7200 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• Ewings_Sarcoma_RNA_seq_drug_sensitivity

  Illumina RNA-Seq will be performed on four Ewing’s sarcoma cell lines and two control cell lines. RNA was extracted from all the lines using a basic Trizol extraction protocol.

  Study EGAS00001000419

• Genentech Small Cell Lung Cancer (SCLC) Screen

  Exome capture, RNA-Seq, whole genome sequencing of set of Small Cell Lung Cancer samples.

  Study EGAS00001000334

• RNA-Seq

  Dac EGAC00001002038

• Single nucleus and in situ RNA sequencing reveals cell topographies in the human pancreas

  Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been established, due to the local concentration of hydrolytic enzymes that can rapidly degrade cells and RNA upon resection. Here we innovated single-nucleus RNA sequencing protocols, and profiled more than 120,000 cells from adult and neonatal human donors to create the first comprehensive atlas of human pancreas cells, including epithelial and non-epithelial constituents. Adult and neonatal pancreata shared common features, including the presence of previously undetected acinar subtypes, but also showed marked differences in the composition of the endocrine, endothelial, and immune compartments. Spatial cartography, including cell proximity mapping through in situ sequencing, revealed dynamic developmental cell topographies in the endocrine and exocrine pancreas. Our human pancreas cell atlas can be interrogated to understand pancreatic cell biology, and provides a crucial reference set for future comparisons with diseased tissue samples to map the cellular foundations of pancreatic diseases.

  Study EGAS00001004653

• A New High-Throughput Sequencing-Based Technology to Study Heterochromatin Structure

  In this study we report epigenomic and transcriptomics datasets for normal control fibroblasts. The following cell lines were obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research: AG08498, AG07095, originally collected as part of the NIA Aging Cell Repository study. We applied a high-throughput sequencing-based technique, named Sequential Analysis of MacroMolecules accessibilitY (SAMMY-seq), for the genome-wide mapping of chromatin regions separated by differential accessibility. The method is based on the sequential extraction of multiple chromatin fractions, corresponding to increasingly compacted and less accessible chromatin regions, which are mapped along the genome using high-throughput sequencing. Additionally we carried out ChIP-seq for the H3K9me3 and H3K27me3 histone modifications and RNA-seq for the characterization of transcriptome in control fibroblasts.

  Study phs002202

• Transcriptome sequencing of gingivo-buccal oral squamous cell carcinoma for integrative analysis: alterations in expression of genes attributable to methylation changes

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out transcriptome (n=72) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India. RNA sequencing was performed on tumor and paired adjacent normal samples from 72 OSCC-GB patients. From each patient, total RNA was extracted from tumor and normal tissue samples using AllPrep DNA/RNA Mini Kit (QIAGEN). The quality and concentration of isolated total RNA were checked using Agilent 2100 Bioanalyzer and NanoDrop 2000 (Thermo Fisher Scientific). The OD260/OD280 ratio was ≥ 2 and RNA Integrity Number (RIN) was ≥ 7.0 for all sequenced samples. Ribosomal RNA (rRNA) was removed from the RNA samples, using Ribo-Zero Magnetic Kit (Epicentre). Sequencing libraries were prepared from rRNA depleted samples using TrueSeq RNA Sample Preparation Kit (Illumina). Each triplex cDNA library pool was sequenced as 100bp paired-end on HiSeq-2000 or HiSeq-2500 (Illumina). Protocols suggested by the manufacturers were used for all assays.

  Study EGAS00001003893

• Transcriptomic response of miRNAs of monocytes to bacterial and viral stimuli assessed by RNA-seq in Africans and Europeans

  Leveraging the miRNA transcriptome of 977 samples, the study aims to define the levels of miRNA and isomiR diversity across individuals and populations, explore the genetic sources of miRNA expression variability and miRNA-environment interactions, evaluate the effects of immune challenges upon miRNA and isomiR expression dynamics, and quantify the relative impact of transcription and miRNA-mediated degradation on gene expression variability.

  Study EGAS00001004192

• atrial appendage RNA-seq in non-, paroxysmal and persistent atrial fibrillation

  64 left atrial appendages from patients without atrial fibrillation (AF) undergoing cardiac surgery, patients with paroxysmal AF and with persistent AF (~20 per group). Trizol RNA isolation, rRNA depletion, paired transcriptome sequencing on illumina NovaSeq 6000. Provided are FastQ and BAM files. Additional data (e.g. clinical characteristics, RIN values etc.) can be provided upon reasonable request. The same RNA samples (62 out of 64) were used for miRNA sequencing. Results from miRNA seuqencing are stored in the EGA database managed by the same DAC.

  Dataset EGAD00001007693

• Computational approach to discriminate human and mouse sequences in patient-derived tumour xenografts

  Whole Exome Sequencing was performed in a dilution series containing known amounts of human and mouse DNA, 3x 100% human 0% mouse, 2x 90/10, 3x 50/50, 2x 25/75 and 3x 0/100. A set of breast cancer clinical samples, matched normal tissue and matched PDTXs (total number = 14) were also analysed. Paired-end 75bp sequences for the dilution series and paired-end 125bp for the clinical samples were obtained on Illumina HiSeq2500; fastq files are provided. A triplicate analysis of the transcriptome using RNA-seq was also performed for the Universal Human RNA Reference and the Universal Mouse RNA Reference samples. Paired-end 150bp fastq files obtained on Illumina HiSeq4000 are provided.

  Dataset EGAD00001003800

• RNA-Seq of Whole Blood from Patients with Intracranial Aneurysms

  Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size. However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imaging on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. We hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. We propose to use whole blood transcriptomes to develop a "one-stop" diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to develop and validate biomarkers to predict risk, as calculated by the currently-used metric of aneurysm size, the clinical PHASES score, and the RRS. Here, we collected blood samples from consented individuals who were receiving cerebral imaging at the Gates Vascular Institute (Buffalo, NY) for intracranial aneurysm. RNA extracted from blood samples (n=43) was subjected to RNA-sequencing and added to our existing database (n=44). When combined with our previous data, we had transcriptome data from 68 aneurysms (after additional sample filtering). This dataset was stratified into low- and high-risk according to IA size, PHASES score, and RRS score. Differentially expressed genes were identified and used to construct predictive models. Fastq files and basic demographic information for the 43 newly-sequenced intracranial aneurysm samples on this project will be available through dbGaP.

  Study phs003072