11750 results for "cancer rna-seq"

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• WGS and RNA-Seq data from a GBM patient PT-BK0248

  WGS and RNA-Seq data from a GBM patient PT-BK0248

  Dataset EGAD00001004228

• WGS and RNA-Seq data from a GBM patient PT-LS4891

  WGS and RNA-Seq data from a GBM patient PT-LS4891

  Dataset EGAD00001004252

• WGS and RNA-Seq data from a GBM patient PT-AB0029

  WGS and RNA-Seq data from a GBM patient PT-AB0029

  Dataset EGAD00001004221

• WGS and RNA-Seq data from a GBM patient PT-LR9369

  WGS and RNA-Seq data from a GBM patient PT-LR9369

  Dataset EGAD00001004251

• WGS and RNA-Seq data from a GBM patient PT-JP2405

  WGS and RNA-Seq data from a GBM patient PT-JP2405

  Dataset EGAD00001004247

• RNA-seq CLL

  RNA-seq of peripheral blood samples from CLL patients.

  Dataset EGAD00001001675

• WGS and RNA-Seq data from a GBM patient PT-JB1730

  WGS and RNA-Seq data from a GBM patient PT-JB1730

  Dataset EGAD00001004245

• RNA-seq sequence data from DNMT3A microcephalic dwarfism patients.

  RNA-seq data generated from cells from control individuals and individuals with de novo DNMT3A variants causing microcephalic dwarfism.

  Dataset EGAD00001004471

• Transcriptome profiling of 25 prostate tumor samples by RNA-Seq

  Transcriptome profiling of 25 prostate tumor samples by RNA-Seq

  Dataset EGAD00001003344

• WGS and RNA-Seq data from a GBM patient PT-RL7940

  WGS and RNA-Seq data from a GBM patient PT-RL7940

  Dataset EGAD00001004258

• RNA-Seq files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  RNA-Seq files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  Dataset EGAD00001000878

• RNA-Seq data for Mesothelioma.

  RNA-Seq data for Mesothelioma.

  Dataset EGAD00001001915

• Defining and Overcoming Intrinsic T Cell Dysfunction to Enable Pediatric Immunotherapy

  T-cells from 71 children and young adults with B-cell malignancies on trial to receive anti-CD19 CAR T-cell therapy were analyzed. These T-cells represent the pre-manufacture T-cells that were subsequently used for CAR T manufacture. Bulk RNA-Seq was performed on sorted T-cell subsets for all patients, in addition to CITE-Seq and single-cell ATAC-Seq on a subset of 6 patients. The primary clinical outcome was duration of B-cell aplasia, a surrogate measure of functional CAR T-cell persistence. From these data, molecular signatures associated with long and short-term CAR T-cell persistence were identified. This data submission includes bulk RNA-Seq, CITE-Seq, and single-cell ATAC-Seq data from this study.

  Study phs002323

• Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data

  Systematic interrogation of single nucleotide variations (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single cell level. While SNV detection from abundant single cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed. Here, we performed a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, using both simulation and scRNA-seq datasets, and identified multiple elements influencing their performance. Our study provided the first benchmarking to evaluate the performances of different SNV detection tools for scRNA-seq data.

  Study EGAS00001003883

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. One possibility for this inefficiency is an incomplete understanding of the molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to develop a foundational dataset for identifying candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Study EGAS00001003667

• Identification of Recurrent SMO and BRAF Mutations in Ameloblastomas

  RNA-seq data from two cases of ameloblastoma was analyzed for candidate gene fusions and point mutations. Recurrent point mutations identified in the RNA-seq data, as well as mutations identified with limited panel targeted deep sequencing, were validated as somatic. Expanding to a larger cohort of 28, one of two activating mutations was found in 80% of cases. No recurrent gene fusions events were identified.

  Study phs000739

• Transcriptome analysis of iPSC-derived hepatocytes from Wilson's Disease patients and healthy controls

  To identify the differences in global gene expression patterns in WD-specific hepatocytes, we performed RNA-seq analysis. Six WD-specific hepatocytes and 6 healthy-donor (HD) hepatocytes were compared in total. The data suggested that our RNA-seq data were partially validated in the context of ATP7B deficiency and that these overlapped genes might be regulated by ATP7B deficiency among mammalian species in common.

  Study JGAS000382

• Discriminating Th17.1 cell driven sarcoidosis-like inflammation from relapse after anti-BCMA CAR T cells in multiple myeloma

  We present a case study on sarcoidosis-like flare-up after Idecabtagen Vicleucel (Ide-cel), a BCMA targeting CAR T cell therapy, and identified a Th17.1 driven autoimmune mechanism as the biological underpinning of this phenomenon using single-cell RNA-seq analysis. Furthermore, single-cell RNA-seq allowed to discriminate between immune-mediated changes and true relapse after CAR T cell treatment.

  Study EGAS00001006133

• Transcriptomic subgroups in soft tissue tumors correlate with morphologic subtype, genomic features, and outcome

  We assessed gene expression (GGE) profiles and gene fusions as detected by transcriptome sequencing (RNA-seq) of 704 soft tissue tumors (STT) representing 56 different tumor types. Comparison with follow-up data identified transcriptional subclusters among sarcomas with complex genomes and among adipocytic tumors that correlated with metastasis-free survival and local recurrences, respectively. Thus, RNA-seq analysis of STT provides clinically important information.

  Study EGAS50000001472

• Whole-exome and RNA sequencing data from a uveal melanoma patient with multi-regional sampling

  This dataset includes whole-exome sequencing (WES) and RNA sequencing (RNA-seq) data from a uveal melanoma patient. Tumor samples were obtained from three distinct regions, each with matched RNA-seq and WES data. Additionally, WES data from the patient’s peripheral blood mononuclear cells (PBMCs) is provided as a germline reference.

  Dataset EGAD50000001422

• TIRE-seq: an Integrated Sample Extraction and Transcriptomics Workflow for High Throughput Perturbation Studies

  TIRE-seq is a novel RNA sequencing method that integrates mRNA purification directly into library preparation, eliminating separate RNA extraction. The technique demonstrated utility across three biological applications, including capturing transcriptional changes in human T cells, identifying genes driving murine dendritic cell differentiation, and analyzing the dose-response effects of temozolomide on patient-derived neurospheres. With its simplified approach and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies.

  Study EGAS50000000867

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Dataset EGAD00001007872

• Single cell RNA-seq profiling of CD8 T cells from elder adults

  Single cell RNA-seq profiling of ~62k purified CD8+ T cell transcriptomes, from six healthy older adult donors using 10X genomics. Cells from each donor were separated based on their IL-7R protein expression (i.e. CD8+ IL7R+ and CD8+ IL7R- T cells).

  Study EGAS00001004255

• BLUEPRINT RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000284

• Indonesian RNA-seq dataset

  This dataset contains 4 batches of Indonesian RNA-seq data from Mentawai, New Guinea and Sumba islands. One RNA-seq batch was prepared without Globin depletion, and three batches were Globin depleted using the Illumina Globin-Zero Gold Kit. There are 179 runs in total, including 119 unique samples. Dataset includes multiple batch control samples.

  Dataset EGAD00001005053