3334 results for "*geneti*"

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• May 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  May 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001005060

• Whole Genome Sequencing data for epigenetic subgroups of meningioma

  Bam files for 124 samples (62 tumor vs blood pairs); Whole Genome Sequencing performed on Illumina HiSeq X Ten

  Dataset EGAD00001005061

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee

  Four iPSC line data were sequenced by WGS. One of them has gene MYBPC3 modified.

  Dataset EGAD00001005066

• GWAS results from Danjou et al, Nature Genetics 2015

  GWAS results in epacts format for Danjou et al, Nature Genetics 2015

  Dataset EGAD00010001722

• Somatic genetic basis of Wilms' tumour

  We investigated the somatic genetic basis of Wilms' tumour and found complex phylogenetic relations between tumours

  Dataset EGAD00001005134

• Somatic genetic basis of Wilms' tumour

  We investigated the somatic genetic basis of Wilms' tumour and found complex phylogenetic relations between tumours

  Dataset EGAD00001005135

• Somatic genetic basis of Wilms' tumour

  We investigated the somatic genetic basis of Wilms' tumour and found complex phylogenetic relations between tumours

  Dataset EGAD00001005136

• The mutational landscape of normal human endometrial epithelium - Additional Samples

  All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

  Dataset EGAD00001005214

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Gastric Organoids (2019-08-07)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005234

• Next gen seq of eye cancers (2019-08-14)

  Retinoblastoma (RB), the commonest eye cancer in children was the first cancer for which a genetic cause was identified: the Rb1 gene is a tumour suppressor gene that is mutated in RB. The Rb1 gene defect alone does not predict the clinical outcome. We propose to study other possible mechanisms: 1. Stepwise further mutations occur in RB, increasing its carcinogenesis. We will sequence the whole genome in RB tissue, and relate the different genes expressed to the treatments used. 2. Extracellular matric proteins contribute to a tumour permissive environment for RB to continue to grow. This includes Samll Leucine Rich Proteoglycans (SLRP), a family of 15 secreted extracellular matrix proteins involved in eye development. 3. Cancer stem cells (CSC), a subpopulation of treatment resistant cells, drive RB tumours, and whether these stem cells can be manipulated for new therapies. The aim of this study is to assist finding targeted diagnostic techniques and treatments for RB. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005251