1169 results for "fut credit Visitez le site Buyfc26coins.com Transaction parfaite et FC 26 coins livrés à l'heure.sArj"

in 10.10 milliseconds.

• Cergentis FFPE-TLC

  In this study, formalin-fixed paraffin-embedded targeted locus capture (FFPE-TLC) sequencing is used as a novel technology for targeted detection of tumor-specific genomic structural variants (SVs) in the primary tumor of 29 colorectal cancer patients with metastatic disease. The tumor region was macrodissected and sequenced for 29 patients, and the "normal" region of the same slide was macrodissected and sequenced for 8 of these patients. SVs were found in the common fragile site (CFS)-associated genes MACROD2, PRKN, FHIT and WWOX as well as SVs caused by three LINE transposable elements. Tumor-specificity of selected SVs was independently verified by droplet digital PCR of tumor tissue DNA and their applicability as plasma circulating tumor DNA biomarkers was demonstrated.

  Study EGAS50000000427

• The_Genomic_Advances_in_Sepsis__GAinS__RNA_seq

  Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 34 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected on the first, third and/or fifth day following ICU admission. RNA was extracted from leukocytes isolated at the bedside using LeukoLOCK kits. We have previously identified sepsis response signatures (SRSs), transcriptomic endotypes that are associated with differential early mortality (Davenport et al, Lancet Respir Med, 2016; Burnham et al, AJRCCM, 2017) and response to treatment in a clinical trial (Antcliffe et al, AJRCCM, 2018). We generated RNA sequencing data on 903 samples, including 134 samples repeated from our previously released microarray data. Libraries were prepared using NEB Ultra II Library Prep kits (Illumina) and sequenced on a NovaSeq 6000. Reads were aligned to the reference genome (GRCh38) using STAR and gene counts quantified using featureCounts (annotation Ensembl v99). Counts were TMM-normalised and log-transformed. Following QC, processed data were available on 864 samples from 667 unique patients.

  Study EGAS00001003772

• Data Access Commitee for Schulte-Schrepping et al., 2020: Severe COVID-19 is marked by a dysregulated myeloid cell compartment

  Dac EGAC00001001684

• GEnomics and Transcriptomics of Human INsulinoma (GETHIN)

  The Genomics and Transcriptomics of Human Insulinoma (GETHIN) The common forms of diabetes - Types 1 and 2 - ultimately result from a deficiency of insulin-producing pancreatic beta cells. The Genomics and Transcriptomics of Human Insulinoma (GETHIN) study was performed in order to identify novel approaches to inducing human pancreatic beta cells to replicate and regenerate. As a corollary, developing drugs that are able to expand human beta cell mass in people with diabetes should reverse diabetes. Unfortunately, identifying druggable pathways that can enhance human beta cell replication has been a major challenge. In 2017, there is only one class of drugs - the harmine analogues - that can induce human beta cells to replicate, and in this case, higher replication rates are desirable. Thus, identifying additional drugs and druggable pathways is a priority in diabetes research. Insulinomas are rare, benign adenomas of the pancreatic beta cell that cause excess insulin production and hypoglycemia: exactly the opposite of Types 1 and 2 diabetes. Beta cell proliferation rates in insulinomas are abnormally high. Thus, the premise for The Genomics and Transcriptomics of Human Insulinoma study is that benign human insulinomas hold the genomic and transcriptomic "recipe", and the repertoire of druggable pathways, that can be exploited to induce regeneration or replication of human beta cells in diabetes. Because, insulinomas are so rare, are almost always benign (non-malignant), and are easily resected by laparoscopic surgery, little attention has been paid to understanding the genomics or transcriptomics of insulinoma. There are at present only three published studies employing next-gen sequencing in insulinoma (PMID:24326773; PMID:25787250; and PMID:25763608). These studies contained 10, 7 and 8 insulinomas, respectively, and highlighted likely mutations in YY1 and MEN1. Our goal was to markedly expand the database and to add RNAseq to these earlier studies. The GETHIN study reports next-gen sequencing on 38 insulinomas, by far the largest series of human insulinomas subjected to next-gen sequencing (see the Selected publications section for reference). This includes paired (genomic plus tumor) whole exome sequencing on 26 human insulinomas (22 sequenced at Mount Sinai, 4 downloaded from Cao et al, PMID:24326773), and 25 sets of RNAseq from insulinomas, some of which also had paired whole exome sequencing, and some of which did not. The insulinoma RNAseq was compared to RNAseq from 22 sets of FACS-sorted normal human beta cells. Since insulinomas are so rare, the 38 insulinomas were collected by several investigators at several institutions over several decades, but most (22 whole exome sets, and all RNAseq) were sequenced at the Icahn School of Medicine at Mount Sinai in New York. The current dataset contains whole exome sequencing and RNAseq on the 11 insulinomas harvested at Mount Sinai. The four from Cao et al can be retrieved from Cao et al PMID:24326773. Fastq files from the remaining 23 insulinomas will be added as the local IRBs and Institutional Certifications are acquired. Complete patient data are provided in our Nature Communications report. Going forward, our intention is to expand this series, with the goal of sequencing 100 human insulinomas. These will be added to dbGaP as they accrue. Paired-end whole exome sequencing (mean usable sequencing depth 79X and 105X for blood and insulinoma, respectively) was performed using an Illumina HiSeq 2500. Insulinoma and sorted normal beta cell RNAseq was performed on Ribozero and polyA paired end libraries using the Illumina HiSeq 2500. Complete sequencing and bioinformatic details are provided in our Nature Communications report. The principal findings from the study are that although each insulinoma has a different set of presumptive driver mutations, the majority converge on genes that are members of the Polycomb Complex, Trithorax Complex and other epigenetic modifying enzymes. In addition, 20% of insulinomas have copy number loss or loss of heterozygosity of all or most of chromosome 11, and the majority display abnormalities in CpG methylation and imprinting control on the imprinted Chr 11 p15.5-15.4 region that contains INS, IGF2, CDKN1C, KCNQ1, and other genes involved in beta cell specification and proliferation.

  Study phs001422

• subset of DEEP IHEC release 2016 (EGAS00001001937), as used in EGAS00001001656 (bidirectional promotors paper, Fatemeh et al. 2018)

  part of the DEEP project results resulted in the publication of 'Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters', Epigenetics & Chromatin (2018), Fatemeh et al., DOI: 10.1186/s13072-018-0236-7, PMID: 30414612, PMCID: PMC6230222. This dataset contains the subset of DEEP data related to that study.

  Dataset EGAD00001005953

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (WGS)

  Data supporting: “Deep molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition.” Nowicki-Osuch, Zhuang et al. WGS (BAM files) 5 Barrett's samples 5 normal oesophageal samples 5 normal gastric cardia samples 5 normal duodenal samples

  Dataset EGAD00001006874

• Sequencing data for oesophageal and related samples - Scott et al (WGS, RNA)

  Data supporting: "Evidence that polyploidy in esophageal adenocarcinoma originates from mitotic slippage caused by defective chromosome attachments" Scott et al. WGS and RNAseq sequencing data Organoid, tumour and normal samples BAM files

  Dataset EGAD00001006738

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• Sequencing data for oesophageal and related samples - Alex Frankell et al (WGS)

  Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. WGS (BAM files) 379 matched tumour-normal pairs

  Dataset EGAD00001004417

• The genomic landscape of lung adenocarcinoma in East Asians

  We performed exome sequencing of 210 and transcriptome sequencing of 181 LUADs of Chinese patients. For more details, please see publication "Genomic landscape of lung adenocarcinoma in East Asians" by Chen J. et. al. in Nature Genetics 2020. https://www.nature.com/articles/s41588-019-0569-6.

  Study EGAS00001002941

• Sequencing data for oesophageal and related samples - Black et al (WGS)

  Data supporting: "Understanding the malignant potential of gastric metaplasia of the oesophagus and its relevance to Barrett’s Oesophagus surveillance: individual-level data analysis" Black et al (WGS OACs/BOs/normals)

  Dataset EGAD00001011187

• Sequencing data for oesophageal and related samples - Abbas et al (WGS)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (WGS for 1397 samples)

  Dataset EGAD00001011196

• Sequencing data for oesophageal and related samples - Izadi et al (WGS, RNA)

  Data supporting: "Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma" Izadi et al. WGS for tumour and normal samples. RNAseq for tumour samples.

  Dataset EGAD00001007493

• Sequencing data for oesophageal and related samples - Noorani et al (WGS)

  Data supporting: "Genomic evidence supports a clonal diaspora model for metastases of esophageal adenocarcinoma." Noorani et al. WGS (BAM files) 134 samples for 18 cases Includes primary, lymph-node, distant metastatic, Barrett's and normal samples.

  Dataset EGAD00001005434

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (bulk RNA)

  Data supporting: “Deep molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition.” Nowicki-Osuch, Zhuang et al. RNAseq (BAM files) 12 Barrett's samples 12 normal oesophageal samples 11 normal gastric cardia samples

  Dataset EGAD00001006882

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001001884

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001002335

• SEAsia.Oceania.Australia

  the tar archive contains unflitered genotype data from Reich et al AJHG 2011 study in plink format

  Dataset EGAD00010002302

• SolomonIslands.Dataset

  The tar archive contains unflitered genotype data from Pugach et al 2018 in plink format

  Dataset EGAD00010002306

• Knoll et al. 2023, Identification of drug candidates targeting monocyte reprogramming in people living with HIV

  Dac EGAC50000000044

• Cardiac fibroblast DAC

  DAC for reviewing requests to access data on cardiac fibroblasts as described by Aguado-Alvaro et al (Nature Communications, 2025)

  Dac EGAC50000000479

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

• BLUEPRINT release August 2016, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002454

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021