7190 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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• lymphoma plasma cfRNA

  Dataset contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma (DLBCL) and 13 primary mediastinal large B-cell lymphoma (PMBCL) patients, and 22 cancer-free controls. Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001010259

• Validated Single-cell RNA sequencing in early breast cancer

  Single-cell RNA and VDJ sequencing of early breast cancer

  Dataset EGAD00001006608

• Single-cell RNA sequencing on 5063 single T cells from six hepatocellular carcinoma patients

  T cells isolated from peripheral blood, tumors and adjacent normal tissues from six hepatocellular carcinoma patients. SmartSeq2 and Tang2009 protocol were used to amplify RNA from single T cells. High depth enables simultaneously expression profiling and TCR assembling.

  Dataset EGAD00001003337

• DCM-controls

  DCM-controls (113 human non-DCM samples) human heart biopsies from 113 non-diseased controls were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

  Dataset EGAD00001003391

• DCM-cases

  DCM-cases (149 human DCM samples) human heart biopsies from 149 patients with dilated cardiomyopathy (DCM) were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

  Dataset EGAD00001003390

• Bulk-tissue paired-end RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Profiling of 24 human anterior cingulate cortex samples by bulk-tissue RNA-sequencing. Samples were derived from 5 non-neurological control individuals and 19 individuals with Lewy body disease (Parkinson’s disease = 7 individuals; Parkinson’s disease with dementia = 6 individuals; dementia with Lewy bodies = 6 individuals). Paired-end FASTQ files for each of the human samples are provided and are denoted by the suffixes R1 (read 1) and R3 (read 2). Fastp (v 0.20.0), a fast all-in-one FASTQ pre-processor, was used for adapter trimming, read filtering and base correction. Fastp default settings were used for quality filtering and base correction. Further details on parameters used are available here: https://github.com/RHReynolds/RNAseqProcessing/blob/master/QC/prealignmentQC_fastp_PEadapters.R.

  Dataset EGAD00001007698

• RNA-sequencing of primary urothelial bladder cancer samples

  Paired-end RNA-sequencing of tumour tissue samples (n=85) from primary urothelial bladder cancer patients. Sequencing was performed using either HiSeq (n=27) or NextSeq (n=58) Illumina platforms. Of the 85 samples, 78 are Non-muscle invasive (NMIBC) and 7 are Muscle invasive (MIBC).

  Dataset EGAD00001007005

• Single-cell RNA sequencing of SarBC-01 treated with Dexamethasone vs DMSO, with or without Matrigel.

  This dataset contains raw FASTQ files from single cell RNA sequencing of SarBC-01 cells treated with Dexamethasone vs DMSO, with or without Matrigel, processed with MULTI-seq. Cells from 4 different culture conditions (+Mat/Dex, +Mat/DMSO, -Mat/Dex, -Mat/DMSO) were harvested, processed for multiplexing using the MULTI-seq protocol and loaded in a Chromium Single Cell 3ʹ GEM Library and Gel Bead Kit v3 (10x Genomics). Gene expression (cDNA) and MULTI-seq libraries were prepared according to the manufacturers’ protocol of Chromium Next GEM Single Cell 3’ reagents Kits v3.1 (Dual Index). Finally, cDNA and MULTI-seq libraries were analyzed using an Agilent Bioanalyzer (DNA High Sensitivity kit) and sequenced on a NovaSeq6000 (S2 flow cell) platform. MULTISEQ BARCODES: TTAGCCAG => Matrigel/DMSO CCACAATG => Matrigel/Dexamethasone GCACACGC => noMatrigel/DMSO AGAGAGAG => noMatrigel/Dexamethasone

  Dataset EGAD00001011155

• Single-cell RNA sequencing data of peripheral blood mononuclear cells obtained from 30 ATL patients, 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Single-cell RNA sequencing (scRNA-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 30 ATL patients (34 samples including 4 sequential ones), 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Dataset EGAD00001007015

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• Gene Expression Signatures Characterized by Longitudinal Stability and Inter-Individual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation

  RNA sequencing (RNAseq) of peripheral blood lymphocytes was used to develop a means to assess immune function in a way that can be used in discovery science and applied to patients individually in clinical settings. The premise is that profiles of RNA present in immune cells is reflective of the combined influence of genetic and environmental variation on immune potential of individuals and that this potential can be tapped to understand human immunity in a variety of biological contexts. CD4+ cells were isolated from fresh whole blood via positive magnetic bead selection and cell lysates were prepared using Qiazol (QIAGEN) and stored at -80ºC for 3 to 8 months. RNA was extracted in batches for cDNA library preparation and RNA-Seq. For this study, we developed standard operating procedures for handling human blood samples and determined: a) the best way to enrich for CD4+ T cells from whole blood and yield high quality RNA, b) the sensitivity of this RNA profiling strategy, and c) the reproducibility of generated immune profiles from healthy subjects. We then developed bioinformatics processes to establish immune response signatures and immune response phenotypes within cohorts of individuals.

  Study phs001512

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program –Sarcoma, Kidney, and Liver Cancers

  The goal was to complete whole exome sequencing (WES) and RNA sequencing (RNA-Seq) on patient derived xenograft samples. Cancer in children is rare with approximately 15,700 new cases diagnosed annually in children 21 years or younger in the U.S. Through use of multimodality therapy (surgery, radiation therapy, and aggressive chemotherapy), 70% of patients will be 'cured' of their disease, and 5-year Event-Free Survival (EFS) exceeds 80%. Consequently, the number of patients that can be enrolled in phase I/II clinical trials is small, and most patients will have been extensively treated, hence drug/radiation resistant. Thus, preclinical studies that accurately translate into effective clinical therapy are an essential component of pediatric drug development. Our group has contributed to studies in the Pediatric Preclinical Testing Program (PPTP) and Pediatric Preclinical Testing Consortium (PPTC) that have led to clinical studies through Children's Oncology Group (COG). Of importance, we have developed and characterized over 330 Patient Derived Xenografts (PDX), developed from tumors both at diagnosis and relapse, that can be used to facilitate pediatric drug development as directed by FDA under the Research to Accelerate Cures and Equity for Children Act (RACE for Children Act).

  Study phs003160

• Single-Cell Genomic and Transcriptomic Analysis of the Aging Human Brain

  We studied human brain aging using single-cell whole genome sequencing and single-nucleus RNA sequencing of the pre-frontal cortex from 19 donors ranging in age from 0.4 years to 104 years. All donors were free of neuropathology and none received a clinical neurological diagnosis prior to death. snRNA-seq libraries were prepared in batches that always included old and young donors to mitigate batch effects in the preparations. Neurons for single-cell WGS were collected from the same tissue region as the snRNA-seq for each donor but represent independent cells. Multiplexed error-robust fluorescent in-situ hybridization (MERFISH) data was also collected from pre-frontal cortex samples of a subset of the 19 donors. Transcriptomic results identified infant-specific cell clusters, and common-down regulation of cell-essential genes involved in ribosomes, transport, homeostasis and metabolism during aging, across all cell types. scWGS identified two-age associated mutational signatures, as well as gene-length and expression-level dependent somatic mutation rates in neurons. Raw sequencing data in fastq format for single-nucleus RNA-seq and single-cell DNA-seq, as well as cell and gene count matrix, transcript metadata, and cell metadata for MERFISH will be available in dbGaP.

  Study phs003445

• Genomic and Genetic Analysis of Brain Tumors and Analysis of Their Clinicopathological Significance

  The treatment outcome of glioma patients remains disappointing, and more studies are needed to improve therapeutic strategies. In particular, it is crucial to understand the mechanisms underlying resistance to treatment and malignant transformation, as well as the intratumoral heterogeneity and interaction of tumor cells and host immunity. Recent advances in omics analysis techniques, such as next-generation sequencing (NGS), have enabled us to obtain omics data more easily and accelerated our ability to integrate this information and precisely characterize cases. In our project, we have already collected more than 100 pairs of human glioma/normal tissue samples, of which some are multiple specimens collected from initial and recurrent tumors, and some include multiple specimens collected from different regions within a single tumor. We used our in-house algorithms, composed of alignment and variant calling programs, to analyze omics data from multiple platforms, such as whole-exome sequencing (WES), RNA sequencing (RNA-seq), and methylation array, with our original cohort of glioma patients. Using several informatics tools, the information about genetic and epigenetic status and expression signatures were analyzed. Those data are expected to provide key information for investigating the mechanisms discussed above. Through this project, we hope to improve strategies for personalized therapy based on comprehensive omics data.

  Study JGAS000004

• Integrated genomic analysis for HCC

  Liver cancer is a common malignancy and is the third cause of cancer-related death in the world and hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for ~90% of cases. Only 20 ~ 30% of patients can benefit from combined immunotherapy and targeted therapy due to the high inter-tumor heterogeneity of HCC. This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) and/or RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the great consistence between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. And we further characterized HCC subtypes using genomic, transcriptomic and clinicopathological features. Among 9 subtypes, 5 subtypes belonged to chromosome instable tumors, while 3 subtypes belonged to chromosome stable tumors. In addition, our subtypes were associated with prognosis and we also found different distributions of subtypes across various features, such as etiology and gender. Our study provided a robust molecular classification based on a large HCC dataset from Western country, it improves our understanding of the mechanisms of carcinogenesis and will facilitate development of genome-based precision medicine in HCC.

  Study EGAS00001007957

• H3K27ac/H3K27me3 landscape of medulloblastoma

  We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

  Dataset EGAD00001009709

• Molecular Signatures of DCIS to Invasive Progression for Basal-Like Breast Cancers: An Integrated Mouse Model and Human Tumor Study

  We studied the genomic signatures of progression in breast ductal carcinoma in situ (DCIS) as it progresses towards triple negative invasive breast cancer (TNBC). Single cell RNA sequencing (scRNAseq) was performed on the C3Tag genetically engineered mouse model that forms human breast-like DCIS and TNBC. Bulk RNA sequencing was performed on RNA harvested from archival formalin-fixed, paraffin embedded (FFPE) pairs comprising of estrogen receptor (ER) positive (ER+) and negative (ER-) subsets of DCIS. 

  Study phs002443

• DNA and RNA Profiling Using Simultaneous Sequencing (Simul-seq)

  Paired DNA and RNA profiling is increasingly employed in genomics research to uncover molecular mechanisms of disease and to explore personal genotype and phenotype correlations. We developed a novel simultaneous DNA and RNA sequencing approach (Simul-seq) that enables comprehensive genomic and transcriptomic profiles from small quantities of cells or tissues. In this study, Simul-seq was performed on patient-derived fibroblast cells as well as an esophageal adenocarcinoma tumor sample and compared with standard DNA and RNA-sequencing approaches.

  Study phs001214

• Genetic Effects on miRNA Expression During Mid-Gestation Neocortical Development

  In this study we aimed to find common genetic variants that influence miRNA expression during mid-gestation neocortical development. Small RNA-sequencing from 212 fetal cortical tissue samples between 14 and 21 weeks gestation were used to profile miRNA expression. Combined with donor genotypes, we were able to find miRNA-eQTLs during neocortical development. The dataset provided here includes 212 Small RNA-sequencing files in FASTQ format from cortical wall samples. Also provided here are 212 donor genotypes in PLINK format (hg19).

  Study phs003106

• Idiosyncratic and generic single nuclei and spatial transcriptional patterns in papillary and anaplastic thyroid cancers

  Thyroid cancer is the most common endocrine malignancy. This dataset encompasses two types of thyroid cancer : anaplastic which is the most de-differentiated and aggressive one, and papillary which is the most common one. We profiled 14 patients, including 10 papillary and 4 anaplastic thyroid carcinomas, using both single nuclei RNA sequencing and spatial transcriptomics to link single cell resolution RNA sequencing with tissue morphology and better understand inter and intratumoral thyroid cancer heterogeneity.

  Study EGAS00001007574

• RNA-SEQ data from 47 CAF (Cancer Associated Fibroblast) samples sorted from fresh breast cancer

  Dataset EGAD00001003808

• SF4324 Primary Wildtype GBM Female, 57.

  Single Cell RNA-Seq of Primary GBM. Gender Female, Age, 57.

  Dataset EGAD00001006017

• Blood RNA-seq from Mexican DMD patients and healthy controls

  These data are part of a study that aimed to assess the potential of blood RNA-seq to track non-invasively disease progression for DMD. In particular, here we focus on a study designed to compare gene expression in blood from DMD patients to that of healthy controls. These data are analysed in the following manuscript: Signorelli, M., Ebrahimpoor, M. et al. (accepted). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients. To appear in EMBO Molecular Medicine.

  Study EGAS00001004907

• Melanoma Brain Metastasis Single-Cell RNA Sequencing Atlas

  Melanoma brain metastasis (MBM) frequently occurs in patients with advanced melanoma, yet our understanding of the underlying salient biology is rudimentary. Here, we performed single-cell/nucleus RNA-seq in 22 treatment-naive MBM (scRNA-seq n=5; snRNA-seq n=17) and 10 extracranial melanoma metastases (ECM; all snRNA-seq), and matched spatial single-cell transcriptomics (n=16) and T cell receptor (TCR)-seq (n=5). Key observations were validated in matched bulk RNA- and ATAC-seq of isogenic MBM/ECM cell culture models (n=24; including triplicates (labeled as *-A, -B and -C) of 4 MBM- and 4 ECM-derived patient cell lines with 2 matched pairs). This work provides comprehensive insights into MBM biology and serves as a foundational resource for further discovery and therapeutic exploration.

  Study phs002944

• Whole Transcriptome Sequencing Data of prDLBCL

  We used sequenced 30 prDLBCL samples using RNA-seq to evaluate possible fusion events and to get expression profiles.

  Dataset EGAD50000000592