TOOLS & FEATURES

Easy tools for complex queries
Designed by biology researchers - developed by computer scientists
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Graphical user interface. GENEVESTIGATOR offers a rich graphical interface to query and interpret a very large database of professionally curated expression data. Its tools help you to find relevant conditions for your genes of interest, to find genes having specific properties (e.g. biomarkers, targets), or to identify gene expression modules that are co-regulated over selected conditions. The tools let you analyze either individual experiments (Single Experiment Analysis) or thousands of experiments simultaneously (Compendium-Wide Analysis).


SINGLE EXPERIMENT ANALYSIS tools


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Samples tool. With this tool, explore the expression level of genes across samples from any experiment selected from the database. Compare the expression of multiple genes and find detailed information about samples in which expression is particularly high or low.


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Diff-Expression tool. Powerful and extremely fast tool to run differential expression analysis between two groups of samples from a chosen experiment. The user can choose and experiment, define samples belonging to each group, and run LIMMA with multiple testing correction (Benjamini-Hochberg).

CONDITION SEARCH tools


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Anatomy tool. Visualize the expression of genes across many tissues and cell types. Example shown: expression of the PAX2 gene across 246 different human tissue types. The plot is sorted by highest to lowest expression. For each boxplot, a detailed view is available to see expression in each underlying sample.


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Cell Lines tool. Visualize the expression of genes across a large collection of cell lines. Example shown: expression of the PCSK4 gene across 416 different human cell lines. The plot is sorted by highest to lowest expressing cell line for this gene. The detailed view shows the sample level expression of the first category.


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Cancers tool. Visualize the expression of genes across a large collection of different cancer types and compare with normal tissues or with metastasic or xenograft samples. Upper section: Boxplots of gene expression of the ERBB2 gene across several subtypes of breast cancer. Lower section: Detailed view of the selected boxplot. With the Neoplasms tool, you can visualize the expression of genes of interest across more than 1,000 different subtypes of cancers and include over 250 different normal tissues as controls into the same plot.


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Perturbations tool. With this tool, you can easily identify conditions that significantly affect the expression of genes of interest. This screenshot displays the response of three probe sets representing the human SOX4 gene to 835 different experimental conditions. . The results have been filtered by p-value and fold-change to extract the most relevant conditions. In the lower section, you can drill down to the sample level for each condition described above and get for instance clinical parameters.



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Development tool. Expression of selected genes from mouse across different stages of development. For each stage, expression values and standard deviations are calculated from all microarrays annotated for that particular stage.

GENE SEARCH tools


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Anatomy / Cell Lines / Neoplasms tools. These three tools have an identical layout and allow searching for genes specifically expressed in chosen tissues, primary cells, cell lines or cancers. In this example, we searched for genes specifically expressed in fallopian tube neoplasm by screening against 1734 tumor type categories. Approximately 60 genes were found to be highly specific for this cancer.



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Perturbations tool. This is an example of a biomarker search using the Perturbations tool from the Gene Search toolset. Crohn's disease and ulcerative colitis are chosen as target categories (for up- or downregulated genes), all other conditions are chosen as base (unchanged). We obtain a list of genes dysregulated in these two diseases but minimally changed in all base conditions.



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Development tool With this tool, you can easily and rapidly identify genes expressed at a particular stage of development of an organism.


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RefGenes tool. Identification of genes having the smallest expression variance across 26,075 human samples (Affymetrix 133 Plus 2 arrays). The two boxplots in the upper section represent, as a comparison, the expression distribution of PPIA and B2M (two commonly used reference genes for RT-qPCR) across the same set of samples.

SIMILARITY SEARCH tools


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Hierarchical Clustering tool. Hierarchical clustering of the expression of 32 genes throughout a time-course experiment. Leaf ordering was applied to achieve a better representation of the chronological events. Two main clusters are clearly visible.



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Biclustering tool. The biclustering tool helps you identify genes that are up- or down-regulated over a subset of conditions (rather than over all conditions). Here we show a bicluster analysis of 200 genes across 555 conditions. 377 different biclusters were identified. One of them is shown here.



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Co-Expression tool. This tool allows the identification of the genes most correlated to a target gene across any chosen set of experiments. The results are calculated on-the-fly, making it very flexible and intuitive. This screenshot shows the identification of the genes most correlated with the human TRDN gene across 1487 different types of tissues and cancers. Genes mutually correlated above a given threshold are linked, revealing distinct clusters among the most correlated genes. Combining this tool with the Perturbations tool above allows users to find biologically very meaningful co-regulation clusters.


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Signature tool. With this tool, you can screen the complete database to find results that are similar to those you have obtained in your own experiment. Simply enter a vector of expression (gene identifiers and corresponding expression values from qPCR, microarrays or RNA-seq) and run the search. GENEVESTIGATOR searches for those conditions in which these genes are regulated the same way.


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Gene Set Enrichment tool. Enter a gene set and easily find out to which pathways, biological processes or diseases it is related. In the top table, a list of all significant gene sets is displayed. In the bottom table, the genes populating the gene sets selected are displayed. A Venn diagram allows you to visualize up to four gene sets and to select genes that overlap between these sets.

General Options


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Selecting experiments of interest. You can easily create a selection of data you would like to work with. Choose either entire experiments (chosen by keyword or by therapeutic area), or select all samples having a particular description (tissue type, disease, cell line, cancer type, genotype, etc.). The selection by keyword or therapeutic area is cross-platform and cross-organism, thus allowing to find all experiments related to a particular topic.


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Filtering options. All experiments in GENEVESTIGATOR have been carefully and precisely annotated by our curators. Users can select experiments or samples at a very detailed level, or can filter results and check the effect of clinical parameters. The above screenshot shows how a selection of samples can be filtered by parameters like age, sex, disease state, smoking, etc.



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Viewing experimental details. Across all GENEVESTIGATOR tools, further details about each gene or condition are available in mouse-over windows. In this example, the exact experimental conditions for doxycycline study 2 are described, including the genetic background and other parameters. Web links to the original repository and to publications describing this experiment are also provided.