12377 results for ""statistically+reactive"+taxa+in+microbial+community"

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• The Gut Microbiome of liver transplant recipients – Cross-sectional + Longitudinal (renal and liver)

  TransplantLines is designed as a single-center, prospective cohort study and biobank including all different types of solid organ transplant recipients as well as living organ donors. In the TransplantLines gut microbiome study the gut microbiome of solid organ transplant recipients is characterized and linked to clinical phenotypes. This batch contains the cross-sectional data from liver transplant recipients and longitudinal data from renal and liver transplant recipients.

  Study EGAS00001006258

• GENEVA Genes and Environment Initiatives in Type 2 Diabetes (Nurses' Health Study/Health Professionals Follow-up Study)

  Type 2 diabetes mellitus (T2D) affects approximately 21 million individuals in the U.S., or almost 10% of the U.S. adult population. Because diabetes is determined by both genetic and environmental factors, a better understanding of the etiology of diabetes requires a careful investigation of gene-environment interactions. The Nurses' Health Study (NHS) and Health Professionals' Follow-up Study (HPFS) are well-characterized cohort studies of women and men for whom stored blood and DNA samples are available as well as detailed information on dietary and lifestyle variables. The major goals of the project include: 1. To conduct a GWA analysis among 3,000 cases of T2D and 3,000 healthy controls in NHS/HPFS cohorts. 2. To use information on the joint effects of genes and a list of carefully selected environmental exposures at the initial screening stage to test gene-environment interactions. This approach optimizes our power to detect variants that have a sizeable marginal effect and those with a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. For this analysis, we have developed a joint test of genetic marginal effect and gene-environment interaction. This flexible two-degree-of-freedom test generally provides greater power than standard methods and has the potential to uncover both marginal genetic effects and stratum-specific effects. The Version 1 (v1) dbGaP release of data from the GENEVA Diabetes Study (NHS/HPFS) includes data from the NHS only. The Version 2 (v2) dbGaP release includes data from both the NHS and HPFS. 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 type 2 diabetes mellitus through large-scale genome-wide association studies of well-characterized cohorts of nurses and health professionals. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000091

• A Phase I/II Trial of Sirolimus (Rapamune®) and Cyclosporine in Patients with Refractory Aplastic Anemia

  The most successful treatment for aplastic anemia is bone marrow transplantation. However, few patients are eligible for this procedure. For others, treatment usually consists of immunosuppressive agents, such as antithymocyte globulin (ATG) and cyclosporine. Unfortunately, even with immunosuppressive therapy, relapse is common. New combinations of medications may offer alternative and more effective treatment options. Sirolimus and cyclosporine are two drugs routinely used to suppress the immune system and prevent rejection in patients who have received organ transplants. While cyclosporine has been proven effective for treating aplastic anemia, sirolimus has not been tested for this disease. This study will evaluate the safety and efficacy of sirolimus in combination with cyclosporine for treating individuals with aplastic anemia that have not responded to other treatments. This study will last at least 6 months. Participants will first be screened to verify diagnosis of aplastic anemia. The screening will include a physical examination, blood test, bone marrow biopsy from the pelvic bone, and review of medications and medical history. Individuals who are eligible will then start the first treatment period. Participants will receive two medications: cyclosporine will be taken twice a day and sirolimus will be taken once a day. Depending on side effects, the dose of either drug may be temporarily stopped or lowered. On Day 1, blood will be drawn and females will undergo a pregnancy test. Subsequent study visits will occur weekly for the first month, every 2 weeks for 2 months, and then once a month for the remainder of the study. Each visit will include a physical examination, vital sign assessment, and review of side effects and medications. Blood tests will be performed weekly for the first 3 weeks, and then every 2 weeks. After 6 months of treatment, if a participant has shown improvements in disease status without major side effects, the treatment will continue. Over time the doses may be lowered. If a participant has not improved while on the study medication, treatment will stop at 6 months. Whenever treatment is discontinued, the participant will again undergo a physical examination, blood tests, and bone marrow biopsy.

  Study phs000695

• Discovering the Genetic Basis of Human Neuroblastoma: A Gabriella Miller Kids First Pediatric Research Program (Kids First) Project

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Children with disseminated neuroblastoma have a very high risk of treatment failure and death despite receiving intensified chemotherapy, radiation therapy and immunotherapy. The long-term goal of our research program is to ultimately improve neuroblastoma cure rates by first comprehensively defining the genetic basis of the disease. The central hypothesis to be tested here is that neuroblastoma arises largely due to the epistatic interaction of common and rare heritable DNA variation. Here we will perform a comprehensive whole genome sequencing of 563 quartets of neuroblastoma patient germline and diagnostic tumor DNAs and germline DNAs from both parents. The case series was recently collected through a Children's Oncology Group epidemiology clinical trial and is robustly annotated with complete demographic (age, sex, race, ethnicity), clinical (e.g. age at diagnosis, stage, risk group), epidemiologic (parental dietary and exposure questionnaire) and biological (e.g. tumor MYCN status and multiple other tumor genomic measures) co-variates. Subjects were consented for genetic research and DNA is immediately available for shipment for sequencing. We propose Illumina-based whole genome sequencing in the 593 "trio" germline samples (Aim 1; due to missing parent: 487 full neuroblastoma triads, 106 child-single parent dyads = 1673 whole genome sequences) and matched diagnostic tumor DNA (Aim 2; N=366) at 30x sequencing depth (N=2039 whole genome sequences). Also in Aim 2 we will perform whole exome (100x) and RNA sequencing on the 366 tumor DNA and 228 tumor RNA samples from this cohort. Finally, we propose a pilot study of structural variation using long-range sequencing in 10 non-overlapping tumor samples chosen based on potentially relevant chromosomal alterations discovered with conventional NGS. Thus, a total of 2277 individual samples and 2655 sequences will be generated. We will use our established analytic pipeline that is currently being used to study the germline genomes of all cases sequenced through the NCI supported Therapeutically Applicable Research to Generate Effective Treatments program. We plan a three-stage analytic approach, first focusing on classic de novo and inherited Mendelian damaging alterations. We will next integrate our extensive epigenomic data from human neuroblastoma cell lines and genome-wide association study data (N=5,703 neuroblastoma cases to date) to guide a comprehensive assessment of noncoding variants that influence tumor initiation with a recently established analytic pipeline. Finally, we will utilize the tumor DNA analyses to inform relevance via somatic gain or loss of function effects at the sequence and/or copy number levels. All data generated in this project will be immediately placed into the Genomic Data Commons (GDC) and we will compute within this environment by importing our analytic pipelines into the GDC. These data will be fully integrated into the Kids First Data Resource and freely shared with all academically qualified petitioners. This comprehensive data set derived from a large and richly phenotyped series of neuroblastoma DNA quartets will be integrated with existing germline and/or tumor genomic data from over 6,000 neuroblastoma subjects (but none with matched patient-parent germline sequencing data) to provide an unparalleled opportunity to comprehensively discover the genetic basis of neuroblastoma.

  Study phs001436

• Korea Epigenome Project(KEP), Korea National Research Institute of Health(KNIH)

  The KEP was launched in 2012 to produce 50 epigenomic sets on Korean chronic diseases related target cells with the participation on Internationsl Human Epigenome Consortium(IHEC) of which focus is constructing 1000 reference epigenome map on 250 human cell type. The objective of the KEP was to provide a comprehensive epigenomic map of Korean chronic disease-related target tissues. Single cells were isolated from the pancreas, fat and kidney. Islet, ductal, acinar, and beta cells from the pancreas were purified into a single homogenous cell type using flow-assisted cell sorting technique. Adipocytes and pre-adipocytes were purified from fat, using Percoll gradient centrifugation technique. Mesangial, distal tubule, proximal tubule, podocytes, and collecting duct cells from the kidney were collected using mechanical sieving and immunostaining methods. Each cell type was derived from normal tissue or those with diabetes, obesity, or chronic kidney disease. Sixty reference epigenome datasets of pancreatic, fat, kidney cells were produced. Cell types such as the islets, and beta from the pancreas, adipocytes, pre-adipocytes from fat tissue, podocyte, mesangial, tubules from kidney were used for primary target to produce a Korean metabolic reference epigenome. And the bisulfite converted-whole genome sequencing, Infinium 450k DNA methylation bead array, mRNA, miRNA-Sequencing were performed to produce a comprehensive epigenomic map. The aim of roadmap reports is preparation of Long-term and Mid-term Technology Roadmaps for Korean Human Epigenome Project towards a competitive execution of International Epigenome Project and successful expansion of the research outcomes. Roadmap reports reviewed on recent technological development of DNA methylation and histone modification analysis, emerging new trends in epigenome medicine, plans for hardware and software analysis systems aimed to epigenome analysis, medical expert opinion on target cells and isolation scheme, bioinformatics expert opinion on analytical tools, new ideas for a putative epigenome studies, trends in single cell epigenome analysis. In conclusion, roadmap report suggested several projects for the future KNIH epigenome research in collaboration with epigenome research group. These are including refocusing the goals of KNIH-driven research in identification of disease mechanism, development of new studies on GWAS-EWA, higher priority on the epigenomic studies of human primary cells, establishment of collaborative relationship with tissue banking centers, establishment of mapping centers and data analysis portals, establishment of Korean Epigenome Research Consortium, establishment of steering committee governing both research and funding, launching of additional funding for epigenomic researches.

  Study EGAS00001001774

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• EGAD00010000628

  The TEENAGE study target population comprised adolescent students aged 13 to 15 years attending the first three classes of public secondary schools located in the wider Athens area of Attica.

  Dataset EGAD00010000628

• EGAD00010000630

  The TEENAGE study target population comprised adolescent students aged 13 to 15 years attending the first three classes of public secondary schools located in the wider Athens area of Attica.

  Dataset EGAD00010000630

• TB-DAR Genotyping Study

  Active TB patients (sputum smear-positive and GeneXpert-positive) recruited at the Temeke District Hospital in Dar es Salaam, Tanzania, as part of a prospective study that ran between November 2013 and June 2022.

  Dataset EGAD00010002507

• GCAT| WGS Structural Variants Catalog V1

  This resource contains the SV annotations using the AnnotSV tool. The description of annotations can be found in AnnotSV web page https://lbgi.fr/AnnotSV/ or GCAT-BSC web page: http://cg.bsc.es/GCAT_BSC_iberianpanel

  Dataset EGAD00010002152