19254 results for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins They are the best FC seller..nEoY"

in 33.12 milliseconds.

• Primary_DIPG_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

  Dataset EGAD00001011080

• Germline genome sequencing samples from the Hereditary Cancer Syndromes (ICCon) Cancer Flagship

  A prospective study of individuals with suspicion of a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or was not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing and a comprehensive cancer virtual gene panel analysis were undertaken.

  Dataset EGAD00001011260

• RNA-seq dataset of Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Creation of living organoid biobank for ewing and ewing-like sarcomas

  Dataset EGAD00001015419

• Low-coverage whole-genome sequencing (lcWGS) data of Genome in a Bottle (GIAB) reference samples

  This dataset contains low-coverage whole-genome sequencing (lcWGS) data generated from three GIAB reference samples (HG001–HG003) for method benchmarking and concordance analysis in FFPE-GWAS workflows. The data were generated using Illumina NovaSeq with paired-end 150bp reads and downsampled to 2x coverage.

  Dataset EGAD00001015533

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51).

  Dataset EGAD00001015602

• Genomic Analysis of Extra-Nodal Natural Killer/T-Cell Lymphoma (ENKTCL)

  In this study, we performed extensive genetic profiling on 209 extra-nodal natural killer/T-cell lymphoma (ENKTCL) nasal-type cases, including 174 Chinese from four hospitals in China, and 31 Hispanic and 4 Caucasian patients from City of Hope and Eberhard Karls University of Tübingen. All of the cases were reviewed by experienced hematopathologists to confirm diagnosis. Written informed consents from patients were reviewed and approved by the institutional review board of each institution. We deposited targeted exon sequencing data of a selected 333-gene panel on the ENKTCL cases in dbGaP. DNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissues with an AllPrep DNA/RNA FFPE Kit. A custom platform (Agilent SureSelect) was used to capture target exons from genomic DNA of ENKTCL tumors. DNA was fragmented to 200bp using a Covaris S220 Focused-ultrasonicator and was end-repaired and ligated to Illumina adaptors with a KAPA Hyper Prep Kit. Ligated products were purified and amplified with a 7-cycle PCR. Exome capture from the PCR products was performed using a SureSelect Target Enrichment Kit. The captured exomes were further amplified with an 8-cycle PCR and purified for cluster generation using the cBot cluster generation system with a HiSeq PE Cluster Kit V4. 100bp paired-end reads were generated from an Illumina HiSeq 2500 system with a HiSeq SBS Kit V4.

  Study phs002925

• Single Cell DNA Methylation Analysis for Forensic Epigenetics

  As part of the Epigenetic CHaracterization and Observation (ECHO) program, the Genomic Analysis Laboratory at the Salk Institute generated the DNA methylation profiles of certain PBMC cell types to determine the change in methylation levels before, during or after exposure to certain biological or chemical agents. Samples from individuals who either handled anthrax in controlled environments or who tested positive to MRSA, MSSA, HIV, COVID-19 or exposed to Flu virus or organophosphates, or control samples were used in single-nucleus methylation (snmC-seq) assays to quantify DNA methylation levels of cytosine residues of the DNA. Around 5-10% cytosine sites were sampled in the assay. Using computational analyses, regions in the genome differentially methylated in response to the exposure were identified. This information can be used to develop diagnostic tools to predict the type of infection or time since exposure.

  Study phs003204

• Pharmacological improvement of CFTR function rescues airway epithelial homeostasis and host defense in cystic fibrosis children

  Rationale: Recent clinical trials have shown that elexacaftor/tezacaftor/ivacaftor (ETI) provides significant benefit to patients with cystic fibrosis (CF) by improving CFTR function. Despite these promising clinical findings, the specific effects on the airway inflammatory status leading to structural damage and impaired lung function, remain elusive. Objectives: We investigated the transcriptional changes at the single cell level of airway epithelial and immune cells that underlie the clinical improvement by ETI therapy in children with CF. Methods: Nasal swabs from thirteen children with CF and at least one F508del allele aged 6 to 12 years were collected at baseline and three months after initiation of ETI and subjected to scRNA-seq. In addition, we collected nasal swabs from 12 age- and sex-matched controls. Sweat chloride concentrations, spirometry and multiple breath washout were used for clinical evaluation of CF children. Measurements and main results: ETI significantly reduced sweat chloride concentrations (-52.2 ± 14.3 mmol/L, P < 0.001) and improved the lung clearance index (-1.3 ± 1.8, P < 0.05). Single cell transcriptomics revealed an impaired interferon signalling in epithelial cells of CF children at baseline, which was partially restored by ETI in conjunction with an ETI-induced increase in expression of MHC I and II encoding genes similar to control levels. Additionally, ETI markedly reduced the inflammatory phenotype of immune cells, particularly of neutrophils and macrophages. Conclusions: Improvement of CFTR function by ETI restores epithelial homeostasis and reduces immune cell inflammatory responses in the upper airways of children with CF, highlighting the potential of early initiation of ETI therapy.

  Study EGAS50000000128

• Genome Sequencing of Circulating Tumor Cells for Minimally Invasive Molecular Characterization of Multiple Myeloma Pathology

  &#8203;&#8203;Multiple Myeloma (MM) develops from well-defined precursor stages known as Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering MM (SMM); however, invasive bone marrow (BM) biopsy limits screening and monitoring strategies for patients. In this study, we enumerated circulating tumor cells (CTCs) from patients with precursor and overt diseases, and developed a novel approach, MinimuMM-seq, which enables detection of translocations and copy number abnormalities through whole-genome sequencing of highly pure CTCs. In a cohort of 51 patients, 24 with paired BM, we applied our method MinimuMM-seq and detected 100% of clinically reported BM biopsy events. The next-generation sequencing (NGS) assay could replace molecular cytogenetics by Fluorescence In Situ Hybridization (FISH) for diagnostic yield and risk classification. In 8 patients we could apply MinimuMM-seq on serially collected samples to track and monitor major clones in peripheral blood. We describe clonal evolution and shifting dynamics of subclones over time, as well as in between blood and marrow compartments. All whole-genome sequencing (WGS) data generated in this study will be made accessible through dbGaP.

  Study phs003084

• RNAseq of GEPARSIXTO

  294 formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer’s protocol (Promega 9FB167). 279 total RNA sequencing libraries were prepared at TGL using a Bravo Automated Liquid-Handling Platform (Agilent G5562A) and the TruSeq Stranded Total RNA Library Prep Gold Kit (Illumina 20020599) following the manufacturer’s protocol (Illumina 1000000040499). RNAseq library quality and quantity were measured using a TapeStation 4200 (Agilent G2991AA) and Qubit 3.0 fluorometer (Life Technologies Q33216), pooled at equal molar ratios, and denatured following the manufacturer’s protocol (Illumina 1000000106351). 271 total RNA sequencing libraries were sequenced at TGL on NovaSeq 6000 (Illumina 20012850) S4 flow cells (Illumina 20028313) following the manufacturer’s protocol (Illumina 1000000019358) using a 2x50 bp paired-end configuration and pool sizes of 91 libraries to target a read depth of 110 million clusters per library on average.

  Dataset EGAD00001010201

• GeoMx DSP of NGS mRNA expression in pre-treatment biopsies from patients with metastatic triple-negative breast cancer treated with PARP inhibitors.

  This dataset contains GeoMx digital spatial profiling (DSP) data from 12 FFPE pre-treatment biopsies of metastatic HR-altered breast cancer patients subsequently treated with PARP inhibitors (Olaparib or Talazoparib). Samples were collected from primary breast tumors (n=7) and metastatic sites including lymph nodes (n=2), bone (n=2), and brain (n=1). Tissue sections were stained for pan-cytokeratin (PANCK) to selectively profile tumor cells, with NGS-based transcriptome data generated for both PANCK+ and PANCK- regions. The dataset includes raw data files (176 fastq files) along with clinical annotations.

  Dataset EGAD50000001932

• Methylome of memory B cells with autoproliferation in MS

  Methylome of resting/hi and autoproliferating/Dim memory B cells in Multiple sclerosis patients. In brief, non-proliferating (CFSEhi) and AP+ (CFSEdim) CD19+ CD27+ B cells from PBMCs of 6 natalizumab-treated female RRMS (NAT) patients were sorted following 7 days of autoproliferation. Methylome libraries for 12 samples were constructed by applying the post-bisulfite adaptor tagging (PBAT) method on lysed cells and sequencing was conducted on Illumina NovaSeq 6000. CpGs with minimum 10X coverage were used for differential methylation position (DMP) analysis.

  Dataset EGAD50000001269

• Whole Exome PC9 and A375 (2019-04-03)

  Drug resistant population of PC9(human non-small cell lung cancer) or A375 (human melanoma) cell lines were used for this study. By exome sequencing, we will analyse mutations of cells in drug tolerent state and after drug holiday. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004891

• Evolutionary trajectories of IDH-mutant astrocytoma identify molecular grading markers related to cell cycling

  To study the evolutionary processes that drive malignant transformation in IDH-mutant astrocytomas, we performed multi-omics on a large cohort of matched initial and recurrent tumor samples. We find that genome-wide DNA-methylation levels decreased over time, mainly in patients with high-grade recurrences. DNA-demethylation was lifted from specific loci associated with DNA replication, and was associated with upregulation of cell cycling associated genes. Upregulation of cell cycling genes occurred predominantly in proliferating tumor cells, and was associated with tumor grade. Temporal DNA-demethylation and upregulation of cell cycling were hardly affected by chemo- and/or radiotherapy, indicating treatment does not affect the course of disease. Further, we defined a DNA-methylation based signature associated with tumor grade and poor prognostic genetic events, with a prognostic power stronger than CDKN2A/B deletion. We validated its prognostic power on primary tumor samples of patients included in the CATNON randomized phase 3 clinical trial. Therefore this model can serve as a molecular grading marker for IDH-mutant astrocytomas.

  Study EGAS00001007527

• Population_dynamics_in_abnormal_haematopoiesis

  Background: Our recent study has made direct insight into the clonal dynamics of blood cell production in an unperturbed setting in a human. Using whole genome sequencing to track acquired somatic mutations, we were able to construct a phylogenetic tree of different stem and progenitor cells and used this tree to determine the dynamics of mature blood cell production in longitudinal samples. These data set the baseline for understanding population dynamics in abnormal haematopoiesis, and how malignant clones outcompete their normal counterparts to drive haematological malignancies. Aim: This study will measure population dynamics in abnormal human haematopoiesis in patients with clonal blood stem cell disorders. Methods: From patient bone marrow or peripheral blood, we have isolated colonies grown from single blood stem cells/progenitors. Colony DNA will be analysed by whole-genome sequencing to build (or populate) a phylogenetic tree to determine clonal relationships and track stem cell contribution to mature blood cell production. These data will also reveal disease-associated genomic features (mutational burden and mutational signatures) in haematopoietic cells.

  Study EGAS00001003181

• AML Proteogenomic Landscape Whole-transcriptome RNA-Sequencing

  Whole transcriptome RNA-sequencing of purified bone marrow blasts of 136 de novo, treatment naive AML patients. For further details, we refer to the manuscript "The Proteogenomic Landscape of AML" by Jayavelu, Wolf, Buettner et al. mRNA extraction and whole transcriptome sequencing For transcriptome analysis the TruSeq Total Stranded RNA kit was used, starting with 250ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (Illumina, San Diego, CA, USA). 100bp paired-end reads were sequenced on the NovaSeq 6000 (Illumina) with a median of 57 mio. reads per sample. RNA Data Analysis Data quality control was performed with FastQC v0.11.9. Reads were aligned to the human reference genome (Ensembl GRCh38 release 82) using STAR v2.6.1. Gene count tables were generated while mapping, using Gencode v31 annotations. All downstream analyses were carried out using R v4.0 and BioConductor v3.12 (Huber et al., 2015; R Core Team, 2020). Size-factor based normalization was performed using DESeq2 v1.28.1(Love et al., 2014).

  Dataset EGAD00001008484

• Pooled Single-Cell RNA-Seq of iPSC-Derived Neural Stem Cells from ADHD and Control Individuals

  This dataset contains FASTQ files from pooled single-cell RNA sequencing (scRNA-seq) of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs). The iPSCs were reprogrammed using the non-integrative Sendai virus system (CytoTune-iPS 2.0), introducing OCT3/4, SOX2, KLF4, and cMYC. Donor somatic cells included keratinocytes, PBMCs, and lymphoblastoid cell lines from individuals with ADHD and age-matched healthy controls (6–18 years). iPSCs underwent standard quality control, including immunocytochemistry, qRT-PCR, mycoplasma testing, and SNP genotyping. NSCs were produced via neural induction and validated by qRT-PCR and immunostaining for PAX6, SOX2, NESTIN, TUJ1, and FOXG1. Sequencing was performed on the Illumina NovaSeq 6000.

  Dataset EGAD00001015644

• Whole-genome sequencing analysis for understanding of the stepwise progression of lung adenocarcinoma

  In this study, we performed long and short read whole-genome sequencing analysis of lung adenocarcinoma from early to advanced stages to identify molecular events associated with the stepwise progression of lung adenocarcinoma. We particularly focused on very early stage of lung adenocarcinoma, such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA). In addition to the whole-genome sequencing analysis, we conducted transcriptome and epigenome analysis, multiplex fluorescence immunostaining. This study would enable us to understand important molecular events of pathogenesis in detail during lung adenocarcinoma progression.

  Study JGAS000570

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line. REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIP’d and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified using Qiagen RNeasy. Knock down of CEBPE was validated by qRT. RNA integrity &gt;7.7 for all samples. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Dataset EGAD00001004084

• Molecular Signatures of DCIS to Invasive Progression for Basal-Like Breast Cancers: An Integrated Mouse Model and Human Tumor Study

  We studied the genomic signatures of progression in breast ductal carcinoma in situ (DCIS) as it progresses towards triple negative invasive breast cancer (TNBC). Single cell RNA sequencing (scRNAseq) was performed on the C3Tag genetically engineered mouse model that forms human breast-like DCIS and TNBC. Bulk RNA sequencing was performed on RNA harvested from archival formalin-fixed, paraffin embedded (FFPE) pairs comprising of estrogen receptor (ER) positive (ER+) and negative (ER-) subsets of DCIS.&nbsp;

  Study phs002443

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  Data generated through single nuclei ATAC sequencing on whole ganglionic eminences from 3 human fetuses (two of 16 and one of 17 gestational weeks). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource with ethical approval. snATAC-Seq libraries were prepared from ~8,000 nuclei per sample using Chromium Next GEM Single Cell ATAC (v1.1) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 617 million read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Schizophrenia Bulletin 2024, https://doi.org/10.1093/schbul/sbae083. Please note that 10X generated BAM files, rather than FASTQ files, have been uploded. FASTQ files can be regenerated using the 10X Genomics bamtofastq tool. https://support.10xgenomics.com/docs/bamtofastq

  Dataset EGAD50000000601

• Single nuclei RNA-Seq from 5 regions of the human fetal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Dataset EGAD00001009303

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001000825

• Multiplexed scRNA-Seq Reveals Cellular and Genetic Correlates of SLE

  Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and cell states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (160 cases, 98 controls) with multiplexed single-cell RNA-seq (mux-seq). Cases exhibited prominent expression of type-1 interferon-stimulated genes (ISG) in monocytes, reduction of na&#239;ve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell-type-specific expression features accurately predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data, mapping cell-type-specific cis-eQTLs and linked known and novel SLE-associated variants to cell-type-specific gene expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

  Study phs002812

• Chondromyxoid fibroma

  Chondromxoid fibroma is a benign tumour of bone with unknown underlying pathogenesis. To determine pathognomic genomic event in chondromyxoid fibroma whole genome sequencing will be undertaken to reconstruct rearrangements and find underlying mutations.

  Dataset EGAD00001001063