9987 results for "cancer rna-seq"

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• Reference epigenome SMC08_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC08_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003852

• Reference epigenome SMC06_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC06_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003850

• Reference epigenome SMC01_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC01_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003845

• Reference epigenome SMC02_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC02_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003846

• Reference epigenome SMC03_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC03_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003847

• Reference epigenome SMC04_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC04_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003848

• Reference epigenome SMC05_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC05_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003849

• Reference epigenome SMC07_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC07_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003851

• Reference epigenome SMC09_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC09_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003853

• MuTHER_adipose_tissue_small_RNA_expression

  We investigate the naturally occurring variation of small RNA expression in conjunction with genetic and gene expression variation. We shall assess the variation in subabdominal fat tissue small RNA levels in 168 unrelated MuTHER individuals. Using gene expression data from the same samples, we can survey how much the small RNA expression contributes to the variance in gene expression profiles. We can also take advantage of the high density genotyping data on these samples to identify genetic associations of small RNA expression levels, and the downstream effect of the genetic variants in small RNA sequence. Previous small RNA sequencing efforts have also extended the repertoire of small RNAs, and we hope to potentially find additional small RNAs active in adipose tissue biology. Altogether, the project should provide an exciting view into small RNA biology in humans, and lead to development of new methodology for analysis of molecular phenotype data.

  Study EGAS00001000212

• Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

  The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

  Study phs003322

• Melanoma and Cancer-Associated Fibroblast Short-Term Cultures Derived from Patient Metastases

  The purpose of this study was to obtain tissue specimens derived from patients with melanoma to generate research tools to advance our understanding of the genetics, pathogenesis, and therapeutics of melanoma. Briefly, tissue was obtained from metastatic lesions and used to generate clonal primary cell lines from melanoma cells and fibroblasts from the tumor microenvironment. RNA was extracted from low passage cell lines using Trizol reagent. cDNA libraries were prepared using the TruSeq mRNA sample preparation kit, v2 (Illumina) and sequenced on the HiSeq 2000 platform (Illumina). The submitted files are bam files that contain both unaligned and aligned reads (human genome, build hg19).

  Study phs001115

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Study EGAS00001006935

• STAG2-ChIP-Seq of STAG2-mutated and cohesin-wildtype adult AMLs

  ChIP-Seq targeting the cohesin subunit STAG2 in STAG2-mutant or cohesin wildtype adult AMLs.

  Dataset EGAD00001011205

• Gene regulation of human CD4+ Treg ChM-seq

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ChM-seq (118 H3K4me3, 118 H3K27ac and 6 inputs). The final quality filtered set included 91 individuals with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq.

  Dataset EGAD00001004828

• ChIP-seq fastq and alignment files

  ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

  Dataset EGAD00001006279

• ChIP-seq bulk

  This dataset gather ChIP-seq data produced by immunoprecipitating CTCF factor in own laboratory in MM.1S cell line in EtOH and Dex conditions. It also gather ChIP-seq dataset produced by external laboratory (Active Motif) for H3K27ac mark and GR transcription factor in same cell line and conditions ( MM.1S ETOH/Dex)

  Dataset EGAD00001011136

• BLUEPRINT Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  Study EGAS00001001638

• Chip-Seq sequencing data of Atypical teratoid/rhabdoid tumors (ATRT)

  Chip-Seq sequencing data of Atypical teratoid/rhabdoid tumors (ATRT)

  Dataset EGAD00001003408

• Reference epigenome ADMSC01_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC01_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003854

• Reference epigenome ADMSC02_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC02_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003855

• Reference epigenome ADMSC03_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC03_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003856

• Reference epigenome ADMSC04_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC04_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003857

• CTCF-ChIP-Seq of cohesin-mutated and wildtype adult AMLs

  ChIP-Seq targeting CTCF in cohesin-mutated (STAG2 or RAD21 mutations) and wildtype adult AMLs (CTRL-AMLs).

  Dataset EGAD00001011200

• Epigenomics and Single-cell Sequencing Define a Developmental Hierarchy in Langerhans Cell Histiocytosis

  Langerhans cell histiocytosis (LCH) is a rare neoplasm predominantly affecting children. It occupies a hybrid position between cancers and inflammatory diseases, and it provides an attractive model for studying cancer development. To explore the molecular mechanisms underlying the pathophysiology of LCH and its characteristic clinical heterogeneity, we investigated the transcriptomic and epigenomic diversity in primary LCH lesions. Using single-cell RNA sequencing, we identified multiple recurrent types of LCH cells within these biopsies, including putative LCH progenitor cells and several subsets of differentiated LCH cells. We confirmed the presence of proliferative LCH cells in all analysed biopsies using immunohistochemistry, and we defined an epigenomic and gene-regulatory basis of the different LCH cell subsets by chromatin accessibility profiling. In summary, our single-cell analysis of LCH uncovered an unexpected degree of cellular, transcriptomic, and epigenomic heterogeneity among LCH cells, indicative of complex developmental hierarchies in LCH lesions.

  Study EGAS00001003822