3928 results for "RNA AND sequencing OR transcriptome"

in 12.33 milliseconds.

• Triple-negative breast cancer sequencing data

  Single-cell RNA sequencing and spatial transcriptomic sequencing data associated with manuscript 'Ectopic NMDAR expression in cancer unmasks germline-encoded autoimmunity'

  Dataset EGAD50000002266

• miRNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  micro RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 6), critical COVID-19 (n = 13) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001406

• Genomic Landscape of Radiation Induced Meningiomas

  EGAS00001002317 - Whole exome sequencing of data of 18 RIMs with matched bloods. Median depth of 112x (range of 110-120). Performed on Illumina HiSeq Platform. EGAS00001002318 - RNA sequencing data of 18 RIMs on the Illumina HiSeq Platform.

  Dataset EGAD00001004358

• WES, ultra-deep sequencing exome and RNAseq data of diseased liver samples

  1. Utra-deep exome sequencing data, illumina pair-end reads, fastq, 190 samples 2. WES data, illumina pair-end reads, fastq, 120 samples 3. RNA-seq data, illumina, pair-end reads, fastq, 20 samples

  Dataset EGAD00001004792

• WES, sWGS and RNA-seq of Asian breast cancer

  The dataset contains a full genomics characterization of 527 Asian breast tumours. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, shallow-whole genome sequencing at 0.1X for copy number analyses, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a HiSEQ4000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a HiSEQ4000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001006399

• Single-cell RNA-seq from tumor-on-chip (TOC)

  8 Fastq files of single-cell RNAseq data from tumor-on-chip (TOC) after 42h of TNBC and CAF mono- or co-culture

  Dataset EGAD50000001296

• Longitudinal 3'RNA-Seq data from MEMORI trial

  80 bam files generated from 3'RNAseq of tumour biopsies from oesophageal adenocarcinoma. Samples were collected within the clinical MEMORI trial.

  Dataset EGAD50000000357

• Human Epidermis scRNA

  Single cell RNA-seq analysis of human skin.

  Dataset EGAD00001004367

• RCC transcriptomic data

  RNA-seq data. 287 Japanese RCC cases.

  Dataset EGAD00001010003

• PDX RNA

  RNAseq from PDX tumours under treatment with dpbs or eribulin. Sarcomatous or mixed sarcoma/carcinoma. 6 PDX tumours each with 2 treatments gave 12 pairs of fastq files.

  Dataset EGAD00001009658

• Whole Transcriptome Sequencing of NXF1 or CRM1 depleted Cell

  mRNA exporters, NXF1 and CRM1 are known to function in mRNA export. However, since each target mRNA has not been identified genome-widely, it is not clear whether they export exclusive mRNA subsets. To reveal this point, we prepared the nuclear and the cytoplasmic RNAs under either exporter inhibited condition and carried out RNA-seq. In these experiments, we also focused in the export machinery of aberrant transcripts that usually retained and decayed in the nucleus.

  Study JGAS000294

• Raw sequencing data from chromosome conformation capture, RNA sequencing and chromatin assays in human primary monocytes

  This dataset contains raw sequencing data from eQTL Capture Hi-C, ATAC-seq and RNA-seq experiments in monocytes isolated from 34 healthy male donors, as well as from Hi-C, 4C-seq and CTCF ChIP-seq in subsets of individuals. The data are released as paired-end Illumina FASTQ files. Hi-C and Capture Hi-C used DpnII digestion and Tn5-based low-input library preparation. In Capture Hi-C, this was followed by targeted capture with custom-designed biotinylated RNA probes targeting ~1100 eQTL regions. ATAC-seq was performed on PFA-fixed cells using a digitonin-based protocol. 4C-seq and CTCF ChIP-seq were performed using standard protocols.

  Dataset EGAD50000001116

• Single-cell RNA and TCR sequencing of CSF cells and PBMCs from individuals with neurological disorders

  We performed single-cell RNA sequencing combined with T-cell receptor sequencing to characterize immune cells from cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) of patients with multiple sclerosis and individuals with other inflammatory neurological diseases used as controls. The aim of this study was to identify and characterize T cells with TCRs shared among people with MS and enriched in the CSF compartment.

  Study EGAS50000001897

• Comparison between b2m KO and US2 expressing iPSC lines

  This dataset contains bulk RNA-seq transcriptomic profiles from a human induced pluripotent stem cell (hiPSC) line and three engineered derivatives: B2M knockout, EGFP overexpression, and US2 overexpression, alongside the parental line. Total RNA integrity was assessed using the Experion RNA StdSens 1K Analysis Kit on the Bio-Rad Experion Automated Electrophoresis System prior to library preparation and sequencing. Libraries were sequenced on an Illumina NovaSeq 6000 generating ~20 million reads per sample. Raw read quality was assessed with FastQC, reads were aligned to the human reference genome hg38 (Ensembl release 109) using STAR, and alignment/library QC metrics (e.g., orientation, composition, coverage) were evaluated with Picard.

  Dataset EGAD50000002321

• Paired RNA-Seq data of Primary lymphomas of the central nervous system (PCNSL)

  Primary lymphomas of the central nervous system (PCNSL) are diffuse large B-cell lymphomas (DLBCLs) which are confined to the central nervous system (CNS). Paired RNA-Seq sequencing was done on Illumina HiSeq2000 machines using Illumina TruSeq RNA library preparation kit. About 36 tumor samples were sequenced.

  Dataset EGAD00001007811

• RNA-seq analysis refines molecular subtypes of hepatocellular carcinoma

  This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the consistency between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. We further characterized HCC subtypes using transcriptomic and clinicopathological features. Our study provided a robust molecular classification based on a large HCC dataset from a Western country, improving our understanding of the mechanisms of carcinogenesis and facilitating the development of genome-based precision medicine in HCC.

  Dataset EGAD00001015427

• RNA and ChIP Sequencing datasets from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma

  This dataset contains the RNA and ChIP Sequencing data from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma. The data is organized in 7 experiments which are divided by both sequencing technology or the application of siRNA or drug interventions (or lack thereof) on neuroblastoma cell lines. The experiment names and the file names have been chosen in each respective experiment to guide future users of the data to replicate the analyses in the manuscript.

  Dataset EGAD00001006964

• Concatenated long-read single-cell RNA sequencing of momentum biopsies of ovarian cancer patients

  Concatenated long-read single-cell RNA sequencing samples prepared using 10X and the HIT-scIsoSeq protocol. The sequencing was performed on Sequel II Pacbio machine. 3 ovarian cancer patients, 5 omentum biopsies samples: 3 metastasis samples (one per patient), 2 healthy samples (one per patient except Patient2). 4 bam files per metastasis sample, 2 bam files per healthy sample.

  Dataset EGAD00001009814

• Paired RNA-Seq of fCAB treated and bisulfite treated VDH01, partly depleted for NSUN3

  Paired RNA-seq of bisulfite treated VDH01 samples control or depleted for NSUN3 (4 replicates each). The samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of fCAB treated vdh01 samples control or depleted for NSUN3(4 replicates each). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of fCAB treated VDH01 samples (3). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of bisulfite treated VDH01 samples (3). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq.

  Dataset EGAD00001008742

• MATISSE bulk RNA-sequencing data

  Tumor availability: Bulk RNA sequencing was performed on tumor biopsies of 48 patients at baseline and 45 patients across time points (baseline n=48, week 1 n=38, week 2 n=34, week 4 n=37), including lymph node metastasis that were sequenced in addition to the primary tumor. Tumor RNA was extracted from formalin-fixed paraffin-embedded (FFPE) primary tumor and lymph node metastasis sections containing at least 10% viable tumor cells present in the sample, except for on-treatment samples with a complete pathological response in which we isolated samples with at least 10% immune-infiltration with no viable tumor cells. A pathologist (LS) scored the tumor percentage and indicated the most tumor-dense region on a hematoxylin and eosin (H&E) stain slide for subsequent RNA isolation. According to the manufacturer's protocol, five to 10 FFPE slides (10 µm) were used for RNA isolation using the AllPrep DNA/RNA FFPE isolation kit (Qiagen, 80234) and the QIAcube. Genetic Diagnostics and Sequencing Services (CeGaT) performed RNA sequencing in Germany. Data processing: Demultiplexing of the sequencing reads was performed with Illumina bcl2fastq (v2.20). Adapters of the reads (Pico v2 SMART adapter, first three nucleotides of the second sequencing read) were trimmed with Skewer (v0.2.2), without quality trimming. RNA-sequencing data was aligned to GRCh38 (Ensembl v109) using STAR (v2.7.9) in 2-pass mode with default settings. Gene counts were generated with the HTSeq (v2.0.2). FastQC (v0.12.1) and MultiQC (v1.14) were used for assessing data quality, on FASTQ files and intermediate processing steps.

  Dataset EGAD50000001470

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• Clinical Cancer Genomic Profiling by Three-Platform Sequencing of Whole Genome, Whole Exome and Transcriptome

  To evaluate the potential of an integrated clinical test to detect diverse classes of somatic and germline mutations relevant to pediatric oncology, we performed three-platform whole-genome (WGS), whole exome (WES) and transcriptome (RNA-Seq) sequencing of tumors and normal tissue from 78 pediatric cancer patients in a CLIA-certified, CAP-accredited laboratory. Our analysis pipeline achieves high accuracy by cross-validating variants between sequencing types, thereby removing the need for confirmatory testing, and facilitates comprehensive reporting in a clinically-relevant timeframe. Three-platform sequencing has a positive predictive value of 97-99%, 99% and 91% for somatic SNVs, indels and structural variations, respectively, based on independent experimental verification of 15,225 variants. We report 240 pathogenic variants across all cases, including 84 of 86 known from previous diagnostic testing (98% sensitivity). Combined WES and RNA-Seq, the current standard for precision oncology, achieved only 78% sensitivity. These results emphasize the critical need for incorporating WGS in pediatric oncology testing.

  Study EGAS00001002217

• The cellular state space of AML unveils novel NPM1 subtypes with distinct clinical outcomes and immune evasion properties

  Acute myeloid leukemia (AML) is a genetically and cellularly heterogeneous disease. We characterized 120 AMLs using bulk genomic and transcriptomic analyses (WES, MP-WGS, RNA-seq), and single-cell RNA sequencing (scRNA-seq). Our results reveal an extensive cellular heterogeneity that distorts the bulk transcriptomic profiles. Notably, NPM1 mutated AML could be stratified into two novel, clinically relevant classes (NPM1class I and NPM1class II).

  Study EGAS50000001084

• Dataset for acute myeloid leukemia samples

  This dataset contains RNA, ATAC and WGS sequencing data of 9 acute myeloid leukemia samples. Sequencing was performed on Illumina HiSeq 2000, HiSeq 4000, NovaSeq 6000 and HiSeq X Ten. The sequencing was always paired.

  Dataset EGAD50000000175

• EPITREAT pilot cohort

  Benchmark data set containing five tumor/normal pairs of non-small cell lung cancer (NSCLC) patients. Tissue pairs were screened with bisulfite (BS) sequencing, MeDIP methylation enrichment sequencing and RNA sequencing in order to identify differentially methylated and expressed spots in the genomes.

  Dataset EGAD00001003116