17516 results for "free coins in fc 26 Visit Buyfc26coins.com for latest FC 26 coins news..Y2KA"

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• RNA_expression_profiling_of_melanoma_patient_derived_xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growthThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001537

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000947

• Mutation_analysis_in_human_iPS_cells_

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced by MiSeq. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000359

• Whole Exome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Whole Exome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003434

• Gut metagenome/FINRISK 2002 (Salosensaari et al. Nature Comms 2021)

  The main goal of the project is the study the associations between the gut metagenome and human health. The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012).

  Study EGAS00001005020

• Single cell transcriptomes of of primary tumors and normal endometrial derived organoids treated with DBZ

  Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumours, and on organoids both treated with DBZ and normal and found both secretory-like and ciliated-like tumour cells.

  Dataset EGAD00001006280

• A108759B

  Whole genome sequencing for single cells for library A108759B 1134 cells; filetype=bam

  Dataset EGAD00001007088

• A108768B

  Whole genome sequencing for single cells for library A108768B 1126 cells; filetype=bam

  Dataset EGAD00001007089

• Follicular lymphoma shallow whole genome sequencing and targeted sequencing of lymphoma panel

  Stage I and stage III/IV Follicular lymphoma samples, shallow whole genome sequencing for copy number analysis and targeted capture sequencing for mutation and translocation analysis.

  Dataset EGAD00001008385

• Shallow whole genome sequencing and targeted capture sequencing data of PCNSL and PTL primary and relapse pairs

  Shallow whole genome sequencing for copy number analysis and targeted capture sequencing data for translocation and mutation anslysis of paired primary and relapse PCNSL and PTL samples

  Dataset EGAD00001008387

• WGS files for Klco RPAML

  WGS files for Klco RPAML study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008413

• Mucosal 16S metadata

  Metadata for 16S-V4 rRNA gene sequence data for intestinal biopsies from NCT02749630 trial participants.

  Dataset EGAD00001008823

• Single Cell Genome Sequence for DLP+ library A108765A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1181A passage 1 on DLP library A108765A

  Dataset EGAD00001009428

• Single Cell Genome Sequence for DLP+ library A110660A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA610 passage 3 on DLP+ library A110660A

  Dataset EGAD00001009430

• Single Cell Genome Sequence for DLP+ library A96213A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6, cell line SA1090 on DLP+ library A96213A

  Dataset EGAD00001009477

• Single Cell Genome Sequence for DLP+ library A98181A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA919 passage 7, patient-derived xenograft SA1050A passage 1 on DLP+ library A98181A

  Dataset EGAD00001009479

• Single Cell Genome Sequence for DLP+ library A98279A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050A passage 1, patient SA1234 on DLP+ library A98279A

  Dataset EGAD00001009486

• Single Cell Genome Sequence for DLP+ library A95621B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A95621B

  Dataset EGAD00001009487

• Single Cell Genome Sequence for DLP+ library A95621A

  Single Cell Genome Sequence for Immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 112.109 cell line SA1055 on DLP+ library A95621A

  Dataset EGAD00001009488

• Breast cancer topographs

  Whole genome sequencing to identify subclonal variants for subsequent mapping back to fixed tissue specimens. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010124

• 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). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• Resilience and Susceptibility Patterns in the Viral Immune Response Using RNA-Seq (ReSP VIRUS Study)

  This is a cross sectional study to investigate the relationship between nasal mucosa gene expression and clinical outcomes in infants with critical Respiratory Syncytial Virus (RSV) infection. We collected nasal mucosa samples from infants admitted to the pediatric intensive care unit with polymerase chain reaction confirmed RSV bronchiolitis. Samples were obtained by mucosal scrape biopsy of the inferior turbinate using a sterile plastic curette and bulk RNA-sequencing of mRNA was performed. Clinical data was extracted from the electronic health record including: demographics, medical history, duration of symptoms, time from admission to sample collection, hospital and intensive care unit length of stay, and type and duration of respiratory support.

  Study phs003053

• A Cultured Leukemia Stem Cell Model Enables Validation of CDK6 as a Stemness Target Against Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) represents a group of aggressive hematological malignancies, the clinical management of which is made challenging due to the persistence of rare and therapy resistant leukemia stem cells (LSCs) which serve as a source of disease relapse and poor outcomes. There are currently a paucity of methods to reliably enrich and study LSCs, hindering the development of therapies that specifically target LSCs. In this study, we deeply characterize the OCI-AML8227 culture model, which maintains a functional stemness hierarchy originating from its highly primitive CD34⁺CD38⁻ cells, to elucidate LSC biology and uncover LSC-specific therapeutic vulnerabilities. We analyzed both bulk and single-cell proteomics, transcriptomics, and epigenomics to generate a LSC protein-protein interaction network, which was then integrated with an LSC-focused small molecule screen using this model. From these findings, CDK6 was discovered as a therapeutic vulnerability specific to LSCs, which was validated in findings from the BEAT-AML cohort and a patient-derived xenograft (PDX) panel of AML samples through palbociclib treatment. Taken together, our studies validate CDK6 as a druggable vulnerability in LSCs, and authenticate OCI-AML8227 cells as a LSC target discovery engine.

  Dataset EGAD50000001156

• EGA submission account terms

  Submission account terms Each EGA submission account has a dedicated submission box. To ensure continued service to all submitters EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. Those that are near to or exceeding this value will be monitored on a weekly basis by the helpdesk team and the submitter will be contacted and guidance provided accordingly on completing their metadata registration. You will be able to register your metadata associated with the files in your submission account via EGA Submitter Portal, Webin or the EGA REST API. EGA also requests that metadata is submitted within 60 days of upload data to a submission box. When we detect files that are over 60 days old in a submission box we will notify the submitter requesting that metadata be submitted or the files removed from the submission box. It is important to note that data is not archived at the EGA until the metadata describing the files has been associated and the archival process has completed. It is only when associated metadata has been submitted that the archival process into EGA is fully triggered. EGA removes files from the submission box once they have been successfully archived, so no action is required by a submitter to remove successfully archived files. Files over 90 days old will be deleted from the submission box unless EGA Helpdesk has been contacted and confirmed an exemption with the submitter.

  Documentation submission/terms

• Origins and timing of emerging lesions in advanced renal cell carcinoma

  Renal cell carcinoma (RCC) with venous tumor thrombus (VTT) arising from the primary tumor occurs in ~10% of cases and is thought to represent more advanced disease. RCC with VTT and distant metastasis provides unique opportunities to examine the origins and relative timing of tumor lesion emergence and to identify molecular correlates with disease state. We performed multi-region exome and RNA sequencing analysis of a clinical cohort of 16 RCC patients with VTT, with eight patients also having sequenced metastasis, to examine which genomic alterations, biological pathways, and evolutionary processes contribute to VTT and metastasis, and to ask whether metastasis typically arises directly from VTT or is independent of VTT.

  Study EGAS00001005897