12214 results for "cancer rna-seq"

in 21.78 milliseconds.

• Single-Cell Multi-Omic Analysis of the Vestibular Schwannoma Ecosystem Uncovers a Nerve Injury-Like State

  Vestibular schwannomas are benign tumors that can lead to significant morbidity, including hearing loss, facial nerve paralysis and obstructive hydrocephalus. The genomic landscape of vestibular schwannomas is relatively bland and the molecular pathophysiology of vestibular schwannomas is poorly understood. Therefore, we performed single cell RNA sequencing on 15 sporadic vestibular schwannomas, with paired single cell ATAC sequencing (n = 6) and whole exome sequencing (n = 12) to perform a detailed characterization of the vestibular schwannoma tumor microenvironment at the transcriptional and epigenetic level. We validated our results by analyzing bulk RNA sequencing data from 22 newly sequenced vestibular schwannomas and 173 previously sequenced bulk RNA sequencing data from 195 vestibular schwannomas. Data available in dbGaP include whole exome sequencing of 12 tumors and matched blood samples. Matching single cell RNA sequencing and single cell ATAC sequencing data is available via NCBI GEO.

  Study phs003318

• TSO500 on RNA

  TruSight Oncology 500 RNA probes panel on case 521

  Dataset EGAD50000000271

• RNA sequencing of myxofibrosarcoma

  RNA sequencing (fastq files) of 29 samples of myxofibrosarcoma

  Dataset EGAD00001004102

• BLUEPRINT September 2016, ChIP-Seq for thymocyte from thymus, on Genome GRCh38

  ChIP-Seq data for 5 sample(s) for thymocyte from thymus, on Genome GRCh38. 17 run(s), 17 experiment(s), 17 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002947

• ChIP-Seq on multiple myeloma and plasma cell leukaemia cell lines

  ChIP-seq data (H3K4Me1, H3K4Me3, H3K27Ac histone modifications) in experimental triplicates on multiple myeloma cell line KMS11 and plasma cell leukaemia cell lines L363 and JJN3. ChIP reactions were performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal Kit. ChIP libraries were generated using HTP Illumina library preparation kit, and sequenced using Illumina HiSeq 2000 with 100 bp single-ended reads. ChIP-seq files are in BED format.

  Dataset EGAD00001003349

• ATAC-seq data from primary AML samples with t(3;8)

  Open chromatin regions in the MYC super-enhancer region were investigated by ATAC-seq in t(3;8) AML. ATAC-seq was performed as described (Buenrostro et al, 2013) with a modification in the lysis buffer (0.30 M sucrose, 10 mM Tris pH 7.5, 60 mM KCl, 15 mM NaCl, 5 mM MgCl2, 0.1 mM EGTA, 0.1% NP40, 0.15 mM Spermine, 0.5 mM Spermidine, 2 mM 6AA) to reduce mitochondrial DNA contamination.

  Dataset EGAD00001007910

• ATAC-seq dataset of patient and healthy donors

  ATAC-seq dataset on a patient (P) presenting with defects of immunity and two (C5, C6) healthy donors. This dataset contains raw and processed files from ATAC-seq chromatin accessibility analysis. There are 3 single-read (50 bp) fastq files (1 per patient/ donor). Processed files consist of narrowPeak files (1 per patient/ donor) and one file that contains read counts in consensus peaks.

  Dataset EGAD00001008370

• DAC for "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling"

  This is the DAC for the study "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling" of PD Dr. Aurélie Ernst (a.ernst@dkfz.de) B420, DKFZ.

  Dac EGAC50000000452

• ATAC-seq samples from 9 cHL cell lines

  The dataset contains 21 ATAC-seq samples from 9 cHL cell lines. Files within the dataset are raw fastq files for each cell line.

  Dataset EGAD50000001273

• IVF MeDIP-seq bam files

  Bam files consisting of aligned MeDIP-seq reads from cord blood cells and cord blood mononuclear cells of twins conceived through in vitro fertilisation

  Dataset EGAD00001003158

• Single-cell RNA-sequencing for peripheral blood mononuclear cells and plasma proteomics data from COVID-19 patients and healthy controls of Japanese

  We performed single-cell RNA-sequencing of peripheral blood mononuclear cells and measured plasma protein expression from COVID-19 patients and healthy controls.

  Study JGAS000783

• RNA sequencing of skin tissue and peripheral blood mononuclear cells from patients with atopic dermatitis and healthy controls.

  We performed RNA-sequencing of skin tissue and peripheral blood mononuclear cells obtained from patients with atopic dermatitis along with healthy controls in Japanese population.

  Study JGAS000628

• Long-read and short-read RNA sequencing of human normal liver organoid with or without SF3B4 overexpression

  There are 2 matched short and long read RNA sequencing samples. The project aims to find alternative splicing events and resulting transcript isoforms modulated by SF3B4

  Study EGAS50000001131

• Small RNA sequencing of human oocytes and early embryos

  This study looks at small RNA expression in human oocytes (n=12), zygotes (n=5), and embryos (n=10). The sample preparation and sequencing were done in two batches.

  Study EGAS50000000157

• Paired RNA sequencing of Thymic epithelial tumors - Additional Dataset

  Paired RNA sequencing of additional samples of Thymic epithelial tumors. Uploaded are the paired fastq files, sequencers were Illumina HiSeq 2500, HiSeq 4000, NovaSeq 6000 and HiSeq X Ten. The kits used were Illumina Truseq RNA and Illumina Truseq stranded mRNA.

  Dataset EGAD50000000324

• Bulk RNA-sequencing of AML blasts pre and post culture

  This dataset contains 18 Fastq files from 9 samples (pre-culture (n=3), post culture in standard (n=4) or niche-llike (n=2) conditions) from 4 patients.They correspond to bulk RNA sequencing on Illumina instrument of libraries prepared using SMARTer Universal Low Input RNA Kit.

  Dataset EGAD00001008773

• HipSci - Congenital Hyperinsulinia - RNA Sequencing - July 2017

  HipSci - Congenital Hyperinsulinia - RNA Sequencing - July 2017

  Dataset EGAD00001003534

• HipSci - Embryonic Stem Cells - RNA Sequencing - April 2016

  HipSci - Embryonic Stem Cells - RNA Sequencing - April 2016

  Dataset EGAD00001002000

• Asthma in the Lives of Families Today (ALOFT)

  Social interactions and the overall psychosocial environment have a demonstrated impact on health, particularly for people living in disadvantaged urban areas. Here we investigated the effect of psychosocial experiences on gene expression in peripheral blood immune cells of 251 children with asthma in Metro Detroit. Participants were included from an ongoing longitudinal study Asthma in the Lives of Families Today (ALOFT; recruited from November 2010-July 2018. The ALOFT project was established to identify the behavioral and biological pathways through which family social environments impact youth with asthma.In version 1 we used RNA-sequencing and a new machine learning approach to identify transcriptional signatures of 19 variables including psychosocial factors, blood cell composition and asthma symptoms. Using longitudinal data collected from a subset of the participants we showed that transcriptional signatures track the longitudinal changes in measured phenotypes. Importantly, we found 169 genes associated with asthma that are regulated by psychosocial factors, and 344 significant gene-environment interactions for gene expression levels. These results demonstrate that immune gene expression mediates the link between negative psychosocial experiences and asthma risk.In version 2, we focused on pubertal development. We identified substantial gene expression changes associated with age and pubertal development. We showed that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.Version 3 uses single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.Version 4 adds scATAC-seq in activated peripheral blood mononuclear cells (PBMC) from 16 children with asthma with phytohemagglutinin (PHA) or lipopolysaccharide (LPS), and treated with dexamethasone (DEX), an anti-inflammatory glucocorticoid. We analyzed changes in chromatin accessibility, measured transcription factor motif activity, and identified treatment and cell-type specific transcription factors that drive changes in both gene expression mean and variability. We observed strong positive linear dependence between motif response and their target gene expression changes, but negative in variability changes. This result suggests that an increase of transcription factor binding tightens the variability of gene expression around the mean. We then annotated genetic variants in chromatin accessibility peaks and response motifs followed by computational fine-mapping of eQTL signals from a pediatric asthma cohort. We found that eQTLs were 5-fold enriched in peaks with response motifs and refined the credible set for 410 asthma risk genes, with 191 having the causal variant in response motifs. These results enhance the understanding of molecular mechanisms for asthma risk variants mediated by gene expression.

  Study phs002182

• RNA sequencing of Resistant BCC samples.

  RNA sequencing of Resistant BCC samples.

  Dataset EGAD00001000881

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. We performed multi-omic analysis including whole-exome, RNA and miRNA sequencing and quantification of 126 proteins in a series 34 LCCL coupled with a screening of 29 anti-cancer agents. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular "proliferation class" of HCC. Genomic alterations of the RAS-MAPK pathway correlated with trametinib sensitivity that was more potent than FGFR4 inhibitors in tumor cells depending on the FGF19/FGFR4 pathway. Moreover, we showed that FGF19 amplification was only functional in tumor cells that retained a hepatocyte differentiation program with expression of FGFR4, KLB and NR1H4 highlighting the complex interplay between the genomic and transcriptomic context in drug response. We also identified drugs/combination that could target efficiently the transcriptomic "progenitor subclass of HCC", as well as specific genetic contexts such as inactivating mutations in TSC1/TSC2 and TP53 associated with higher sensitivity to the mTOR inhibitor rapamycin and the AURKA inhibitor alisertib, respectively. LCCL represent relevant preclinical models for drug-biomarker discovery in HCC and enabled to identify molecular contexts linked with particular therapeutic vulnerabilities that may be useful to stratify patients in future clinical trials

  Study EGAS00001003536

• WES and Panel-seq data of pediatric tumors

  Paired-end WES and targeted Panel-seq data from 140 pediatric tumor samples. Sequencing was performed on Illumina HiSeq 4000, MiSeq or HiSeq 2500.

  Dataset EGAD50000000577

• non-IVF MeDIP-seq bam files

  Bam files consisting of aligned MeDIP-seq reads from cord blood cells and cord blood mononuclear cells of twins not conceived through in vitro fertilisation

  Dataset EGAD00001003159

• ATAC-seq of spermatogonia

  Raw sequencing reads of ATAC-seq of spermatogonia in FASTQ format, comprising 6 samples sequenced on the Illumina HiSeq 4000 platform.

  Dataset EGAD00001007759

• Neuroblastoma Cell Line Circle-seq Data

  This dataset comprises Circle-seq data for 12 neuroblastoma cell lines supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

  Dataset EGAD00001006579

• RCC ATAC-seq data

  ATAC-seq data 72cases

  Dataset EGAD00001009868

• Dataset to study clonal evolution in iAMP21 patient SJBALL030072using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJBALL030072with 66 high quality cells sequenced (61 blast and 5 normal)

  Dataset EGAD00001010288

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A063 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A063 with 80 high quality cells sequenced (75 blast and 5 normal)

  Dataset EGAD00001011328

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A066 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A066 with 69 high quality cells sequenced (62 blast and 7 normal)

  Dataset EGAD00001011329

• Dataset to study clonal evolution in TCF3:PBX1 patient SJE2A067 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJE2A067 with 78 high quality cells sequenced (73 blast and 5 normal)

  Dataset EGAD00001011330

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• Spatial Transcriptomics of Vaccine Therapy With or Without Cyclophosphamide in Treating Patients Undergoing Chemotherapy and Radiation Therapy for Stage I or Stage II Pancreatic Cancer That Can Be Removed by Surgery

  Pancreatic ductal adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. Here, spatial transcriptomics data were generated from 16 pancreatic cancer patients treated with GVAX, whose tumors presented with induced intratumoral TLS. Resected tumor specimens were embedded in OCT media and freshly frozen. Sections were cut into 6.5 x 6.5 mm dimensions compatible with Visium spatial transcriptomics slides. TLS-positive tumor sections from 14 patients (14 tumor samples in total) and lymph nodes from remaining patients (2 lymph node samples in total) were selected by an expert pathologist for profiling. We used 4 Visium slides and covered the 16 capture areas with sections cut in a cryostat at 10 µm. The fresh frozen Visium protocol was followed according to manufacturer's recommendations (10x Genomics Spatial 3' v1). Tissue permeabilization and library construction was carried out according to the manufacturer's protocols. Permeabilization time was optimized to 30 minutes. The captured tissue sections were permeabilized to allow RNA to be captured onto the slide where it reverse-transcribed to cDNA. The cDNA was then amplified, and sequencing libraries were prepared using the 10x Genomics Visium Spatial Gene Expression Reagent Kit for Library Preparation. The libraries were then sequenced using an Illumina NovaSeq sequencer. The raw data obtained from the sequencing were processed using the SpaceRanger (spaceranger-1.2.0) pipeline for alignment onto the GRCh38-2020-A reference transcriptome quantification of gene expression. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation.

  Study phs003862

• Genomic features of Helicobacter pylori-na��ve diffuse-type gastric cancer.

  Helicobacter pylori (HP) is a major etiologic driver of diffuse-type gastric cancer (DGC). However, improvements in hygiene have led to an increase in the prevalence of HP-na��ve DGC; that is, DGC that occurs independent of HP. Although multiple genomic cohort studies for gastric cancer have been conducted, including studies for DGC, distinctive genomic differences between HP-exposed and HP-na��ve DGC remain largely unknown. Here, we employed exome and RNA sequencing with immunohistochemical analyses to perform binary comparisons between 36 HP-exposed and 27 HP-na��ve DGCs from sporadic, early-stage, and intramucosal or submucosal tumor samples. Among the samples, 33 HP-exposed and 17 HP-na��ve samples had been preserved as fresh-frozen samples. HP infection status was determined using stringent criteria. HP-exposed DGCs exhibited an increased single nucleotide variant burden (HP- exposed DGCs; 1.97 [0.48���7.19] and HP-na��ve DGCs; 1.09 [0.38���3.68] per megabase; p=0.0003) and a higher prevalence of chromosome arm-level aneuploidies (p<0.0001). CDH1 was mutated at similar frequencies in both groups, whereas RHOA���ARHGAP pathway misregulation was exclusive to HP-exposed DGCs (p=0.0167). HP-exposed DGCs showed gains in chromosome arms 8p/8q (p<0.0001), 7p (p=0.0035) and 7q (p=0.0354), and losses in 16q (p=0.0167). Immunohistochemical analyses revealed a higher expression of intestinal markers such as CD10 (p<0.0001) and CDX2 (p=0.0002) and a lower expression of the gastric marker, MUC5AC (p=0.0305) among HP-exposed DGCs. HP-na��ve DGCs, on the other hand, had a purely gastric marker phenotype. This work reveals that HP-na��ve and HP-exposed DGCs develop along different molecular pathways, which provide a basis for early detection strategies in high incidence settings.

  Study JGAS000575

• A Multimodal Atlas of Human Brain Cell Types 2021 Data

  Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This dataset consists of transcriptome samples collected during Patch-seq recordings from layer 5 pyramidal neurons in the human middle temporal gyrus.

  Study phs002697

• Osteosarcoma sequencing data

  This study shares DNA and RNA sequencing data from embryonal rhadbomyosarcoma patients

  Study EGAS00001005600

• HipSci - Alport Syndrome - RNA Sequencing - July 2017

  HipSci - Alport Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003532

• HipSci - Battens Disease - RNA Sequencing - July 2017

  HipSci - Battens Disease - RNA Sequencing - July 2017

  Dataset EGAD00001003533

• HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003535

• HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  Dataset EGAD00001003540

• HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  Dataset EGAD00001003541

• HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  Dataset EGAD00001003542

• HipSci - Usher Syndrome - RNA Sequencing - July 2017

  HipSci - Usher Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003543

• RNA sequence of HUB_5 cell culture

  RNA sequence data for conditionally reprogrammed cells from patient HUB_5

  Dataset EGAD00001001923

• Single cell RNA sequencing of cerebrospinal fluid

  Single-cell RNA sequencing of cells isolated from cerebrospinal fluid from 81 individuals with multiple sclerosis (n=33) or other neurological disease (n=48) using 10x Genomics 3’ expression (v2 chemistry).

  Study EGAS00001007478

• RNA sequencing of OM-ALI cultures derived from control and AD individuals exposed to SARS-CoV-2

  RNA sequencing of air-liquid interface (ALI) cultures of olfactory mucosa (OM) cells derived from control (n=3) and AD (n=3) individuals exposed to SARS-CoV-2.

  Study EGAS50000000408

• Nasopharyngeal RNASeq Comparing SARS-CoV-2+ Patients and SARS-CoV-2 Negative Control Subjects

  The goal of this analysis was to compare RNAs enriched in the upper respiratory tract of SARS-CoV-2 patients and SARS-CoV-2 negative controls. RNA-sequencing of RNA isolated from the viral transport medium associated with nasopharyngeal swab samples from SARS-CoV-2+ patients and SARS-COV-2 negative controls.

  Study phs002433

• Genomic characterization of a patient with AGS and CdLS transcriptomic comparison of his monocytes against healthy and disease control samples

  In this study, we describe an extreme genetic phenotype of two simultaneous genetic lesions, leading to broad alterations in immunophenotype and transcriptome. Whole Exome Sequencing and RNA-Sequencing of CD14+ monocytes was performed on the case patient, and RNA-sequencing was also performed on disease (Systemic Lupus Erythematosus) and healthy controls.

  Study EGAS00001007829

• An Organoid Biobank of Rare Human Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping

  We performed whole genome sequencing and RNA-sequencing of neuroendocrine neoplasm. The aim of this study was to provide genetic landscape of neuroendocrine neoplasm, to construct available animal models, and to engineer neuroendocrine neoplasm from normal colon epithelium. The reference genomes used are GRCh37 for whole genome sequencing and GRCh38 for RNA-sequencing.

  Study JGAS000237

• Gene expression in brain (Schizophrenia) study

  The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways.

  Study EGAS00001004199

• Single nucleus and bulk transcriptomics in prefrontal cortex of individuals with alpha synucleinopathies

  We explore cell-specific changes in gene expression across different α-synucleinopathies. We perform single nucleus RNA sequencing using 10X Genomics, and bulk RNA sequencing from the prefrontal cortex of individuals with alpha synucleinopathies - Parkinson's Disese (PD), monogenic LRRK2 PD, and multiple system atrophy (MSA), together with neurologically healthy controls.

  Study EGAS50000000301