9337 results for "cancer rna-seq"

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• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX055_VOA11924A_37C

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005170

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX056_VOA11924F_37C

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005171

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX054_SA604X9XB02417_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005172

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX054_SA604X9XB02417_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005173

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX057_SA535X5XB02887_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005174

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX057_SA535X5XB02887_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005175

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005176

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005177

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005178

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX067_VOA12024_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005179

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX067_VOA12024_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005180

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in late severe COVID-19

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of late severe COVID-19. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001008161

• Whole exome and RNA sequencing data from the OXIRI phase 1b clinical trial in Asian pancreatic ductal adenocarcinoma (PDAC) patients

  This dataset contains 8 samples, each of which has paired-end WXS fastq files for Tumour and Normal samples, as well as RNA-Seq fastq file.

  Dataset EGAD00001008632

• Transcriptome: chondrosarcoma

  Transcriptome sequencing of nine patients diagnosed with chondrosarcoma. cDNA was generated using the NuGEN Ovation RNA-Seq FFPE system. Total RNA was randomly primed and thermally sheared and the resulting cDNA fragment was amplified. The cDNA was then mechanically sheared using sonication to generate ~250 bp fragments. Sequencing libraries were generated using the NuGEN Ovation Ultralow System V2 library prep kit and sequenced on HiSeq2500 TruSeq v3.

  Dataset EGAD00001008699

• Whole-genome and transcriptome sequencing files obtained in monozygotic twins discordant for Mayer-Rokitansky-Küster-Hauser syndrome

  Raw, unfiltered, paired-end fastq files obtained through whole-genome and RNA-sequencing, respectively. RNA-seq of affected individuals in three twin pairs. WGS of blood in five twin pairs as well as uterine rudiment tissue of selected affected individuals.

  Dataset EGAD00001008992

• RNA-Seq of GM adipose tissue samples

  This dataset contains 210 fastq files (RNA sequencing was performed in two centers) from 105 individuals (106 files in subcutaneous tissue and 104 files in visceral tissue). Of the 210 fastq files, 129 files are in PEx100 mode (appeared in a single fastq file) and 81 files are in PEx49bp mode (appeared in two separate fastq files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010253

• RNA-seq of PBX1 knock-down or overexpressing cell lines

  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 44 samples derived from RNA-sequencing data of bile duct and CCA cell lines. Data was generated on Illumina NovaSeq 6000 device in paired-end mode and is stored in compressed FASTQ file format.

  Dataset EGAD00001011325

• Oxidative phosphorylation is a key ontogenetic feature of monocyte immunometabolism promoting myeloid differentiation after birth

  The dataset consists of 12 samples of monocytes, which were analyzed using RNA-sequencing (RNA-seq). These samples were categorized into four distinct groups, each comprising three samples. The dataset was designed to investigate the transcriptomic and metabolic profiles of monocytes across different age groups and stimulation conditions. 3 neonatal controls, 3 neonatal LPS stimulated, 3 adult controls and 3 adult LPS stimulated samples.

  Dataset EGAD00001011340

• Childhood Cancer Model Atlas

  we establish a single-site collection of 243 cell lines, including 207 paediatric cancer cell lines representing 14 distinct extracranial and brain childhood tumour types. We subjected 164 paediatric cancer cell lines to multi-omic analyses across three dimensions (DNA-sequencing, RNA-sequencing, DNA methylation) to classify them based on clinically relevant molecular subtypes.

  Study EGAS00001006320

• G&T-seq: parallel sequencing of the genomes and transcriptomes of single cells

  The ability to simultaneously sequence the genome and transcriptome of the same single cell offersa powerful means to dissect functional genetic heterogeneity at the cellular level. Here we describeG&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from singlecells. By applying G&T-seq to over 220 single cells we reveal cellular properties that cannot beinferred from DNA or RNA sequencing alone, including associations between DNA copy numbervariation and gene expression dosage. We further demonstrate the detection of coding interchromosomalfusions and single nucleotide variants in both the genomes and transcriptomes ofindividual cells. G&T-seq enables the study of genotype-phenotype associations in single cells, andthe investigation of DNA cell lineage trees of healthy and diseased tissues with transcriptome inferredcell types and states.

  Study EGAS00001001204

• RNA sequencing of follicular T cell lymphoma

  Study EGAS00001004646

• Genomic Studies of Bipolar Disorder in a Large Cohort from The Netherlands

  The transcriptomes of whole blood samples of a large cohort of individuals from the Netherlands were assayed using RNA-seq. These whole blood samples included patients diagnosed with schizophrenia or bipolar disorder, family members of patients, and healthy controls. Within the whole blood dataset, about 600 of the samples were sequenced to an average of 13.9 million mapped reads per sample, while about 2,000 were sequenced to an average of 5.9 million mapped reads per sample, in order to assess changes in power to detect eQTLs based on sample size. We find that expression, defined as the log transcripts per million reads (TPMs), is highly correlated when comparing the moderate (13.9M) and lower (5.9M) coverage datasets. Additionally, a subset of about 150 individuals provided fibroblast cell lines which were assessed for the levels of gene expression using RNA-seq at an average of 50 million mapped reads per sample. We use downsampling techniques to generate synthetic datasets derived from this real fibroblast RNA-Seq data to explore the relationship between coverage and number individuals in an eQTL analysis. Corresponding individual-level genotypes for the samples included in the expression matrix are also made available. The genotypes were derived from multiple other project cohorts, each using different genotyping platforms including OmniExpress Exome, Global Screening Array, Illumina550, and PsychChip. A Plink file set of these cohorts is provided here after merging the separate project file sets and extracting only the individuals who have expression data also provided here; quality control for SNP-missingness is recommended. We demonstrate in this study that given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample to allow for an a greater number of individuals sequenced. 

  Study phs002856

• "Elucidation of Immune Status and Its Clinical Significance in Patients with Solid Tumors, Including Gastrointestinal Cancers": A Phase II Clinical Trial of Lenvatinib Plus Pembrolizumab in Patients with Advanced Gastric Cancer

  The objective is to analyze tumor and normal cell exome sequencing of gastric cancer patients participating in the EPOC1706 trial before treatment and RNA sequencing specimens of tumor biopsy specimens at two points before treatment and after the combination therapy of Lenvatinib plus pembrolizumab, in order to search for biomarkers to predict treatment response. Exome sequencing from 10 gastric cancer patients participating in the EPOC1706 trial, and RNA sequencing of tumor biopsy specimens at two time points before treatment (9 patients) and after the combination therapy (8 patients) were obtained.

  Study JGAS000894

• Plasma-Seq follow-up CSPC4

  We performed serial plasma-Seq analyses on a male who progressed from castration-sensitive to castration-resistant prostate cancer within 10 months following treatment with androgen-deprivation therapy.

  Dataset EGAD00001000396

• Aggregated panel-seq VCF for initial cohort screened for BoB

  Aggregated VCF file from cancer genes panel seq for the initial (n=500) cohort of solid tumors screened for the Basket of Baskets study

  Dataset EGAD00001008437