Data Access Commitee for the project : Methylome profiling of human mesenchymal chondrosarcoma
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ABSTRACT:
PROVIDER: EGAC00001003217 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Data Access Committee EGAC00001003214
| EGAC00001003214 | EGA
Project description:The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets.
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Project description:Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.
| S-EPMC6823446 | biostudies-literature
Project description:The 1000 Genomes Project was launched as one of the largest distributed data collection and analysis projects ever undertaken in biology. In addition to the primary scientific goals of creating both a deep catalog of human genetic variation and extensive methods to accurately discover and characterize variation using new sequencing technologies, the project makes all of its data publicly available. Members of the project data coordination center have developed and deployed several tools to enable widespread data access.
| S-EPMC3340611 | biostudies-literature
Project description:Data Access Committee EGAC00001001472
| EGAC00001001472 | EGA
Project description:Data Access Committee EGAC00001002803
| EGAC00001002803 | EGA
Project description:Methylation of DNA molecules is a key mechanism associated with human disease, altered gene expression and phenotype. Using reduced representation bisulphite sequencing (RRBS) technology we have analysed DNA methylation patterns in healthy individuals and identified genes showing significant inter-individual variation. Further, using whole genome transcriptome analysis (RNA-Seq) on the same individuals we showed a local and specific relationship of exon inclusion and variable DNA methylation pattern. For RRBS, 363 million, 100-bp reads were generated from 13 samples using Illumina GAII and HiSeq2000 platforms. Here we also present additional RRBS data for a female pair of monozygotic twins that was not described in our original publication. Further, We performed RNA-Seq on four of these individuals, generating 174 million, 51-bp high quality reads on an Illumina HiSeq2000 platform. The current data set could be exploited as a comprehensive resource for understanding the nature and mechanism of variable phenotypic traits and altered disease susceptibility due to variable DNA methylation and gene expression patterns in healthy individuals.
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Project description:Phase 1 of the Human Microbiome Project (HMP) investigated 18 body subsites of 242 healthy American adults to produce the first comprehensive reference for the composition and variation of the "healthy" human microbiome. Publicly available data sets from amplicon sequencing of two 16S ribosomal RNA variable regions, with extensive controlled-access participant data, provide a reference for ongoing microbiome studies. However, utilization of these data sets can be hindered by the complex bioinformatic steps required to access, import, decrypt, and merge the various components in formats suitable for ecological and statistical analysis. The HMP16SData package provides count data for both 16S ribosomal RNA variable regions, integrated with phylogeny, taxonomy, public participant data, and controlled participant data for authorized researchers, using standard integrative Bioconductor data objects. By removing bioinformatic hurdles of data access and management, HMP16SData enables epidemiologists with only basic R skills to quickly analyze HMP data.
| S-EPMC6545282 | biostudies-literature
Project description:We applied methylome and copy number profiling to a set of 45 well characterized MCS cases to evaluate their potential diagnostic value. Notably, the findings were reproducible also when analysing the round cell and cartilaginous component separately. Furthermore, four outliers were identified by methylome profiling for which the diagnosis had to be revised. Methylome profiling represents a sensitive, specific and reliable tool to support the diagnosis of MCS, particularly if only the round cell component is obtained in a biopsy and the diagnosis is not suspected. It can furthermore aid in confirming the diagnosis in case RNA sequencing for the HEY1::NCOA2 fusion transcript is not available.
| EGAS00001007042 | EGA
Project description:Metastatic lung cancer is one of the leading causes of cancer death. In recent years, epithelial-to-mesenchymal transition (EMT) has been found to contribute to metastasis, as it enables migratory and invasive properties in cancer cells. Previous genome-wide studies found that DNA methylation was unchanged during EMT induced by TGF-? in AML12 cells. In this study, we aimed to discover EMT-related changes in DNA methylation in cancer cells, which are poorly understood.We employed a next-generation sequencing-based method, MSCC (methyl-sensitive cut counting), to investigate DNA methylation during EMT in the A549 lung cancer cell line.We found that methylation levels were highly correlated to gene expression, histone modifications and small RNA expression. However, no differentially methylated regions (DMRs) were found in A549 cells treated with TGF-? for 4 h, 12 h, 24 h and 96 h. Additionally, CpG islands (CGIs) showed no overall change in methylation levels, and at the single-base level, almost all of the CpGs showed conservation of DNA methylation levels. Furthermore, we found that the expression of DNA methyltransferase 1, 3a, 3b (DNMT1, DNMT3a, DNMT3b) and ten-eleven translocation 1 (TET1) was altered after EMT. The level of several histone methylations was also changed.DNA methylation-related enzymes and histone methylation might have a role in TGF-?-induced EMT without affecting the whole DNA methylome in cancer cells. Our data provide new insights into the global methylation signature of lung cancer cells and the role of DNA methylation in EMT.The virtual slides for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1112892497119603.
| S-EPMC4108085 | biostudies-literature