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• Multi-omic data of subjects of FUSION study

  Finland-United States Investigation of NIDDM Genetics (FUSION) Study has sought to understand the genetic basis of type 2 diabetes (T2D) and diabetes-related traits including glucose, insulin, lipid levels, and obesity. We have performed extensive multi-omic characterization of the study subjects, including SNP array genotyping, whole genome/exome DNA sequencing of blood/tissue/iPSC cells generated from fibroblast, as well as RNAs. The study has provided crucial data for understanding molecular and cellular mechanisms of the disease-causing variants and their respective target genes. This set of data will be a valuable resource to the T2D community.

  Study EGAS00001008440

• NeoPAL study - RNAseq and Targeted DNA sequencing data

  This dataset is composed of 159 RNAseq data (fastq, bam and count tables) and 35 targeted DNAseq data (fastq).

  Dataset EGAD50000001490

• RNA-sequencing of ex situ stimulated donors blood cells

  Cells from whole blood stimulation assay were cryopreserved. The cryopreserved cells were thawed and subjected to RNA preparation. RNA obtained were subjected to for bulk sequencing.

  Study EGAS50000001077

• SureTypeSC - accurate genotyping of single-cell SNP array data

  We used a collection of single cells from two Coriell cell lines to train and validate a machine learning method for quality assessment of the single cell genotypes

  Study EGAS00001004621

• Genomic profiling of well-differentiated and dedifferentiated liposarcoma from the same patient

  Well-differentiated, dedifferentiated, and matched normal tissues from liposarcoma (51 specimens) from 17 patients were obtained for whole exome sequencing. Tumors were submitted from 9 patients were used for RNA sequencing. The bam files are made available in this dataset.

  Dataset EGAD00001003976

• Islet RFX6 Study Manuscript Data

  This submission includes raw FASTQ files (for bulk RNA-seq and 10X joint snATAC+snRNA multiome profiling experiments), sample phenotype files, and genotypes for the data included in the manuscript.

  Dataset EGAD00001008777

• Processed DNA methylome sequencing data

  The dataset contains methylation values of all SNP-filtered CpG sites for all samples from the air pollution study (total n=60). Nasal lavage samples were collected from n=29 moderately exposed (residing in Stuttgart) and n=31 lowly exposed (residing in Simmerath) individuals. For methods and study details, please see PMID 37343754.

  Dataset EGAD00001011208

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from cognitively healthy individuals exposed to traffic-related ultrafine particles (UFPs) for 24h and 72h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD00001011317

• COVID_Methyl_scRNA

  DAC for the study of whole-genome enzymatic DNA methylation sequencing and single-cell RNA sequencing of nasal cells from COVID-19 patients. Nasal swabs were collected from COVID-19 patients during the acute phase of infection as well as 3 and 12-months post-infection. Cells isolated from nasal swabs were subjected to whole-genome enzymatic DNA methylation sequencing (n=33) and scRNA-seq (n=24). For n=12 former COVID-19 pateints, follow-up samples were collected at 3 and 12 months post-infection and subjected to scRNA-seq.

  Dac EGAC50000000197

• Benchmarking of ProSolo, a new probabilistic single nucleotide variant caller for single cell DNA sequencing data. This study provides the whole exome sequencing dataset used in this assessment.

  Benchmarking of ProSolo, a new probabilistic single nucleotide variant caller for single cell DNA sequencing data that provides control over the false discovery rate of different single cell events at genomic sites (e.g. alternative allele presence or allele dropout). Here, we provide the newly generated whole exome sequencing data used in assessing ProSolo's performance. It contains whole exome sequencing of: a patient with a constitutional mismatch repair defect (MSH6-) and their parents and siblings, a granulocyte bulk sample and 5 single granulocytes sequenced after whole genome amplification.

  Study EGAS00001004123

• Multi-sample whole exome sequencing from 4 cases of advanced breast cancer.

  Metastatic and primary tumour samples were collected from 4 patients with advanced breast cancer. Samples were collected at autopsy and also from biopsies taken during life. Tumour and germline samples are available. Whole exome sequencing was performed on all samples.

  Dataset EGAD00001003137

• Tel Aviv RNA-seq dataset of of BiPSCs and FiPSCs derived cells

  RNA-seq data obtained from directed differentiation of a subset of FiPSCs and BiPSCs cell lines towards islet-like cells. RNA was collected at two key developmental stages: definitive endoderm (DE) and pancreatic progenitors (PP).

  Dataset EGAD00001003780

• Single cell RNA sequencing of CD34+ CB and BM samples in SLE and healthy controls

  Single cell RNA paired-end sequencing was performed on CD34+ progenitor cells derived from 4 SLE patients, 6 healthy control samples and 2 umbilical cord blood samples using Illumina MiSeq/NextSeq 500.

  Dataset EGAD00001011277

• Baseline epigenetic clock measures in the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA)

  Epigenetic clock measures for a subset of 1,870 participants within the NICOLA cohort. The following epigenetic clocks were generated: (±PC)PhenoAge, (±PC)GrimAge, (±PC)Horvath1, (±PC)Hannum, PCDNAmTL and DunedinPACE. +PC represents the use of the principal component adjusted version of the clock.

  Dataset EGAD50000002063

• Liver Regulatory Genomics Data Access Committee

  Data access committee for genomic datasets generated for human liver tissue and human primary liver cells by the Regulatory Genomics of Metabolic Disease group (Imperial College London, Section of Genetics and Genomics).

  Dac EGAC50000000715

• LCM-ATACseq on human lung macrophages

  In this study we employed Laser Capture Microdissection (LCM) for the multimodal profiling of lung macrophages cell populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (~100 cells) were collected from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation), and processed for ATAC-seq.

  Study EGAS00001006167

• DNA and RNA sequencing data from Ovarian Carcinosarcoma patients from the Glasgow Cohort.

  In this study, we analysed DNA and RNA sequencing data from Ovarian Carcinosarcoma patients, from isolated carcinoma and sarcoma components and investigated DNA variants as well as gene expression. Genomic analyses from this data and further investigation from preclinical models of ovarian carcinosarcoma support the conversion theory for disease development and indicate that microtubule inhibitors could be used to suppress EMT and stimulate anti-tumour immunity.

  Study EGAS00001006605

• Comparison Across Multiple Types of Sleep Deprivation

  This study is designed to assess neurobehavioral performance, as well as molecular and physiological changes associated with variations in timing and quantity of sleep. Gene expression changes associated with neurobehavioral (cognitive) performance were assessed in a time-series among individuals randomly assigned to four separate sleep conditions during a 10-day inpatient study: a well-rested control, sleep restriction with nighttime sleep, sleep restriction with daytime sleep to roughly simulate shiftwork schedules, and total (acute) sleep deprivation.

  Study phs003924

• Adult granulosa cell tumor WGS data cohort with corresponding reference germline WGS data

  Adult granulosa cell tumors (AGCTs) harbor a somatic FOXL2 c.402C>G mutation in ~95% of cases and are mainly surgically removed due to limited systemic treatment effect. In this study, potentially targetable genomic alterations in AGCTs were investigated by whole genome sequencing on 46 tumor samples and matched normal DNA. Copy number variant (CNV) analysis confirmed gain  of chromosome 12 and 14, and loss of 22. Pathogenic TP53 mutations were identified in three patients with highest tumor mutational burden and mitotic activity, defining a high-grade AGCT subgroup. Within-patient tumor comparisons showed 29-80% unique somatic mutations per sample, suggesting tumor heterogeneity. FOXL2-wildtype AGCTs had DICER1, TERT(C228T) and TP53 mutations and similar CNV profiles as FOXL2-mutant tumors. Our study confirms that absence of the FOXL2 c.402C>G mutation does not exclude AGCT diagnosis. The lack of overlapping variants in targetable cancer genes, indicates the need for personalized treatment for AGCT patients 

  Study EGAS00001004249

• Tumor transcriptomes of PitNET patients with and without somatostatin analogue treatment before surgery

  Dataset contains fastq files of tumor transcriptomes of 12 pituitary neuroendocrine tumors. Patients with and without somatostatin analogue treatment before tumor surgery can be compared. Sequencing was performed on MGISEQ-2000.

  Dataset EGAD00001006446

• CAGE-seq of frontal post-mortem human brain tissue of patients with FTD and healthy controls

  CAGE-sequencing was performed on frontal post-mortem human brain tissue of patients with FTD caused by mutations in GRN, MAPT or C9orf72 and healthy controls.

  Dataset EGAD00001006843

• Finding structural variation and functional consequences from the primary leukemia cells (CLL) at the single-cell level

  In this study, we aimed to identify somatic structural variation of chronic lymphocytic leukemia (CLL) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 63-year-old female patient.

  Study EGAS00001004925

• Whole-Exome Sequencing Study of Diabetic Nephropathy

  To identify rare variants of diabetic kidney disease (DKD), we conducted a whole-exome sequencing (WES) study. This study employed an extreme case–control design, which included a selection of the 593 most rapidly progressing DKD cases from the Chronic Renal Insufficiency Cohort (CRIC) Study (phs000524). In this two-stage WES study of DKD, participants with DKD from the CRIC were compared with control groups of participants without DKD from another cohort in the first stage. Suggestive signals identified in the first stage were confirmed in the second stage analysis among a diverse population with existing whole-genome sequencing (WGS) data. Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test implemented within our mixed model framework. As a result, we identified four novel gene loci, DIS3L2, KRT6B, ERAP2 and NPEPPS, that achieved exome-wide significance and may play an important role in the DKD disease course. This large WES study provides novel insights into DKD's molecular mechanisms.

  Study phs003429

• Genome-wide cell-free DNA fragmentation in patients with cancer

  Cell-free DNA (cfDNA) in the blood provides a noninvasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an approach to evaluate fragmentation patterns of cfDNA across the genome and found that cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles. We applied this method to analyze fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancers and 245 healthy individuals. A machine learning model incorporating genome-wide fragmentation features had sensitivities of detection ranging from 57% to >99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation based cfDNA analyses detected 91% of cancer patients. The results of these analyses highlight important properties of cfDNA and provide a proof of principle approach for screening, early detection, and monitoring of human cancer.

  Study EGAS00001003611

• Diverse transcriptomic and mutational patterns but limited functional pathway alterations in patient-derived SS cells

  We profile the whole-transcriptome of 7 patient-derived Sézary Syndrome (SS) cells to identify expression patterns, functional programs and expressed gene mutations that may provide clues on new therapeutic options for SS patients. The libraries were sequenced on NextSeq500 (Illumina) with a paired-end read length of 2x75bp.

  Study EGAS50000001151