3901 results for "*geneti*"

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• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004416

• Ovarian Cancer Organoid Biobank - RNASeq data

  Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004509

• Genetic drivers of epigenetic and transcriptional variation of human immune responses to infection (RNA-seq, ATAC-seq and ChIPmentation)

  RNA-seq, ATAC-seq and ChIPmentation data from monocyte-derived macrophages that were infected with Influenza A virus strain PR8WT, or a matching non-infected control.

  Dataset EGAD00001008422

• Assessment of genetic and epigenetic variation in human IPS cells

  In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs but it is unclear whether some cell types carry through fewer mutations through reprogramming (either due to mutations present in the primary cells, or mutations accumulated during reprogramming). Through in depth analysis of hiPSCs generated from different somatic cells, it will be possible to assess the variation in genetic stability of different cell types.

  Dataset EGAD00001000798

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for mature neutrophil, on genome GRCh37)

  RNA-Seq data for 205 mature neutrophil sample(s). 205 run(s), 205 experiment(s), 205 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002675

• Raw data for "Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse"

  FASTQ files from Illumina sequencing of 10x Visium experiments.

  Dataset EGAD00001010260

• GILD-ExomeSeq-PTNHL

  This study is meant to gain further knowledge in haematological cancers. Patients samples (mainly DNAs or PCR products) from haematolocical cancer patients will be sequenced, and the outputs will be correlated to their diagnosis and/or prognosis; the findings may also add more insight into the understanding of biology in this type of tumour. We will be sequencing Primary Testicular Lymphomas (PTL) to identify genetic drivers of this rare cancer

  Dataset EGAD00001001986

• Genetic landscape of Extranodal NK/T-cell lymphoma

  Whole-exome sequence (WES) data of tumor-normal pairs from 40 ENKTCL patients and RNA sequence (RNA-seq) data of tumors from 20 ENKTCL patients.

  Dataset EGAD00001009852

• Whole-exome sequencing of 20 samples of actinic keratosis (10s) and cutaneous squamous cell carcinoma (10s)

  Whole-exome sequencing of 20 samples of actinic keratosis (10) and cutaneous squamous cell carcinoma (10) was performed to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns. 7 samples were shown to belong to the stem cell-like subclass (4 AK and 2 SCC), 12 - to the keratinocyte-like subtype (6 AK and 6 SCC) and one SCC sample is unclassified (was not included in the methylation analysis). Exome regions were captured using Agilent Low Input Exome-Seq Human v5 kit and sequenced on Illumina Hiseq4000 with paired-end 100-nucleotide reads.

  Dataset EGAD00001003765

• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues.

  Dataset EGAD00001002266