15120 results for "cancer studies using rna-seq"

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• High-throughput determination of the antigen specificities of T cell receptors in single cells

  High-throughput linking of T cell receptor (TCR) sequences to their binding antigens is vital for immune profiling, yet challenging. We present Tetramer associated TCR Sequencing (TetTCR-Seq) to address this challenge. Binding is determined using a library of DNA-barcoded antigen tetramers that are rapidly and inexpensively generated using an in vitro transcription/translation platform. We included CMV+ donors (CMV seropositive donors who are infected with Cytomegalovirus) to screen for CMV specific TCRs.

  Study phs001678

• WTCCC case-control study for Breast cancer

  WTCCC genome-wide case-control association study for Breast cancer (BC) using the 1958 British Birth Cohort collection as controls.

  Study EGAS00000000024

• ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells-of-origin

  Cell-free DNA in human plasma provides access to molecular information about the pathological processes in the organs or tumors from which it originates. These DNA fragments are derived from fragmented chromatin in dying cells, and retain some of the cell of origin histone modifications. Here, we apply chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) to 268 human samples. In healthy donors, we identified bone marrow megakaryocytes, but not erythroblasts, as major contributors to the cfDNA pool. In patients with a range of liver diseases, we show that we can identify pathology-related changes in hepatocyte transcriptional programs. In metastatic colorectal carcinoma patients, we detected clinically relevant, and patient-specific information, including transcriptionally active HER2 amplifications. Altogether, cfChIP-seq using low sequencing depth, provides systemic and genome-wide information, can inform diagnosis, and facilitate interrogation of physiological and pathological processes using blood samples.

  Study EGAS00001004913

• Somatic Mutations in Single Human Neurons from Patients with Congenital Neurodegenerative Diseases

  It has been hypothesized that accumulating DNA lesions in neurons contribute to aging and neurodegeneration. Despite their pathophysiological importance, the DNA lesions have not been systematically examined with effective methods. In this study, we developed a computational method for detecting genomic deletions in single-cell whole-genome sequencing (scWGS) data, and analyzed the whole genome of human single neurons. Single neurons were obtained from neurotypical individuals of various ages and from patients with three different congenital neurodegenerative diseases: Ataxia telangiectasia (AT), Cockayne syndrome (CS), and Xeroderma pigmentosum (XP). Single-neuron WGS data of AT brains are released here, and the data of other two diseases are released in a separate dbGaP study (phs001485).To understand the molecular mechanisms underlying AT, we performed single-nucleus RNA-sequencing (snRNA-seq) of postmortem cerebellar vermis and prefrontal cortex from individuals with AT and controls. To genetically confirm the diagnosis of AT, we also performed WGS on postmortem brain tissue from each individual with AT. Induced pluripotent stem cells (iPSCs) from individuals with AT and controls were differentiated into microglia, and the transcriptomes were profiled with bulk RNA-sequencing (RNA-seq).

  Study phs003005

• snRNA-seq/snATAC-seq multiome of first and second trimester human gonads - HUGODECA dataset

  Comprehensive map of first- and second-trimester gonadal development in humans using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays, and imaging. ArrayExpress Accession: E-MTAB-11708

  Dataset EGAD00001009388

• RNA-seq, WGS and WES of Hepatocellular carcinomas, enriched in fibrolamellar carcinomas

  Dataset EGAD00001005308

• RNA-seq of human embryonic heart, lung, and cerebellum

  Characterization of cell types in the human embronic heart, lung, and cerebellum.

  Study EGAS00001004375

• Myeloma XI trial data

  The dataset contains WGS and RNA-seq from Myeloma XI trial

  Dataset EGAD00001005491

• bulkRNA

  Bulk RNA-seq for cALL patient-derived PDX samples

  Dataset EGAD00001006133

• RNAseq data

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes raw FASTQ files.

  Dataset EGAD00001011168

• Gene expression of transduced human primary germinal centre B-cells

  RNA-seq sequencing data of human germinal centre B-cells (42 samples)

  Dataset EGAD00001005281

• Berlin Neuroblastoma Dataset

  Paired tumor/normal WGS and RNA-seq of primary neuroblastoma.

  Dataset EGAD00001005488

• Identifying aberrant splicing isoforms and potential neoantigens in non-small cell lung cancer

  To identify aberrant splicing isoforms and potential neoantigens, we performed full-length cDNA sequencing of seven non-small cell lung cancer specimens using a long-read sequencer MinION. We detected aberrant splicing isoforms using our bioinformatics pipeline and constructed a comprehensive catalogue.

  Study JGAS000245

• Multivalent State Transitions Shape the Intratumoral Composition of Small Cell Lung Carcinoma

  Small cell lung carcinoma (SCLC) is an aggressive, tobacco-associated tumor characterized by rapid growth, early metastases, and initial response followed by almost invariable resistance to chemotherapy. Studies to date have not resolved the extent that diverse transcriptional programs drive SCLC and contribute to its lethality. We combined patient-derived xenograft (PDX) (n = 64) resources with multi-omic profiling, single-cell fluorescence tracking of ex vivo tumor cells, and mathematical and statistical models to study the topology of the SCLC transcriptional state space and its plasticity.

  Study phs003102

• Single cell RNA sequencing of bone marrow mononuclear cells

  Bone marrow aspirates were obtained from patients with relapsed/refractory large B cell lymphoma (rrLBCL), mononuclear cells isolated by ficoll density-gradient centrifugation, and loaded onto a 10X Chromium for single cell RNA-sequencing using 5’ chemistry without prior cryopreservation. Healthy donor bone marrow mononuclear cells were obtained from healthy allogeneic stem cell transplant donors and analyzed following viable cryopreservation.

  Study EGAS00001006836

• CD4+ T cell subsets stratified by complement receptor type 2 (CR2) expression

  FACS-sorted CR2+ and CR2- naive and memory CD4+ T cells from healthy donors, plus CR2+ naive CD4+ T cells activated using CD3/CD28 beads, were analyzed ex-vivo. Exome-enriched RNA sequencing was carried out for all subsets.

  Study EGAS00001001870

• Cell type-specific transcriptomics of esophageal adenocarcinoma as a scalable alternative for single cell transcriptomics

  We developed a protocol for the separation of esophageal carcinoma tissue into leukocytes (using CD45 as a marker), epithelial cells (EpCAM), and fibroblasts (two out of PDGFRA, CD90, anti-fibroblast) by fluorescence-activated cell sorting followed by RNA-sequencing

  Study EGAS00001004053

• Fusion gene analysis using multiplex single primer extension-based RNA-sequencing

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains fusion gene analysis using multiplex single primer extension-based RNA-sequencing for a subset of 25 patients of the screening cohort. Data was generated on Illumina NexSeq 550 device in paired-end mode and is stored in compressed FASTQ file format.

  Dataset EGAD00001011326

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833