GxDb the Gene eXpression DataBase developed at IGBMC by Laëtitia Poidevin, Olivier Poch, Wolfgang Raffelsberger and Raymond Ripp
voir le wiki privé http://lbgi.fr/lbgiki/index.php/GxDb
See the GxDb website
Aim of GxDb
During the recent years gene expression profiling through transcriptomics has become an essential tool in many domains of research. This technique generates large quantities of data that may be exploited in many different ways allowing to reveal different aspects of the nature of the original data. The analysis and the meta- analysis of such data still remain quite laborious and often are not easily accessible to biologists. In this context, we develop an innovative platform, called GxDb, in order to offer an integrative tool for the analysis of transcriptomics data analysis. This platform is accessible through a secured web- portal and allows convenient upload of data, storage in a relational database and running many treatment and analysis procedures automatically. At the user interface, data query and analysis is greatly facilitated through the various modules and options for graphical display. GxDb clearly extends the opportunity to compare results from different treatment and analysis procedures (including human expert analysis) and/or different experiments. This also gives to the biologist tools for investigating and understanding the strengths and weaknesses of the data-treatments or combination thereof used during analysis, thus allowing to choose the best approach and tools for a given experimental question or a given gene.
Public Datasets in GxDb
- MouseGeneAtlasV3 High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we profiled gene expression from a diverse array of normal tissues, organs, and cell lines in mice.
- HumanGeneAtlas The tissue-specific pattern of mRNA expression can indicate important clues about gene function. High-density oligonucleotide arrays offer the pportunity to examine patterns of gene expression on a genome scale. Toward this end, we have designed custom arrays that interrogate the expression of the vast majority of rotein-encoding human and mouse genes and have used them to profile a panel of 79 human and 61 mouse tissues. The resulting data set provides the expression patterns for housands of predicted genes, as well as known and poorly characterized genes, from mice and humans. We have explored this data set for global trends in gene expression, valuated commonly used lines of evidence in gene prediction methodologies, and investigated patterns indicative of chromosomal organization of transcription. We describe undreds of regions of correlated transcription and show that some are subject to both tissue and parental allele-specific expression, suggesting a link between spatial xpression and imprinting. Keywords: different tissues.
- ALL Gene expression profiles were examined in 33 adult patients with T-cell acute lymphocytic leukemia (T-ALL) different immunophenotypic characteristics: 1,T2,T3,T4 and Tnc(incomplete phenotype)
- HumanBreastCancer Human breast cancer cell line MCF-7 is usually sensitive to chemotherapy drug BMS-554417, an insulin receptor (IR) and insulin-like growth factor receptor (IGFR) inhibitor. However, through step-wise increase in BMS-554417 doses in culture media, we were able able to screen and select a single MCF-7 clone that is BMS-554417 resistant. It is cross resistant to BMS-536924. This new line of MCF-7 cells was named as MCF-7R4. The transcriptome profiling of both MCF-7 and MCF-7R4 was performed sing Affymetrix HG-U133 plus2.0 GeneChip arrays.
- HumanEmbryo The process of early development of mammals is subtly and accurately controlled by the regulation networks of embryo cells. Time course expression data measured at different stages during early embryo development process can give us valuable information by revealing the dynamic expression patterns of genes in genome wide scale. In this study, Human embryo expression data were generated at one cell stage, two cell stage, four cell stage, eight cell stage, morula, and blastocyst.
Data obtained at the level of .CEL files are analysed with 6 different normalization softwares :
using programs developped with the R statistical package (http://www.r-project.org) and Bioconductor.
R is an open platform for statistical computation and Bioconductor is a microarray data analysis in R.
All the experiments in GxDb are clustered using 3 clustering methods from the Cluspack package
- km_dpc K-means Density of Point Clustering
- mm_aic Mixure Model Akaike’s Information Criterion
- mm_bic Mixure Model Bayesian Information Criterion