7190 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

in 47.01 milliseconds.

• Integrated Genomic and Transcriptomic Analysis of Small Cell Lung Cancer Reveals Inter- and Intratumoral Heterogeneity and a Novel Chemotherapy-Refractory Subtype

  We integrated histology, transcriptome, exome, and treatment outcomes of small cell neuroendocrine cancer (SCNC) from a range of metastatic sites, revealing complex intra- and intertumoral heterogeneity of neuroendocrine (NE) differentiation and transcriptomic subtypes (ASCL1, NEUROD1, POU2F3, YAP1 and ATOH1). High NE SCNCs were more likely to benefit from replication stress-targeted therapies, in contrast to non-NE tumors which were more likely to respond to immune response-targeted therapies.

  Study phs002541

• Epigenetic and transcriptional profile of memory B cells in Multiple sclerosis

  Methylome and transcriptome data of non-proliferating and autoproliferating memory B cells (CD27+) from Multiple sclerosis patients under natalizumab treatment, that have been generated and analyzed for the study "T-bet+ CXCR3+ B cells drive hyperreactive B-T cell interactions in multiple sclerosis". Aim is to understand epigentic and transcriptional differences in activated memory B cells in MS and how epigentic differences translated in transcriptional changes in the same patient.

  Study EGAS50000000872

• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• Sarcopenia related to Head and Neck squamous cell carcinomas: transcriptome modifications of muscle cells induced by distant malignant cells

  The biological mechanisms of sarcopenia are still very poorly understood, particularly in the case of Head and Neck Squamous Cell Carcinomas (HNSCC). However, there is good reason to believe that diffusible factors originating from tumor cells exert a distant deleterious effect on muscle cells. To test this hypothesis we implemented a dual approach based both on experiments carried out in vitro and on the study of muscle fragments from patients.

  Study EGAS50000000669

• Whole-genome sequencing reveals genomic signatures associated with the inflammatory microenvironments in Chinese NSCLC patients

  Chinese lung cancer patients have distinct epidemiologic and genomic features, highlighting the presence of specific etiologic mechanisms other than smoking. We integrate genomic (whole-genome sequencing, WGS) and transcriptome (polyA-enriched RNASeq) sequencing from 92 NSCLC cases and comprehensively identified the distinct genomic features of Chinese NSCLC patients. We reveal that inflammatory infiltration may contribute to the accumulation of EGFR mutations, especially in never-smokers.

  Study EGAS00001002954

• Molecular subtypes of malignant peritoneal mesothelioma

  Malignant Peritoneal Mesothelioma (PeM) is a rare but frequently fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no targeted therapies for PeM yet exist. This study performs comprehensive integrative analysis of genome, transcriptome, and proteome of treatment-naive PeM tumors with the aim of identifying mesothelioma-related molecular alterations and potentially identifying novel treatment strategies.

  Study EGAS00001002820

• UROMOL 2020 - SNP data

  The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters.

  Study EGAS00001004862

• BAM files: Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  cDNA depleted RNA (500ng total RNA input) was fragmented to 150-200 nucleotides in first strand buffer for 3 minutes at 94°C. Random hexamer primed first strand was generated in presence of dATP, dGTP, dCTP and cTTP. Second strand was generated using dUTP instead of dTTP to tag the second strand. Subsequent steps to generate the sequencing libraries were performed with the KAPA HTP Library Preparation Kit for Illumina sequencing with minor modifications, i.e., after indexed adapter ligation to the dsDNA fragments, the library was treated with USER enzyme (NEB_M5505L) in order to digest the second strand derived fragments. After amplification of the libraries, samples with unique sample indexes were pooled and sequenced paired-end 2x50bp on a HiSeq2500 system following standard Illumina guidelines.

  Dataset EGAD00001003806

• Sequencing data for oesophageal and related samples - Normals release 3 (RNA)

  Dataset EGAD00001003902

• Sequencing data for oesophageal and related samples - Normals release 5 (RNA)

  Dataset EGAD00001005384

• Sequencing data for oesophageal and related samples - Normals release 2 (RNA)

  Dataset EGAD00001003838

• Sequencing data for oesophageal and related samples - Normals release 4 (RNA)

  Dataset EGAD00001004022

• mCEL-Seq2 analysis of human brain tissues and border regions

  mCEL-Seq2 analysis with reference mapping of human brain tissues and border regions

  Dataset EGAD50000000046

• 16SV4 ribosomal RNA gene sequencing data

  16SV4 ribosomal RNA gene sequencing data of GI samples and associated mixed community cultures collected from pediatric patients at risk for IBD.

  Dataset EGAD50000000485

• Metabolic and molecular consequences of the TBC1D4 p.Arg684Ter variant in human skeletal muscle

  Skeletal muscle of Inuit homozygous carriers of the common Greenlandic TBC1D4 p.Arg684Ter variant is severely insulin resistant but have normal metabolic responses during exercise

  Dataset EGAD50000000059

• Cell subtypes subsets from subcortical MS snRNA-seq atlas

  Curated subsetting of cell subtypes derived from the 9 principal cell types within our subcortical Multiple Sclerosis (MS) lesions snRNA-seq atlas.

  Dataset EGAD50000000522

• Studying the cellular diversity of the human hypothalamus

  We use single-cell and spatial transcriptomics to catalogue cellular populations and their locations in the human hypothalamus

  Study EGAS50000000716

• Spatial transcriptomics analysis of triple negative breast cancers

  Spatial transcriptomics analysis of triple negative breast cancers Both bulk sequencing and ST were performed Counts, images etc are available at https://zenodo.org/doi/10.5281/zenodo.8135721

  Dataset EGAD50000000686

• A distinct monocyte cellular state links systemic immune dysregulation to pulmonary impairment in long COVID

  single cell multiome dataset (snRNA-seq + snATAC-seq) from PBMC of patients with long COVID disease.

  Dataset EGAD50000001729

• single cell transcriptomics fastq files from PBMC of long COVID patients

  This dataset consists of 8 patients' data fastq files. 4 in each LR1 and 4 in LR2. the dataset was generated using 10X genomics and novaseqX.

  Dataset EGAD50000001730

• Visium CytAssist Spatial Gene Expression analysis for FFPE glioblastoma samples

  This study used spatial transcriptomics to investigate gene expression patterns in FFPE glioblastoma tumor samples from four patients.

  Study EGAS50000001242

• Multi-omics characterisation of immune cells in Long Covid

  We generated 10X Multiomics (paired RNA+ATAC) for Long Covid patients with up to 14 months follow-up.

  Study EGAS50000000142

• Single-cell RNAseq data from 6 Invasive Lobular Carcinoma (ILC)

  Fastq files of single-cell RNAseq data from from Cancer Associated Fibroblasts (CAFs), cancer cells and immune cells isolated from 6 primary Invasive Lobular Carcinomas (ILCs)

  Dataset EGAD50000001121

• GOSH_Tumour_Embryology_Paediatric_Behjati_RNA_Managed_Access

  The aim of the study is to study thyroid development and function, and how this is altered in Down Syndrome and Thyroid Cancer.

  Study EGAS00001006737

• The mutational landscape of skin tumours in CYLD cutaneous syndrome

  This dataset contains genomic and transcriptomic profiling of skin samples (74) from patients with CYLD cutaneous syndrome

  Dataset EGAD00001005305