12223 results for "playerauctions fc 26 Visit Buyfc26coins.com for latest FC 26 coins news..HXSQ"

in 38.22 milliseconds.

• Investigating_the_genetics_of_immunity_against_Salmonella_in_humans

  This study entails whole genome sequencing of an interleukin (IL)-12 b-1 receptor-deficient individual who presented with a chronic systemic Salmonella Enteritidis infection that did not resolve with standard IFNg and antibiotic treatment. Whole genome sequencing of the patient’s parents are also included.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 EGAS00001001664

• Paired exome analysis in urothelial carcinoma

  In this study we characterized genomic alterations in two to five metachronous tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth), Ultra deep targeted sequencing (~6,809x mean read depth) and whole transcriptome RNA-seq was performed for all samples. In addition multiregional WES was performed on 8 adjacent regions from a single tumor.

  Study EGAS00001001686

• Genomic Signatures Reveal DNA Damage Response Deficiency in Brain Metastases of Colorectal Cancer

  Brain metastasis (BM) of colorectal cancer (CRC) is rare but lethal, and lacks effective therapies or a good understanding of its genomic landscapes. We conduct an analysis of whole-exome sequencing (WES) and whole-genome sequencing (WGS) data on 19 trios of patient-matched BMs, primary CRC tumors, and adjacent normal tissue to (1) document genomic signatures during the evolution of CRC BM; (2) identify clinically actionable targets for the BM treatment; and (3) identify potential drivers in CRC BM.

  Study EGAS00001003659

• Whole Exome Sequencing of 15 Tumor/Normal pairs of inflammatory hepatocellular adenomas

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors. The present series corresponds to 15 Tumor/Normal pairs of Whole Exome Sequencing (WES) of IHCA samples. Aligned bam files can be both in hg19 (CHC750T/CHC750N; CHC2189T/CHC2189N; CHC2615T/CHC2614N) or hg38 (other samples).

  Study EGAS00001003686

• Boson HCV infected liver bulk RNASeq study

  ACE2 is a receptor for the SARS-CoV-2 and differences in its expression may affect susceptibility to infection. In a genome-wide eQTL analysis using hepatitis C virus-infected liver tissue, we discovered that polymorphism in a type III interferon gene (IFNL4), which eliminates IFN-lambda-4 production, is associated with a two-fold increase in ACE2 RNA expression. Conversely, among genes negatively correlated with ACE2 expression, IFN-signalling pathways were highly enriched and ACE2 was downregulated after IFN-alpha treatment.

  Study EGAS00001004996

• Blood RNA-seq from Mexican DMD patients and healthy controls

  These data are part of a study that aimed to assess the potential of blood RNA-seq to track non-invasively disease progression for DMD. In particular, here we focus on a study designed to compare gene expression in blood from DMD patients to that of healthy controls. These data are analysed in the following manuscript: Signorelli, M., Ebrahimpoor, M. et al. (accepted). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients. To appear in EMBO Molecular Medicine.

  Study EGAS00001004907

• High-grade serous ovarian cancer refined with single-cell RNA-sequencing

  We performed single-cell RNA-sequencing of 18,403 cells unbiasedly collected from 7 treatment-naive HGSOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. Next, we explored which phenotypic clusters correlate with overall survival based on expression of these transcriptomic markers in 1467 bulk RNA-seq tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

  Study EGAS00001004987

• The_British_Autozygosity_Populations_BioResource

  This data set contains whole exome sequences of individuals with self-stated parental relatedness from the East London Genes & Health cohort. Rare frequency functional variants in these healthy individuals will be studied with respect to the genetic health of the participants and loss-of-function analysis of human genes. 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 EGAS00001002742

• Whole genome analysis of mutation hotspots in gastric cancer

  Tissue-specific driver mutations in non-coding genomic regions remain undefined for most cancer types. In this study, we unbiasedly analysed 212 gastric cancer whole genomes to identify recurrently mutated non-coding regions in gastric cancer. Applying comprehensive statistical approa- ches to accurately model background mutational processes, we observe significant enrich- ment of non-coding indels (insertions/deletions) in three gastric lineage-specific genes. We further identify 34 mutation hotspots, of which 11 overlap CTCF binding sites (CBSs).

  Study EGAS00001002872

• Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

  Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no comprehensive and direct accuracy evaluations of these tools is published. Here, we evaluate and determine the precision of five commonly used computational NIPT aneuploidy analysis tools, considering diverse sequencing depth (coverage), arbitrary sequencing read placement, and fetal DNA fraction on clinically validated NIPT samples.

  Study EGAS00001005323

• Molecular analysis of FIT interval colorectal cancers

  To optimize a fecal immunochemical test-based screening program, the rate of missed colorectal cancers (CRCs), so-called FIT-interval CRCs, should be minimized. A specific molecular make-up of those CRCs could be an explanation for those interval CRCs. Knowledge of the molecular make-up of these missed lesions could facilitate more accurate detection of all precursor lesions. In this study we aimed to compare the molecular make-up of FIT-interval CRCs and screen-detected CRCs (SD-CRCs).

  Study EGAS00001004683

• scRNAseq of human primary nasal epithelium differentiated at air-liquid interface exposed to SARS-CoV2

  The nasal epithelium is a plausible entry point for SARS-CoV-2, a site of pathogenesis and transmission, and may initiate the host response to SARS-CoV-2. Antiviral interferon responses are critical to outcome of SARS-CoV-2. Yet little is known about the interaction between SARS-CoV-2 and innate immunity in this tissue. Here we applied single-cell RNA sequencing and proteomics to a primary cell model of human primary nasal epithelium differentiated at air-liquid interface.

  Study EGAS00001005633

• Cell-free DNA and bone marrow samples from myelodysplastic syndromes

  We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA. Sequencing of BM DNA and cfDNA showed a comparable mutational profile and variant allele frequencies (VAF) strongly correlated between both sample types. Our results support the analysis of cfDNA as a promising strategy for performing molecular characterization, detection of chromosomal aberrations and monitoring of MDS patients.

  Study EGAS00001005992

• Single cell multi-omic data of glioblastoma evolution under therapy

  We report a single-cell multi-omics atlas of GBM longitudinal specimens that represents decades of biobanking. We identify novel cell-intrinsic and cell-extrinsic targets for therapy development which we validate in situ and in low-passage patient-derived cell lines. We identify novel genetic correlates of the mesenchymal cellular phenotype. These studies integrate disparate findings in the literature around hypermutation status and immunogenicity as well as the source of the mesenchymal shift at recurrence.

  Study EGAS00001004909

• Single cell RNAseq of lung adenocarcinoma

  Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing as well as single-cell BCR sequencing of cells from 16 LUADs and 47 multi-region normal lung tissues of defined spatial proximities from the tumors. Our multi-region single-cell sequencing analyses unravel cell populations, states, and phenotypes in the spatial and ecological evolution LUAD from the lung that comprise high-potential targets for early interception.

  Study EGAS00001005021

• Clonal dynamics of normal hepatocyte expansions in homeostatic human livers and their association with the biliary epithelium

  BAM files containing paired-end mtDNA sequencing data from morphologically normal human liver. CCO-proficient hepatocytes acquired from livers in which clonal CCO-deficient hepatocyte patches had been previously identified. Individual BAM files are named according to their patch, line and sample location, where PT denotes tissue near to the portal triad (PT), central hepatic vein (CV) and midway between these two structures (Mid). "Stroma" control samples were used for identifying germ-line variants. Sequenced on NextSeq 500 platform.

  Study EGAS00001006962

• This study aims to evaluate the relationship between cardiometabolic risk factors and the most common genetic variation (SNPs)

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey “2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition)”, a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axiom™ 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Study EGAS00001007818

• COVID-19 Severity First Wave of Infection for Severe Patients in Madrid

  We recruited 98 hospitalised patients displaying severe COVID-19 symptoms from the first wave of infection. A stringent exclusion criteria based on non-genetic factors such as age, blood oxygen, radiologic findings and other typical COVID-19 signs was performed. Gingival or peripheral blood samples were taken for 98 individuals and whole exome sequencing performed using ExomeCapture-Seq capture KAPA HyperExome on Illumina machines.

  Dataset EGAD00001008464

• Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis

  Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis. A total of 10 non-PCD patients (ALI day 14), 9 non-PCD patients (ALI day 21), 8 non-PCD patients (ALI day 28), 4 PCD patients (ALI day 14, day 21 and day 28), and 23 PCD patients (ALI day 21). Non-PCD patients and the 4 PCD patients on the three ALI days were sequenced at a depth of 100M reads, the remaining 23 PCD patients were sequenced at a depth of 70M. Overall sequencing design was rRNA depletion and 150bp paired-end.

  Dataset EGAD00001009498

• Tumour sample for patient SA287

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA287

  Dataset EGAD00001009185

• Tumour sample for patient SA588

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA588

  Dataset EGAD00001009194

• Tumour sample for patient SA586

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA586

  Dataset EGAD00001009193

• Tumour sample for patient SA585

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA585

  Dataset EGAD00001009192

• Tumour sample for patient SA530

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA530

  Dataset EGAD00001009191

• Tumour sample for patient SA404

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA404

  Dataset EGAD00001009190

• Tumour sample for patient SA402

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA402

  Dataset EGAD00001009189

• Tumour sample for patient SA398

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009188

• Tumour sample for patient SA395

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA395

  Dataset EGAD00001009187

• Tumour sample for patient SA394

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA394

  Dataset EGAD00001009186

• Tumour sample for patient SA283

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA283

  Dataset EGAD00001009184

• Tumour sample for patient SA279

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA279

  Dataset EGAD00001009183

• Tumour sample for patient SA276

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA276

  Dataset EGAD00001009182

• Tumour sample for patient SA275

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA275

  Dataset EGAD00001009181

• Tumour sample for patient SA274

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA274

  Dataset EGAD00001009180

• Tumour sample for patient SA272

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA272

  Dataset EGAD00001009179

• Tumour sample for patient SA219

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA219

  Dataset EGAD00001009178

• Tumour sample for patient SA218

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA218

  Dataset EGAD00001009177

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• Single Cell Genome Sequence for DLP+ library A95629B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051D passage 1 on DLP+ library A95629B

  Dataset EGAD00001009320

• Single Cell Genome Sequence for DLP+ library A95632A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA1-/- Tp53-/- cell line 184-hTERT-22 L9 83.86 on DLP+ library A95632A

  Dataset EGAD00001009321

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Single Cell Genome Sequence for DLP+ library A95635A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 116.126 on DLP+ library A95635A

  Dataset EGAD00001009324

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• Single Cell Genome Sequence for DLP+ library A95652A

  Single Cell Genome Sequence for immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 on DLP+ library A95652A

  Dataset EGAD00001009326

• 10x Genomics Single Cell Gene Expression for SA1096A

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1096

  Dataset EGAD00001009139

• Spatial transcriptome sequence data from cross section of cancer containing prostates

  Spatial transcriptome sequence data from two tumour containing prostates. Entire cross section of organ divided into cubes to fit spatial transcriptomics arrays. The dataset contains paired-end sequences from 21 sections of 1k array sections and 9 sections of 10x Visium sections for patient 1 as well as 28 sections of 10x Visium sections for patient 2.

  Dataset EGAD00001008644

• Mucosal 16S sequencing data

  16S-V4 rRNA gene sequence data for intestinal biopsies from NCT02749630 trial participants. Biopsies from patients were collected at screening, day 30, and day 85 and prepared for 16SV4 rRNA gene sequencing.

  Dataset EGAD00001008843

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• CCA RNA-seq data (60 CCA, 6 normal, 16 cell-line)

  Fastq files for RNA-seq for 60 CCAs, 6 normal bile duct tissues, 14 CCA cell-lines (including replicates), and 2 normal cholangiocyte cell-lines (including replicates). RNA was extracted using the Qiagen RNeasy Mini kit. Illumina Tru-Seq Stranded Total RNA kit (Illumina, San Diego, California, USA) was used to prepare RNA libraries from 1 µg of total RNA. Paired-end 150 bp sequencing was performed using Illumina HiSeq4000 sequencer with the paired-end 150 bp read option.

  Dataset EGAD00001011998