19263 results for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins They are the best FC seller..nEoY"

in 100.50 milliseconds.

• H3Africa H3AChipDesign AWI-Gen

  60 samples from Burkina Faso and Ghana generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004448

• Pilot Fetal Cell Atlas_RNAseq (2018-08-20)

  As part of the Human Cell Atlas we will study fetal tissue. . This dataset contains all the data available for this study on 2018-08-20.

  Dataset EGAD00001004305

• Temporal stability of circulating microRNAs in human serum

  Circulating microRNA biomarkers for disease have been subject to extensive research. However, insufficient consideration of variability in the healthy population has led to few markers achieving the performance necessary in independent follow-up studies to be taken forward to clinical practice. To investigate the natural variation of circulating microRNA over time, we performed small RNA sequencing in a longitudinal study of 66 women with no history of cancer, and determined the distribution and dynamics (via intraclass correlation coefficients, ICCs) of the miRNA profile over 3 time points sampled across 2-5 years. We also investigate abundances in circulation, as well as the impact of normalization, age, BMI, and other sample collection factors on microRNA measurements from small RNA sequencing.

  Study EGAS00001003221

• Genetic Study on Nephropathy in Type-2 Diabetes

  A collection of patients with type-2 diabetes was collected at the Joslin Diabetes Center. Patients were categorized to a group of cases with diabetic nephropathy, and a group of controls with normoalbuminuria. From these groups, 173 cases and 177 controls were randomly selected for a genome-wide association study.

  Study phs000302

• snRNA-seq schizophrenia control Prefrontal cortex

  Human Brodmann Area 8/9 tissue from 43 schizophrenia subjects and 42 control individuals was obtained from three sources, NBB (Netherlands Brain Bank), Craig A. Stockmeier (University of Mississippi Medical Center), Macedonian/New York State Psychiatric Institute Brain Collection (Andrew J. Dwork, Columbia University). All subjects included in the study were matched between the two groups for age, gender, and postmortem interval. Nuclei were isolated and enriched for 85% neuronal nuclei before single nucleus RNA sequencing was performed with 10x Genomics Chromium Single Cell protocol v3.

  Dataset EGAD50000002447

• Bulk TCRseq data from 149 patients with bladder cancer

  For this dataset we performed bulk TCRseq on tumor and serial blood samples from patients with muscle invasive bladder cancer (n patients = 119, n blood = 209, n tumor = 28) or non-muscle invasive bladder cancer (n patients = 30, n blood = 56, n tumor = 19) for a total of 149 patients and 312 samples. Each sample consists of a paired fastq file. Sequenced on the Ilumina NovaSeq6000 platform using SP and S1 flow cells (v1.5, 2x101 cycles), with a mean yield of 42 million reads covering the CDR3β region.

  Dataset EGAD50000001382

• 2017_AML_WGS

  This 2017_AML_WGS study includes 10 paired samples derived from Korean AML paitients. 10 AML Bone Marrow samples were collected and paired with each normal(Saliva or BM derived) sequencing data. The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002388

• AML_WES

  This 2014_AML_WES study includes 40 paired samples derived from Korean AML paitients. AML Bone Marrow samples were collected and paired with each normal(Saliva or BM derived) sequencing data. The results of this CN study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001559

• BLUEPRINT release August 2015, ChIP-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  ChIP-Seq data for 1 mesenchymal stem cell of the bone marrow sample(s). 9 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001578

• BLUEPRINT release August 2016, RNA-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  RNA-Seq data for 2 mesenchymal stem cell of the bone marrow sample(s). 2 run(s), 2 experiment(s), 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002473

• BLUEPRINT release August 2016, ChIP-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  ChIP-Seq data for 2 mesenchymal stem cell of the bone marrow sample(s). 16 run(s), 14 experiment(s), 14 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 EGAD00001002381

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma_CM67-RNASeq

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006306

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006309

• Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis

  The role of non-coding variants in polygenic skin disease and their connection to homeostatic transcription factors (TFs) in epidermis was investigated. Homeostatic TFs were identified by perturb-seq in differentiating keratinocytes, using either 10x or split-pool approaches to sequencing, with follow-up validation by siRNA and RNA-seq. TF binding events were profiled by population sampling Cleavage Under Targets & Release Using Nuclease (CUT&RUN), in which a random population of neonatal foreskin keratinocytes were assayed by CUT&RUN for homeostatic TFs under progenitor growth and differentiation conditions. Heterozygous alleles were identified from the TF binding data and examined for allele specific binding events (ASBs). ASBs were then compared with non-coding variants linked to skin disease. Variants with potentially pathogenic effects were identified. Promoters and high TF occupancy genomic regions were found to be "buffered" against variants causing ASBs.

  Study phs003977

• Human papillomavirus integration induces oncogenic host gene fusions in oropharyngeal cancers

  HPV integration disrupts host genomic structure and expression, but whether these alterations promote cancer development remains unclear. Multiple genomic analyses of oropharyngeal cancers identified several host gene fusions, including recurrent FGFR3-TACC3 fusions, expressed from rearranged genomic loci adjacent to HPV integration sites. Evolutionary modeling implicated integration of virus concatemers into the host genome as a common initiating event in fusion formation. Co-expression of HPV16 E6/E7 and FGFR3-TACC3, but neither alone, was sufficient for tumor development in both xenograft and syngeneic mouse models and led to unique transcriptional programs implicated in carcinogenesis. FGFR3-TACC3 expression decreased the ubiquitination and degradation of E6 and E7, thereby increasing oncoprotein abundance. We conclude that expression of HPV16 oncoproteins and host gene fusions generated from HPV integration sites can be sufficient for cancer development.

  Study EGAS50000000892

• Multi-omic Profiling of Central Nervous System Leukemia Identifies mRNA Translation as a Therapeutic Target

  Central nervous system (CNS) dissemination of B-precursor acute lymphoblastic leukemia (B-ALL) has poor prognosis and remains a therapeutic challenge. Here we performed targeted DNA sequencing, transcriptional and proteomic profiling of paired leukemia infiltrating cells in the bone marrow (BM) and CNS of xenografts. Genes governing mRNA translation were upregulated in CNS leukemia, and subclonal genetic profiling confirmed this in both BM-concordant and BM-discordant CNS mutational populations. CNS leukemia cells were exquisitely sensitive to the translation inhibitor omacetaxine mepesuccinate, which reduced xenograft leptomeningeal disease burden. Proteomics demonstrated greater abundance of secreted proteins in CNS infiltrating cells including complement component 3 (C3) and drug targeting of C3 influenced CNS disease in xenografts. CNS infiltrating cells also exhibited selection for stemness traits and metabolic reprogramming. Overall, our study identifies therapeutic targeting of mRNA translation as a novel therapeutic approach for B-ALL leptomeningeal disease.

  Study EGAS00001005647

• Gene copy number variation in pediatric mental illness in a general population

  We assessed the relationship of gene copy number variation (CNV) in mental health/neurodevelopmental traits and diagnoses, physical health, and cognitive biomarkers in a community sample of 7,100 unrelated European, and East Asian children and youth (Spit for Science). Diagnoses of mental health disorders were found in 17.5% of participants and 27.6% scored in the highest 10% on either or both ADHD and OCD trait measures. Clinically relevant CNVs were present in 3.9% of participants and were associated with elevated scores on a continuous measure of ADHD (p=5.0×10-3), on a cognitive biomarker of mental health (response inhibition (p=1.0×10-2)), and on prevalence of mental disorders (p=1.9×10-6, odds ratio: 3.09). With a rise of mental illness, our data establishes a baseline for delineating genetic contributors in paediatric-onset conditions.

  Study EGAS00001006659

• non-malignant plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 125 different human donors: 88 patients with a non-malignant disease and 37 cancer-free controls. Samples were sequenced on a NovaSeq X and sequencing data is provided in FASTQ format.

  Dataset EGAD50000001806

• DupiAERD

  Dataset contains bulk RNA sequencing reads from 44 NERD patients under dupilumab therapy before and after aspirin provocation at baseline and after 24 weeks of treatment. Dataset is a multiplexed .bam file containing all sequencing reads with tagged identifiers.

  Dataset EGAD50000000565

• Genetics of Microcephalic Osteodysplatics Primordial Dwarfism

  This project aims to find causal variants in 50 patients diagnosed with Microcephalic Osteodysplastic Primordial Dwarfism (MOPD), of presumed recessive inheritance performing whole exome sequencing to ~50x mean depth.This is a collaboration with Prof A. Jackson, MRC Human Genetics Unit, Edinburgh

  Dataset EGAD00001000342

• Human placenta microRNA sequencing dataset

  Human placenta samples from 52: 5 first trimester , 7 second trimester, and 40 term placenta. Data is uploaded as BAM files.

  Dataset EGAD00001007766

• RNA-seq of BCR-ABL1 lymphoblastic leukemia

  This dataset is derived from whole-transcriptome sequencing (RNA-seq) of RNA from 57 BCR-ABL1 lymphoblastic leukemias (53 diagnostic, 4 relapse).

  Dataset EGAD00001010307

• Clinical and Genetic Evaluation of Individuals with Undiagnosed Disorders through the Undiagnosed Diseases Network (UDN)

  The National Human Genome Research Institute and the NIH Clinical Center established the intramural Undiagnosed Diseases Program (UDP) in 2008 to make progress in uncovering, understanding, and treating rare disorders. Based on the success of the UDP, the NIH Common Fund established the Undiagnosed Diseases Network (UDN) in FY 2013 (Phase I, 9/16/2015-8/31/2018) to achieve this type of cross-disciplinary approach to disease diagnosis in academic medical centers around the United States. The NIH Common Fund expanded the network in 2018 (Phase II, 9/1/2018-6/20/2023) to increase the availability of diagnostic services, foster opportunities for collaboration between laboratory and clinical investigators, provide resulting data and protocols to the broader community, and assess development of a sustainable national resource after Common Fund support ends. The UDN transitioned from Common Fund in 2023. The National Institute of Neurological Disorders and Stroke (NINDS) will oversee the Network in Phase III, which launched in July 2023, with help from 17 different NIH Institutes and Centers along with the NIH Office of the Director. With help from patients, family members, patient advocacy groups, a Data Management and Coordinating Center (DMCC), several Clinical Sites, and other stakeholders, the NIH envisions the UDN evolving into a larger, diverse, and self-sustained network that fosters scientific discovery and provides expert diagnostic services for undiagnosed patients across the nation. The overarching goals of the UDN in Phase III include: Continuing the proven success of the UDN in improving the clinical evaluation of difficult-to-diagnose patients using a collaborative team approach and investigating and validating promising new diagnostic technologies. Facilitating research into the etiology of undiagnosed diseases by collecting and sharing standardized, high-quality clinical and laboratory data including genotyping, phenotyping, and documentation of environmental exposures. Promoting a broader integrated and collaborative community across multiple Clinical Sites and among laboratory and clinical investigators prepared to investigate the genetic, pathophysiologic, cell biologic, and molecular mechanisms underpinning these difficult-to-diagnose conditions.

  Study phs001232

• UCSF Sebaceous Carcinoma DAC for review of sequence data release from manuscript in Nature Communications, based in the UCSF Departments of Dermatology and Pathology

  Dac EGAC00001000850

• RNA Editing Exome

  Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project.

  Dataset EGAD00001000626