19442 results for "Buy fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins This is the best service ever..VBsp"

in 47.42 milliseconds.

• Normal sample for patient SA718

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009582

• Normal sample for patient SA720

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009583

• Tumour sample for patient SA718

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009584

• Tumour sample for patient SA720

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009585

• Normal sample for patient SA1017

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009586

• Normal sample for patient SA1026

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009587

• Normal sample for patient SA1027

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009588

• Normal sample for patient SA1028

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009589

• Normal sample for patient SA1040

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009590

• Normal sample for patient SA1064

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009591

• Normal sample for patient SA1065

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009592

• Normal sample for patient SA1069

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009593

• Normal sample for patient SA1073

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009594

• Normal sample for patient SA1074

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009595

• Normal sample for patient SA576

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA576

  Dataset EGAD00001009596

• Normal sample for patient SA610

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009597

• Normal sample for patient SA992

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009598

• Normal sample for patient SA994

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA994

  Dataset EGAD00001009599

• Normal sample for patient SA288

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA288

  Dataset EGAD00001009601

• Normal sample for patient SA299

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA299

  Dataset EGAD00001009602

• Normal sample for patient SA415

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA415

  Dataset EGAD00001009603

• Normal sample for patient SA666

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA666

  Dataset EGAD00001009604

• Tumour sample for patient SA1065

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009605

• Tumour sample for patient SA1064

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009606

• Tumour sample for patient SA1026

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009607

• Tumour sample for patient SA1069

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009608

• Tumour sample for patient SA1017

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009609

• Tumour sample for patient SA1027

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009610

• Tumour sample for patient SA1073

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009611

• Tumour sample for patient SA1074

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009612

• Tumour sample for patient SA576

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA576

  Dataset EGAD00001009613

• Tumour sample for patient SA1028

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009614

• Tumour sample for patient SA1040

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009615

• Tumour sample for patient SA992

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009616

• Tumour sample for patient SA610

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009617

• Normal sample for patient SA416

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA416

  Dataset EGAD00001009618

• Normal sample for patient SA1070

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009619

• Tumour sample for patient SA1070

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009620

• Tumour sample for patient SA997

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA997

  Dataset EGAD00001009621

• A73044B

  Whole genome sequencing for single cells for library A73044B 2085 cells; filetype=bam

  Dataset EGAD00001007101

• A73047D

  Whole genome sequencing for single cells for library A73047D 2091 cells; filetype=bam

  Dataset EGAD00001007102

• A95633B

  Whole genome sequencing for single cells for library A95633B 2259 cells; filetype=bam

  Dataset EGAD00001007104

• A96115A

  Whole genome sequencing for single cells for library A96115A 1635 cells; filetype=bam

  Dataset EGAD00001007111

• A96193B

  Whole genome sequencing for single cells for library A96193B 2410 cells; filetype=bam

  Dataset EGAD00001007118

• A96240B

  Whole genome sequencing for single cells for library A96240B 1683 cells; filetype=bam

  Dataset EGAD00001007122

• A95623A

  Whole genome sequencing for single cells for library A95623A 1897 cells; filetype=bam

  Dataset EGAD00001007607

• A95668B

  Whole genome sequencing for single cells for library A95668B 1905 cells; filetype=bam

  Dataset EGAD00001007609

• A95720A

  Whole genome sequencing for single cells for library A95720A 1467 cells; filetype=bam

  Dataset EGAD00001007613

• A96190A

  Whole genome sequencing for single cells for library A96190A 1833 cells; filetype=bam

  Dataset EGAD00001007620

• A96233B

  Whole genome sequencing for single cells for library A96233B 1601 cells; filetype=bam

  Dataset EGAD00001007623

• A98234B

  Whole genome sequencing for single cells for library A98234B 1600 cells; filetype=bam

  Dataset EGAD00001007627

• A98304A

  Whole genome sequencing for single cells for library A98304A 1560 cells; filetype=bam

  Dataset EGAD00001007636

• A108851B

  Whole genome sequencing for single cells for library A108851B 1681 cells; filetype=bam

  Dataset EGAD00001007596

• A108870A

  Whole genome sequencing for single cells for library A108870A 1795 cells; filetype=bam

  Dataset EGAD00001007598

• Recurrent Somatic Mutations of PTPN1 in Primary Mediastinal B cell lymphoma and Hodgkin Lymphoma

  Hodgkin lymphoma (HL) and primary mediastinal B cell lymphoma (PMBCL) are related lymphomas sharing pathological, molecular and clinical characteristics. Here, we discovered recurrent somatic coding sequence mutations of the tyrosine phosphatase gene PTPN1 in the tumor genomes and transcriptomes of these B cell lymphomas (6 of 30 or in 20% of HL cases and 13 of 49 or in 27% of PMBCL cases), consisting of nonsense, missense and frameshift mutations. We demonstrate that PTPN1 mutations lead to reduced phosphatase activity and increased phosphorylation of JAK-STAT pathway members. Moreover, silencing of PTPN1 by RNA interference in HL cell line KM-H2 resulted in hyperphosphorylation and overexpression of downstream oncogenic targets. Our data establish PTPN1 mutations as novel drivers in B cell lymphomagenesis.

  Study EGAS00001000554

• Neuroblastoma tumor heterogeneity and cell plasticity (from PDX and cell lines)

  Two cell identities, noradrenergic and mesenchymal, have been characterized in neuroblastoma cell lines according to their epigenetic landscapes relying on specific core regulatory circuitries of transcription factors. Yet, their relationship and relative contribution in patient tumors remain to be defined. Here, we document a spontaneous plasticity between the noradrenergic and mesenchymal identities in a subset of cell lines. Strikingly, mesenchymal neuroblastoma cells revert to a noradrenergic phenotype in vivo. Consistently, tumor cells with a mesenchymal identity are detected in single-cell transcriptomic analyses of neuroblastoma tumors and PDX models. Our data also highlight neuroblastoma intra-tumor heterogeneity with the co-existence of distinct tumor populations, including sympathoblast-like and chromaffin-like cells suggesting that neuroblastoma cells arise from a common sympatho-adrenal progenitor.

  Study EGAS00001004781

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015378

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015379

• Altered Interactions between Circulating and Tissue-Resident CD8 T Cells with the Colonic Mucosa Define Checkpoint Inhibitor Colitis

  Therapeutic immune checkpoint blockade has revolutionized oncology, but treatments are limited by immune-related adverse events, including checkpoint inhibitor colitis (irColitis). To define molecular drivers of irColitis, we profiled ~300,000 cells from the colonic mucosa and blood of 29 patients and controls. Patients with irColitis showed expanded mucosal Tregs (regulatory T cells), CD8 tissue-resident memory T cells expressing CXCL13 and Th17 gene programs, and recirculating ITGB2 CD8 T cells. Cytotoxic CD4 T cells, recirculating CD8 T cells, and endothelial cells expressing hypoxia gene programs were further expanded in colitis associated with anti-PD-1/CTLA-4 compared to in the presence of anti-PD-1 therapy. Luminal epithelial cells in irColitis patients expressed PCSK9, PD-L1, and interferon-induced signatures associated with apoptosis, increased cell turnover, and malabsorption.Raw data files from both colon and PBMCs from irColitis patients and controls have been provided to dbGaP. Count matrices derived from raw RNA-Seq data will be available through GEO accession GSE206301.

  Study phs003418

• Functional and genomic heterogeneity of long-term self-renewing compartment as the origin of treatment resistance in pancreatic tumors

  Adaptive drug-resistance mechanisms allow human tumors to evade treatment through selection and expansion of treatment-resistant clones. Here, studying clonal evolution of tumor cells derived from human pancreatic tumors, we demonstrate that in vitro cultures and in vivo tumors are maintained by a common set of tumorigenic cells that can be used to establish clonal replica tumors (CRTs), large cohorts of animals bearing human tumors with identical clonal composition. Using CRTs to conduct quantitative assessments of adaptive responses to therapeutics, we uncovered a multitude of functionally heterogeneous subpopulations of cells with differential degrees of drug sensitivity. High-throughput isolation and deep characterization of unique clonal lineages showed genetic and transcriptomic diversity underlying functionally diverse subpopulations. Molecular annotation of gemcitabine-naïve clonal lineages with distinct responses to treatment in the context of CRTs generated signatures that can predict the response to chemotherapy, representing a potential biomarker to stratify patients with pancreatic cancer. RNA-Seq data on these clones are available on EBI ENA, under accession number: PRJEB27735.

  Study EGAS00001003442

• Fetal origins of malignant germ cell tumours

  Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells (PGCs). They are uniquely able to generate embryonic and extraembryonic tissues, which in malignant GCTs carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the phylogenetic and transcriptional diversity of 15 malignant gonadal GCTs and four normal testis biopsies by sequencing 131 whole genomes and 416 transcriptomes from 14 gonadal histologies, excised by laser capture microdissection. Our findings demonstrate that tumours were initiated by whole genome duplication likely in embryogenesis, within ~5-8 cell divisions post-PGC specification, followed by chromosome 12p gains associated with invasive disease. Of note, 12p imbalances were not only generated through GCT-typical isochromosomes, but also through non-isochromosomic configurations. Whilst tumours developed along homogenous phylogenetic pathways, they spawned manifold tissues independent of genetic subclonal diversification. A key feature of GCT tissues was the expression of fetal-specific genes. The transcriptional diversity notwithstanding, we found universal transcriptional elements correlated with hallmark 12p gains. Overall, our study reveals stereotyped phylogenies and transcriptomes underpinning the development of GCT that originate in fetal life and may lend themselves to therapeutic manipulation.

  Dataset EGAD00001007037

• WGS BAM files fromxa0Genomic Features and Classification of Homologous Recombination Deficient Pancreatic Ductal Adenocarcinoma

  Background and Aims: Homologous recombination deficiency (HRD) in pancreatic ductal adenocarcinoma (PDAC), remains poorly defined beyond germline(g) alterations in BRCA1, BRCA2 and PALB2. Methods: We interrogated whole genome sequencing (WGS) data on 391 patients including 49 carriers of pathogenic variants (PVs) in g_BRCA_ and PALB2. HRD classifiers were applied to the dataset and included: 1) the genomic instability score (GIS) used by Myriad MyChoice HRD assay; 2) substitution base signature 3 (SBS3); 3) HRDetect; and, 4) Structural Variant (SV) burden. Clinical outcomes and responses to chemotherapy were correlated with HRD status. Results: Biallelic tumour inactivation of g_BRCA_ or PALB2 was evident in 43/49 germline carriers identifying HRD-PDAC. HRDetect (score ?0.7) predicted gBRCA1/PALB2 deficiency with highest sensitivity (98%) and specificity (100%). HRD genomic tumour classifiers suggested that 7-10% of PDAC that do not harbor g_BRCA/PALB2_ have features of HRD. Of the somatic HRDetect cases, 69% were attributed to alterations in BRCA1/2, PALB2, RAD51C/D and XRCC2, and a tandem duplicator phenotype. TP53 loss was more common in BRCA1- compared to BRCA2-associated HRD-PDAC. HRD status was not prognostic in resected PDAC. However in advanced disease the GIS (p=0.02), SBS3 (p=0.03) and HRDetect score (p=0.005) were predictive of platinum response and superior survival. PVs in g_ATM_ (n=6) or g_CHEK2_ (n=2) did not result in HRD-PDAC by any of the classifiers. In four patients, BRCA2 reversion mutations associated with platinum resistance. Conclusions: Germline and parallel somatic profiling of PDAC outperforms germline testing alone in identifying HRD-PDAC. An additional 7-10% of patients without gBRCA/PALB2 mutations may benefit from DNA damage response agents.

  Dataset EGAD00001007571

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Cardiff, UK (Owen)

  Study EGAS00001005855

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Edinburgh, Scotland, UK.

  Study EGAS00001005843

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Cardiff, UK (O'Donovan)

  Study EGAS00001005852

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Landen, Stockholm, Sweden.

  Study EGAS00001005838

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Stockholm, Sweden (Pedersen)

  Study EGAS00001005856

• Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

  Study EGAS00001007291

• Kinomics data

  To ellucidate protein activity in mRCC, Kinomics data was generated as part of the EuroTarget study

  Dataset EGAD50000002293

• Study2OrangeFiber

  SOMAscan plasma proteome datasets generated from participants consuming the orange fiber snack prototype (study 2)

  Dataset EGAD00010002191

• Study1PeaFiber

  SOMAscan plasma proteome datasets generated from participants consuming the pea fiber snack prototype (study 1)

  Dataset EGAD00010002192

• SolomonIslands.Dataset

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

  Dataset EGAD00010002306

• SEAsia.Oceania.Australia

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

  Dataset EGAD00010002302

• Present-day genomics from the Eurasian steppe

  502 genotypes obtained from Illumina DNA-arrays. Available as plink formatted files

  Dataset EGAD00010001538

• Bacteria Lateral sclerosis

  The study aims to find bacteria in neural tissue from patients with amyotrophic lateral sclerosis

  Dataset EGAD00001004458

• Belgian epilepsy patients

  The genomic sequence of brain expressed miRNA genes was sequenced in Belgian epilepsy patients.

  Dataset EGAD00001001851

• Swedish schizophrenia patients

  The genomic sequence of brain expressed miRNA genes was sequenced in Swedish schizophrenia patients

  Dataset EGAD00001001849

• Hessequa-descendants mitogenomes

  Complete sequence of the mitochondrial DNA of 87 Hessequa-descendant individuals

  Dataset EGAD00001007676

• Single cell RNA sequencing of synovial B cells in early Rheumatoid Arthritis

  This dataset includes 3432 paired single cell sequencing fastq files derived from synovial B cells of 5 early Rheumatoid Arthritis patients. Libraries were prepared using the SmartSeq2 protocol. All wells contained ERCC spike-ins. Libraries were sequenced on an Illumina NovaSeq instrument with 2x100bp paired-end reads yielding a median of 2.5M reads/well. Sample aliases ending on 368 and 384 represent empty control wells. Sample aliases starting with P11417_4 and P13157_1 belong to ACPA- patient A7, sample aliases starting with P11417_5 and P11417_6 belong to ACPA+ patient A1, sample aliases starting with P13157_2 belong to ACPA- patient A3, sample aliases starting with P13157_3 and P13157_6 belong to ACPA+ patient A2, sample aliases starting with P13157_4 and P13157_5 belong to ACPA- patient A4.

  Dataset EGAD00001009076

• Data access committee (DAC) in the Graduate School of Medical Science and Engineering (GSMSE) at Korea Advanced Institute of Science and Technology (KAIST)

  Dac EGAC00001001643

• DAC of The polarity and specificity of antiviral T lymphocyte responses determine susceptibility to SARS-CoV-2 infection in cancer patients and healthy individuals

  Dac EGAC00001002517

• Single-cell multi-omics defines the cell-type-specific impact of splicing aberrations in human hematopoietic clonal outgrowths

  Study EGAS00001007402

• TSO500 on DNA

  Targeted sequencing using the TruSight Oncology 500 DNA probes panel, on samples 162 and 521

  Dataset EGAD50000000270

• MiRNA_Validation

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002752

• MiRNA_TrainTest

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002754

• Gentoypes_Lesotho

  Individuals genotyped on the Illumina GSA v2. Autosome and X chromosome.

  Dataset EGAD00010002468

• Baka_saliva_450K

  Epigenome of 36 rainforest hunther-gathering Baka of Cameroon by Illumina HumanMethylation450 array, used in the EGAS00001002226 study

  Dataset EGAD00010001251

• RNA Editing AZIN1 amplicon sequencing

  AZIN1 amplicon sequencing data of the EGAS00001000495 project.

  Dataset EGAD00001000708

• Metadata file

  "Master" file of patient clinical characteristics and outcomes, samples, and the results of certain analyses, including immunohistochemistry.

  Dataset EGAD00001008792

• Tracing the origins of relapse in AML to stem cells

  Aligned whole genome sequence from AML relapse project

  Dataset EGAD00001003234

• IRF5 HL RNASeq dataset

  bam files associated with the study EGAS00001001205

  Dataset EGAD00001001417

• Landscape of AL mutations

  Exome Sequencing to Define the Landscape of Plasma Cells in Systemic Light chain Amyloidosis

  Dataset EGAD00001001861

• AI_NF1glioma_WES

  The dataset includes 59 tumor samples from 56 NF1-glioma patients profiled by Whole Exome Sequencing.

  Dataset EGAD00001004375

• ICR MOPOPGEN UK exome control series

  BAM files of individuals from the 1958BC aligned to hg17

  Dataset EGAD00001004396

• Dataset for hepatopancreaticobiliary_malignancy-RNA

  Rare cancer sequencing data of 119 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008863

• The cellular immune and airway epithelial profile throughout childhood and in response to COVID-19 at multi-omic single cell level.

  Single-cell data gene expression data set (5’Chromium 10X) of healthy paediatric volunteers, and paediatric and adult COVID-19 patients. Gene expression was determined from samples of nasal, tracheal and bronchial brushings and blood (PBMCs). In addition to gene expression, PBMC’s were assayed by CITE-seq. A subset of samples have VDJ sequencing data for T cell receptors (TCR) and B cell receptors (BCR).

  Dataset EGAD00001007718

• Czech Roma and non-Roma array data

  42 Roma and 52 non-Roma Czech volunteers genotyped with the Axiom TM genome-wide human origins array

  Dac EGAC50000000478

• Reproducibility of 10x Genomics single cell RNA sequencing method in the immune cell environment

  Study EGAS00001005905

• Metabolic requirements of the metastasis-initiating tumour cell population using oral squamous cell carcinoma (OSCC) as a model system

  Study EGAS00001004765

• cfDNA shallow Whole-Genome sequencing - healthy donors

  sWGS of the blood samples from 14 (fourteen) healthy donors

  Dataset EGAD50000001860