation of the homeobox transcription factor gene DUX4 and the ETS transcription factor gene ERG are hallmarks of a subtype of B-progenitor ALL with a distinct gene expression profile that comprises up to 7% of B-ALL. DUX4 rearrangement and overexpression is present in all cases, and is accompanied by profound transcriptional deregulation of ERG, frequent ERG deletion and expression of a truncated ERG isoform, ERGalt. ERGalt utilizes a non-canonical first exon that is bound by DUX4 and induces its expression....

  Study EGAS00001001923

• GoDARTS T2D-GENES Exome Sequencing Study is a subset of the ~52,000 Type 2 diabetes exome sequencing project.

  The GoDARTS T2D-GENES Exome sequencing study is a subset of a larger Type 2 Diabetes Exome Sequencing project. This effort is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date and includes samples from: T2D-GENES, GoT2D, ESP, SIGMA T2D, LuCAMP, and ProDIGY. This data generated from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for T2D through multiethnic sequencing studies. Sequencing for the GoDARTS study was performed at the Broad Institute using Illumina Rapid Capture on Illumina HiSeq machines.

  Study EGAS00001002937

• Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes

  Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes

  Dataset EGAD00001000050

• Evaluation of Ancestry Admixture among Chileans

  The purpose of this study is to investigate ancestry admixture among Chileans with and without gallbladder cancer.

  Study phs001385

• Renal_habitat_RNA

  This project is correlating the molecular profiling of renal tumours with multiparametric and 13C-MRI including by 13C-MRSI.

  Study EGAS00001003704

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• COLO-829/COLO-829BL

  COLO-829 is a publicly available immortal cancer cell line and COLO-829BL is a lymphoblastoid cell line derived from the same patient

  Dataset EGAD00000000055

• UNC Tumor Donation Program Set 2021

  The goal of this study is to study gene expression patterns in primary, metastatic tumors, and normal tissues.

  Study phs002429

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal