11944 results for "coins fc Visit Buyfc26coins.com for latest FC 26 coins news..yU53"

in 23.55 milliseconds.

• Center for Common Disease Genomics [CCDG] Neuropsychiatric: Autism Spectrum Disorder (ASD) – Whole Exomes

  The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of 1) undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases, 2) understanding how best to design rare variant studies for common disease, and 3) developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The goal of the Autism Spectrum Disorder (ASD) program is to work together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes.

  Study phs002502

• LySeqST: A targeted sequencing assay for robust genomic classification of diffuse large B-cell lymphoma

  Diffuse large B-cell lymphoma (DLBCL) is a biologically heterogeneous disease. Two genomic classification systems, LymphGen and DLBclass, are capable of reproducibly classifying single tumors into subtypes with prognostic relevance in the context of standard-of-care R-CHOP chemoimmunotherapy. Preliminary data from subgroup analyses of clinical trials suggest that the distinct biological features are targetable with drugs that exploit subtype-specific vulnerabilities, and large clinical trials are being designed to test this hypothesis. Although whole exome sequencing (WES) remains the gold standard for each of these classification systems, many laboratories may opt for smaller targeted sequencing panels that reduce costs associated with sequencing, data storage, and processing. Here, we describe the design and validation of a targeted sequencing panel (LySeqST) that captures the genomic features required specifically for LymphGen classification. We perform in silico and real-world validation vs. WES data and demonstrate that LySeqST can be used to accurately classify DLBCL tumors. In an unselected population-based cohort, we determine the real-world proportions and validate the prognostic relevance of LymphGen subtypes, confirming that only tumors expressing the dark zone gene expression signature are consistently associated with inferior outcomes. Our results support the use of LySeqST for accurate genomic classification of DLBCL.

  Study EGAS50000001601

• Rapid identification of somatic genome rearrangements as personalized biomarkers for blood-based cancer monitoring

  Increasing evidence shows the value of circulating tumour DNA (ctDNA) to detect cancer and monitor its progression. Somatic genomic structural variations (SVs) are promising personalized biomarkers for sensitive and specific detection of ctDNA in liquid biopsies. However, accurate, affordable, and fast identification of such SV biomarkers is challenging, which hinders routine use in the clinic. Here, we demonstrate a novel approach - termed SHARC - for rapid discovery of somatic SV breakpoints as personalized tumour biomarkers. SHARC combines low-coverage cancer genome sketching by using Oxford Nanopore portable sequencing with a random forest classification and a dedicated filtering pipeline to enrich for somatic SVs. Our method leverages the real-time and long-read capabilities of Nanopore sequencing to identify somatic SV breakpoints at nucleotide resolution from a tumour biopsy within two days. We applied SHARC to tumour samples of high-grade ovarian and prostate cancer and validated on average 10 somatic SVs per sample with the use of PCR mini-amplicons. Finally, we demonstrate that these somatic SV biomarkers can be used to detect tumour presence from liquid biopsies in a quantitative manner and we retrospectively monitored treatment response in patients with prostate cancer, demonstrating its potential benefit for clinical practice.

  Study EGAS00001003963

• Bisulfite-converted duplexes for the strand-specific detection and quantification of rare mutations

  The identification of mutations that are present at low frequencies in clinical samples is an essential component of precision medicine. The development of molecular barcoding for next generation sequencing has greatly enhanced the sensitivity of detecting such mutations by massively parallel sequencing. However, further improvements in specificity would be useful for a variety of applications. We herein describe a technology (BiSeqS) that can increase the specificity of sequencing by at least two orders of magnitude over and above that achieved with molecular barcoding and can be applied to any massively parallel sequencing instrument. BiSeqS employs bisulfite treatment to distinguish the two strands of molecularly barcoded DNA; its specificity arises from the requirement for the same mutation to be identified in both strands. Because no library preparation is required, the technology permits very efficient use of the template DNA as well as sequence reads, which are nearly all confined to the amplicons of interest. Such efficiency is critical for clinical samples, such as plasma, in which only tiny amounts of DNA are often available. We show here that BiSeqS can be applied to evaluate transversions, as well as small insertions or deletions, and can reliably detect one mutation among >10,000 wild type molecules.

  Study EGAS00001002406

• Hypoxia acts as an environmental cue for the human TRM differentiation program

  Tissue-resident memory T-cells (TRM) provide frontline defense against infectious diseases and contribute to anti-tumor immunity; however, aside from the necessity of TGF-β, knowledge regarding TRM-inductive cues remains incomplete, particularly for human cells. Oxygen tension is an environmental cue that distinguishes peripheral tissues from the circulation and here, we demonstrate that differentiation of human CD8+ T-cells in the presence of hypoxia and TGF-β1 led to the development of a TRM phenotype, characterized by a greater than five-fold increase in CD69+CD103+ cells expressing human TRM hallmarks and enrichment for endogenous human TRM gene signatures, including increased adhesion molecule expression and decreased expression of genes involved in recirculation. Hypoxia and TGF-β1 synergized to produce a significantly larger population of TRM phenotype cells than either condition alone, and comparison of these cells from the individual and combination conditions revealed distinct phenotypic and transcriptional profiles, indicating a programming response to milieu rather than a mere expansion. Our findings identify a previously unreported cue for the TRM differentiation program and can enable facile generation of human TRM phenotype cells in vitro for basic studies and translational applications such as adoptive cellular therapy.

  Study EGAS00001005286

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

  Study phs002809

• EGA metadata schema

  EGA Schemas In this page, you will find information on how the European Genome-phenome Archive (EGA) manages its metadata standards using both XML Schema Definition (XSD) and JavaScript Object Notation (JSON) formats. If you are not sure what this means, you may want to explore our brief metadata introduction. This information may be of your interest if you are planning to learn more about how the EGA is built and how to wrap around it for other processes. Nevertheless, if you are a common user (e.g. submitter or requester), you would not have to worry about these schemas nor their format, since they are implemented in user-friendly ways for you. Metadata standards are rules that define how to format and structure data of metadata objects (i.e. entities), like EGA's samples or experiments in a consistent manner. These objects are the nodes of the metadata model of the EGA (Figure 1). Figure 1. Diagram of EGA's metadata model. The model's building blocks are objects (e.g. sample), which can reference each other (e.g. an experiment referencing the used samples). Once your files are uploaded, they can also be referenced by Runs and Analyses. The submission object is an object itself that compiles many others. At EGA, we inherit our metadata schemas from the European Nucleotide Archive (ENA), and we have expanded them to include bespoke objects such as "Policy", "Dataset", and "DAC" (Data Access Committee) for our specific use-case: handling sensitive human data. See below a list of all our metadata objects and some context for each. Metadata Object EGA accession Description Examples of metadata fields Study EGAS… Information about the study Study type, study title, study abstract… Sample EGAN… Information about the used samples in the experiment or analysis Taxon ID, scientific name, biological sex, phenotype… Experiment EGAX… Information about the performed experiment Used libraries, sequencing platform, reference to the used samples… Analysis EGAZ… Contains information about the analysis Type of analysis, used assembly, reference sequence… Run EGAR… The run holds information about the files containing the raw reads generated in a run of sequencing Platform, spot descriptor, raw file references… DAC EGAC… Contains information about the Data Access Committee (DAC) DAC contacts, contact emails… Policy EGAP… Contains the Data Access Agreement (DAA) and policy which its usage complies with Policy text, data use ontologies (DUO) codes… Dataset EGAD… Contains the collection of runs/analysis to be subject to controlled access Dataset type, compilation of Run's and Analysis' IDs There are two different sets of schemas, based on their formats, in which the EGA accepts metadata: XSDs (for XML files) and JSON Schemas (for JSON files). EGA's XML Schema Definition . When programmatic submissions are pushed through the European Bioinformatics Institute (EBI) system, XML format is used. The schemas that are applied for this format are defined in XML Schema Definition (XSD) files, which can be found at ENA's GitHub repository. You can find more information on how to validate and submit your data programmatically in our programmatic submission documentation. Furthermore, see at our GitHub repository some XML examples with either made-up values (similar to what you would submit) or descriptive values for each field (just for documentation). EGA's JSON Metadata Schemas . When programmatic submissions are pushed through the Centre for Genomic Regulation (CRG) system, JSON format specifications are used instead. See the full JSON specifications for further details. In conclusion, the EGA metadata schemas are crucial for maintaining the quality and consistency of submitted data. By understanding and following the rules outlined in these schemas, you can ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource. Sample checklists Besides the standards in our schemas, we have another layer called Sample checklists. These are another system that the EGA inherits from ENA, and specifies what attributes are required or allowed for a sample object. The EGA uses these checklists to enforce that, for example, a sample object has the three mandatory attributes: subject ID, sex and phenotype of the individual the sample was taken from. When you submit to EGA, our checklist is automatically selected by default.

  Documentation submission/metadata/ega-schema

• TK-EPN862 - Patient-dervied xenograft model of Posterior Fossa A Ependymoma - RNAseq

  Ependymomas (EPN) are the third most common malignant brain cancer in children. Treatment strategies for pediatric EPN have remained unchanged over recent decades, with 10-year survival rates stagnating at just 67% for children aged 0-14 years. Moreover, patients who survive treatment for the most common subtype of pediatric EPN (posterior fossa A (PFA)), often suffer long-term neurological side effects as a result of therapy. It is evident that there is a need for safer, more effective treatments for pediatric EPN patients. There are ten distinct subgroups of EPN, each with their own molecular and prognostic features. To identify and facilitate the testing of new treatments for EPN, in vivo laboratory models representative of the diverse molecular subtypes are required. Here, we describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of PFA EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using immunohistochemistry, DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. Both patient and PDOX tumors classified as PFA EPN by methylation profiling, and shared similar histological features consistent with this molecular subgroup. RNA sequencing revealed that gene expression patterns were maintained across the primary and metastatic tumors, as well as the PDOX. Copy number profiling revealed gains of chromosomes 7, 8 and 19, and loss of chromosomes 2q and 6q in the PDOX and matched patient tumor. No clinically significant single nucleotide variants were identified, consistent with the low mutation rates observed in PFA EPN. Overexpression of EZHIP RNA and protein, a common feature of PFA EPN, was also observed. Despite the aggressive nature of the tumor in the patient, this PDOX was unable to be maintained past two passages in vivo. Others who have successfully developed PDOX models report some of the lowest success rates for EPN compared to other pediatric brain cancer types attempted, with loss of tumorigenicity not uncommon, highlighting the challenge in propagating these tumors in the laboratory. Here, we discuss our collective experiences with PFA EPN PDOX model generation and propose potential approaches to improve future success in establishing preclinical EPN models

  Study EGAS00001006844

• University of Washington Center for Mendelian Genomics (UW-CMG): Atrioventricular Septal Defects (AVSD) Study

  The Centers for Mendelian Genomics project uses next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian conditions. By discovering genes that cause Mendelian conditions, we will expand our understanding of their biology to facilitate diagnosis and new treatments.

  Study phs001774

• ATAC sequencing raw data files of human Treg cell subsets

  Assay for Transposase-Accessible Chromatin using sequencing (ATAC) sequencing of human CD38+, HLA-DR+, CD38+ HLA-DR+, and CD38- HLA-DR- regulatory T (Treg) cell subsets sorted from peripheral blood pooled from 4 healthy donors. After isolation and purification of Treg cell subsets with flow cytometry, samples were frozen and transferred to Active Motif for ATAC sequencing. The dataset contains one raw sequencing file (fastq) of accesible regions for each of the above-mentioned Treg cell subsets.

  Dataset EGAD50000000664

• RNA-seq

  Our cohort represents infants with ALL in whom KMT2Ar was not detected by FISH or by standard cytogenetics. Whole-transcriptome sequencing (WTS) libraries were prepared using the NEBNext Ultra II RNA Directional library kit for samples with at least 100ng RNA (n=19), the Clontech double stranded cDNA conversion kit plus the Nextera XT library protocol for samples with less than 100ng RNA (n=4), or ribodepletion using NEBNext rRNA Depletion Kit v2 (Human/Mouse/Rat) for Total RNA (n=1). Libraries were paired-end sequenced using the Illumina HiSeq 2500.

  Dataset EGAD50000000595

• BELLINI clinical trial bulk RNA-Seq data: cohorts A, B & С

  RNA-Seq data of 78 breast cancer primary tumors obtained from 45 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (15 patients, 25 samples) received nivolumab for 4 weeks, patients in cohort B (15 patients, 28 samples) received nivolumab + ipilimumab for 4 weeks, and patients in cohort C (15 patients, 25 samples) received nivolumab + ipilimumab for 6 weeks. The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000.

  Dataset EGAD50000000808

• Profiling of human fecal microbiota for succinate consumption

  The objective of this study was to identify the bacterial taxa responsible for succinate consumption in human gut microbiomes. We enriched fresh stool from healthy donors in growth medium with and without supplemented succinate. We then measured metabolite concentrations and bacterial composition in the stool and enrichment samples.

  Study EGAS50000000519

• RNA-Seq Brest Patient-derived Tumor Organoids

  This dataset includes 14 RNASeq samples from 8 patients. For some patients, organoids at different passages have been profiled. They can be identified by their alias, composed of the following structure: <subjectId>_O<organoid_number>_<passage>_RNA. For example, ICSBCS002_O1_1_RNA indicates the earlier passage of organoid 1 for subject ICSBCS002, and ICSBCS002_O1_2_RNA indicates the later passage. Additionally, WCM2137_O1_RNA and WCM2137_O2_RNA indicate two organoids (O1 and O2) derived from different tissues. More information about the passages and tissues can be found in the sample information table.

  Dataset EGAD50000000960

• Illumina GSA-MD v3 genotyping arrays for 183 samples

  Genotyping arrays for 183 samples from patients with a neuroendocrine tumor of the small intestine. All samples have been hybridized on Illumina GSA-MD v3 arrays with standard automated protocols. Reading of the chips was performed on Illumina iScan+ scanners and this file is the result of primary analysis done using Illumina GenomeStudio software. It contains data for 147 tumors, 2 adenomas, 1 lymph node, 19 mesenteric nodules, 6 liver metastasis and 8 normal ileum samples.

  Dataset EGAD50000000905

• Sequencing data of the ampulla and fimbriae of the fallopian tube in pre-menopausal women

  A total of 10 pre-menopausal patients were recruited for this study. Sequencing of both the fimbriae and ampullary region of the fallopian tubes was performed using 10x Genomics single-cell RNA-seq and ATAC-seq. For one patient, data were sequenced across 4 lanes, while the remaining patients' data were sequenced in 2 lanes each, resulting in a total of 44 sequencing datasets for each platform.

  Dataset EGAD50000000889

• Clinical Outcomes for 344 Diffuse Large B-Cell Lymphoma Patients

  This dataset contains clinical outcomes for 344 Diffuse Large B-Cell Lymphoma patients. For each subject we have recorded AGE (binarized: > 60, <= 60), SEX (male or female), LDH (serum lactate dehydrogenase), ECOG (Performance status 3 or 4), STAGE (Disease stage III or IV according to the Ann Arbor staging system), EXBM (Two or more extranodal sites of disease (outside of a lymph node), BSYMP (Presence of B symptoms), and BM (Bone marrow involvement). All data are delivered as a single XLSX file with one row per patient.

  Dataset EGAD50000001536

• Genetic analysis in monozygotic twins discordant for bipolar disorder

  To identify genes relevant to bipolar disorder, an exome sequence analysis was conducted in 3 pairs of healthy monozygotic twins as control twins in this study. In addition to this data set, an exome sequence analysis was also conducted in several monozygotic twins discordant for bipolar disorder.

  Study JGAS000014

• comprehensive genetic analysis and database construction for head and neck cancer

  The main purpose is to conduct comprehensive genetic analysis of head and neck malignant tumor tissue and patient-derived blood, and to construct a database for it. By analyzing these databases, we aim to clinically identify recurrence and metastasis prediction markers and establish new molecular target therapies.

  Study JGAS000214

• RRBS of 58 pleural mesothelioma samples (Paired-end)

  The dataset contains RRBS data (bam files) for 58 pleural mesothelioma samples. The samples were sequenced on NovaSeq6000 (Illumina, San Diego, CA) in paired-end 150bp mode. RRBS raw reads were trimmed for adaptor sequences using trim galore (v. 0.6.5) (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) and filtered for low-quality sequences using fastQC (v. 0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). High quality trimmed reads were mapped to the Human reference genome (UCSC genome assembly GRCh38/hg38) using Bismark (v. 0.22.3) with default parameters.

  Dataset EGAD50000002129

• TTFields Glioblastoma Data Access Committee, Charité – Universitätsmedizin Berlin

  This Data Access Committee is responsible for reviewing and approving data access requests for genomic and associated clinical data from patients with glioblastoma, IDH wildtype, treated with surgery, standard chemoradiotherapy and Tumor Treating Fields at Charité – Universitätsmedizin Berlin. The DAC ensures that any data use is consistent with the patients’ informed consent, the study’s ethical approval and applicable data protection regulations. Approved applicants may use the data only for biomedical research on brain tumours and related methods, must not attempt re-identification of participants, and may not share the data with unauthorized third parties

  Dac EGAC50000000843

• Transcriptomics for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002236

• CEITEC DAC

  A CEITEC Data Access Committee (DAC) is a body of one or more named individuals who are responsible for data release to external requesters. The members of DAC are selected members of research groups and their respective leaders. Multiple datasets may be affiliated to a single DAC. DAC continues communication with requester to understand the purpose of use, i.e. research setting the dataset is envisioned for by requester, to identify if data sharing is possible directly under current conditions for the dataset, or actions such as re-consenting is needed and desirable to accommodate the proposed research setting/data use.

  Dac EGAC50000000049

• Long-read sequencing identifies a common transposition haplotype predisposing for CLCNKB deletions

  Long-read whole genome sequencing, long-read long-range PCR sequencing, targetted long fragment long-read sequencing data of the CLCNKA/CLCNKB locus in 27 Bartter syndrome patients. Multiple different deletion alleles are identified and a new common transposition haplotype predisposing for CLCNKB deletions is described.

  Study EGAS00001007339