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• UK10K COHORT TWINSUK

  The UK10K project proposes a series of complementary genetic approaches to find new low-frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome-wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein-coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will directly analyse quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The TwinsUK samples will be part of the cohort study and will undergo whole genome sequencing. For further information with regard to this cohort please contact Brent Richards (brent.richards@kcl.ac.uk) or Nicole Soranzo (ns6@sanger.ac.uk).

  Study EGAS00001000108

• UK10K NEURO ASD BIONED

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The BioNED (Biomarkers for Childhood onset neuropsychiatric disorders) study has been carrying out detailed phenotypic assessments evaluating children with an autism spectrum disorder. These assessments included ADI-R, ADOS, neuropsychology, EEG etc. There are 56 DNA samples from this study (25 extracted from blood). For further information with regard to this cohort please contact Patrick Bolton (patrick.bolton@kcl.ac.uk).

  Study EGAS00001000111

• RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.

  Background: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called `epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. Results: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder. Conclusions: Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity.

  Study EGAS00001002484

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary with Neuroendocrine Differentiation

  PURPOSE: Cancer of unknown primary (CUP) is a group of metastatic tumors in which the standard diagnostic work-up fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large since their tumors might have actionable driver mutations that can provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomics analyses could inform on the origin of the tumor. PATIENT AND METHODS: Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a PDX mouse model and bioinformatics was used to identify an actionable mutation, predict resistance development to the targeted therapy, and to correctly diagnose the origin of the tumor. The Cancer Genome Atlas was used to benchmark the bioinformatics workflow. RESULTS: Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatics workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from The Cancer Genome Atlas. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION: Comprehensive genomics analyses could inform on the origin of tumors in patients suffering from CUP.

  Study EGAS00001003026

• Disease and phenotype relevant genetic variants identified from histone acetylomes in human hearts

  Identifying genetic markers for heterogeneous complex diseases such as heart failure has been challenging, and may require prohibitively large cohort sizes in genome-wide association studies (GWAS) in order to demonstrate statistical significance1. On the other hand, chromatin quantitative trait loci (QTL), elucidated by direct epigenetic profiling of specific human tissues, may contribute towards prioritising variants for disease-association. Here, we captured non-coding genetic variants by performing enhancer H3K27ac ChIP-seq in 70 human control and end-stage failing hearts, mapping out a comprehensive catalogue of 47,321 putative human heart enhancers. 3,897 differential acetylation peaks (FDR < 0.05) pointed to recognizable pathways altered in heart failure (HF). To identify cardiac histone acetylation QTLs (haQTLs), we regressed out confounding factors including HF disease status, and employed the G-SCI test2 to call out 1,680 haQTLs (FDR < 0.1). A subset of these showed significant association to gene expression, either in cis (180), or through long range interactions (81), identified by Hi-C and Hi-ChIP performed on a subset of hearts. Furthermore, a concordant relationship was found between the gain or disruption of specific transcription factor (TF) binding motifs, inferred from alternative alleles at the haQTLs, associated with altered H3K27ac peak heights. Finally, colocalisation of our haQTLs with heart-related GWAS datasets allowed us to identify 62 unique loci. Disease-association for these new loci may indeed be mediated through modification of H3K27-acetylation enrichment and their corresponding gene expression differences.

  Study EGAS00001003586

• Lung Plasma rearrangement screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000367

• A model for predicting response to PD-1 inhibitors in NSCLC

  Whole exome sequencing was used to examine the impact of human leukocyte antigen B44 in a non-small cell lung cancer cohort treated with single agent pembrolizumab with over five years of follow-up.

  Study phs002244

• Whole-genome sequencing with complement C1s deficiency linked to systemic lupus erythematosus

  This dataset includes two FASTQ files (R1 and R2) from an Illumina germline nuclear DNA whole-genome sequencing run of a single sample. The sample corresponds to a 34-year-old male with a rare deficiency in complement component C1s, linked to systemic lupus erythematosus (SLE). Genomic analysis revealed two novel mutations in the C1S gene.

  Dataset EGAD50000000988

• Novel genome editing strategies to uncover genotype-phenotype correlations in Polycystic Kidney Disease: a proof-of-concept

  Bulk RNA-seq of genome-edited HEK293T cell lines engineered to model specific PKD1 variants. This dataset enables the exploration of genotype-phenotype correlations in Polycystic Kidney Disease (PKD)

  Study EGAS50000001188

• GILD-ExomeSeq-PTNHL

  This study is meant to gain further knowledge in haematological cancers. Patients samples (mainly DNAs or PCR products) from haematolocical cancer patients will be sequenced, and the outputs will be correlated to their diagnosis and/or prognosis; the findings may also add more insight into the understanding of biology in this type of tumour. We will be sequencing Primary Testicular Lymphomas (PTL) to identify genetic drivers of this rare cancer

  Dataset EGAD00001001986

• POT1 splice site mutant analysis

  We are interested in the contribution mutations in the Shelterin complex protein POT1 may have to the development of melanoma. We have identified a patient who carries a splice site mutation in POT1 and as part of our analysis of this gene we aim to sequence the transcriptome of this patient to see how this mutation influences splicing. RNA has been obtained from lymphocytes collected from the patient.

  Dataset EGAD00001000786

• PLCRC study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from Colorectal cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000947

• RNAseq of ribosomal footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Dataset EGAD00001001930

• Analysis of Papilloma Infiltrating T cells from an Exceptional Responder to Immunotherapy

  This data corresponds to single cell RNA-seq data of TIL from a young woman with recurrent respiratory papillomatosis who was treated with PD-L1 blockade and experienced durable disease control over a 4+ year period. A HPV6 E2-specific, HLA-B*55 restricted TCR was identified and shown to be present in both the immediate post treatment and 4 year TIL, with a gene expression profile indicative of being a tissue resident memory T cell. 

  Study phs002826

• Evolution of Chronic Lymphocytic Leukemia to Richter's Syndrome (RS)

  Richter's syndrome arising from chronic lymphocytic leukemia is a striking example of an aggressive malignant histology that emerges from indolent cancer. To understand this process, we reconstructed phylogenies based on whole exome sequencing of matched normal, CLL and RS samples. We computationally deconvoluted CLL and RS clones and identified drivers of transformation. We additionally performed whole genome sequencing, whole transcriptome sequencing and single-cell transcriptome sequencing to understand the mutational signatures, genome-wide events and gene expression changes associated with transformation.

  Study phs002458

• Genomic Data Access Committee for Early and Late Onset Colorectal Cancer Study

  This Data Access Committee (DAC) manages access to genomic data generated from the study "A Clinically and Genomically Annotated Early Onset Colorectal Cancer and Late Onset Colorectal Cancer." The study focuses on identifying the distinct genomic profiles of early-onset colorectal cancer (EOCRC) compared to late-onset colorectal cancer (LOCRC) through whole-genome sequencing (WGS) of both tissue and blood samples. The DAC is responsible for reviewing and approving access requests from researchers who wish to utilize this data for non-commercial, academic purposes related to colorectal cancer research. The committee ensures that all data access is granted in compliance with ethical standards and that the data is used solely for the approved research objectives. Researchers requesting access to this data must provide a detailed research proposal, institutional review board (IRB) approval, and demonstrate relevant expertise in genomic research. All data will be stored in secure, encrypted environments, and any further sharing or use of the data requires additional DAC approval.

  Dac EGAC50000000359

• Observational studies using advanced analytical techniques to understand the biological functions of kidney component cells

  The purpose of this study is to establish a foundation for understanding the functions of kidney component cells and the biology of renal disease. Single cell and spatial transcriptome analyses of human kidney component cells will be performed to analyze the gene expression profiles of those cells and explore their relationship between the gene expression profiles and clinical parameters. The research foundation established here is worthwhile for understanding disease mechanisms in the kidney or discovering novel therapeutic drugs for renal disease.

  Study JGAS000736

• RNA sequencing of CD8 T cells from melanoma patients prior to and during checkpoint immunotherapy and untreated healthy controls

  We are interested in inter-individual variation in transcriptional response to immune checkpoint blockade. We have analysed poly A purified RNA expression from CD8 T cells (297 transcriptomes in total) isolated from metastatic melanoma patients (n=106) prior to and during treatment with either single agent (Pembrolizumab) or combination (Ipilimumab/ Nivolumab) immune checkpoint blockade. We compare expression at different stages of treatment and additionally contrast this with that from healthy controls (n=68).

  Study EGAS00001004081

• Investigating genetic susceptibility to rheumatic heart disease in Oceania

  This case-control study investigated susceptibility to rheumatic heart disease in over 3,000 individuals recruited across eight Oceanian countries. Cases were patients with rheumatic heart disease and controls were members of the general population. In addition to the Illumina HumanCore-24 BeadChip genotyping, a subset of 128 samples were analysed using the higher density Illumina HumanOmniExpressExome BeadChip of which 64 were also analysed using low coverage sequencing with the Illumina HiSeq 4000 platform.

  Study EGAS00001001881

• Lung cancer organoids addition

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004943

• Functional genomics approaches to understand osteoarthritis (2019-08-01)

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). We will obtain diseased and non-diseased cartilage as well as other disease-relevant tissue following TJR, coupled with a blood sample. We will generate genotype data and will characterise the pairs of diseased and non-diseased tissue samples in terms of methylation, transcription (RNASeq) and expression (quantitative proteomics). We will apply integrative approaches to combine information across the omics levels to characterise genes, pathways, and networks that underlie osteoarthritis progression. 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/ . This dataset contains all the data available for this study on 2019-08-01.

  Dataset EGAD00001005215

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006643

• Impact of mutational profiles on response of primary oestrogen receptor-positive breast cancers to oestrogen deprivation

  Presurgical studies allow study of the relationship between mutations and response of estrogen receptor positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in Phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 Controls). In poor responders (based on Ki67 change) we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores   occur in approximately 30% of tumours. In Phase II we combine targeted sequencing on another 28 treated patients with Phase I. We find six genes frequently mutated: PIK3CA, TP53, CDH1, MLL3, ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy.

  Dataset EGAD00001002651