11925 results for "cancer rna-seq"

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• Cystic fibrosis multi-omics study

  Cystic fibrosis (CF) is a genetic disorder affecting approximately 1 in 2,500 people in the UK. Here, we generated a number of high-throughput sequence data sets for monocytes and neutrophils from CF patients and matched healthy volunteers (HV); including ChIP-Seq (H3K27Ac), chromatin accessibility (ATAC-Seq), and transcript/gene expression (RNA-Seq) data. Analysis of gene expression and epigenetic profiles demonstrates a robust innate immune gene expression profile that distinguishes CF and HV during periods of disease exacerbation. Upregulation of pathways responsible for the production of proinflammatory cytokines is described.

  Study EGAS00001006421

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000640

• RNA-seq

  The RNA was extracted using the AS1390 PROMEGA kit according to the manufacturer’s instructions. The samples underwent sequencing using a Novaseq 6000 machine, equipped with an SP 200 cycles v1.5 cartridge. The sequencing process varied slightly across batches based on the input RNA and the library preparation kits used.

  Dataset EGAD50000002023

• RNA-sequencing

  Raw reads from RNA-sequencing of monocyte-derived macrophages from three individuals with heterozygous TET2 loss (Ly9, Ly11, Ly14) and two wild-type controls (Ly8 and an unrelated control). Libraries were prepared using ScriptSeq RNA-Seq Library Preparation Kit and Illumina sequenced with paired-end 75bp reads.

  Dataset EGAD00001004784

• Targeted RNA Expression Profiling via scTAMARA-seq

  This dataset comprises targeted single-cell RNA expression profiles derived from the same CD34+ bone marrow sample (patient X.1) used for scTAMARA_DNA. 120 RNA targets were selected using LASSO regression to capture key transcripts predictive of cell state within the hematopoietic compartment.

  Dataset EGAD00001015495

• Human pancreatic beta cell RNA-seq

  Dataset EGAD00001000393

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line RNA-Seq derived

  Study EGAS00001006803

• 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

• Histone and transcriptome profiling of glioblastoma initiating cells

  ChIP-seq and RNA-seq of glioblastoma initiating cells and their differentiated counterparts with and without inhibition/knockdown of KDMs.

  Dataset EGAD00001005124

• CBB post-mortem hippocampal short-RNA-seq

  Short RNA sequencing of post-mortem human hippocampi from the Calgary Brain Bank. The dataset includes patients with Alzheimer's disease (AD) and healthy control individuals (Ctrl).

  Dataset EGAD00001006886