About this Class

Learn how to easily analyze your gene expression data yourself - using Qlucore Omics Explorer NCI/CCR:To get access to Qlucore, put a request into NCI at Your Service under Get Help https://service.cancer.gov/Get Help Qlucore empowers bench scientists to easily visualize and analyze large numerical data sets such as gene expression (array and RNA-seq), DNA methylation, miRNA, Proteomics, Metabolomics and Flow Cytometry data. No scripting, tables or complex settings, you will have instant visual feedback on complex calculations, interactive plots, and integration with GSEA. Morning session (10AM - noon) – Introduction and live basic hands-on training for new users , bring your government-issued laptops so you can get on the network and follow along, we will provide the license access) Qlucore Omics Explorer is an interactive analysis and visualization tool that helps the user to find groups, structures, variable networks and discriminating variables. You can use your own data and also analyze public data. Omics Explorer supports 3D PCA plots, t-SNE plots, Heat maps with hierarchical clustering, Scatter plots, Volcano plots, Box plots etc. A number of statistical methods are included, like t-test, F-test (ANOVA) and different regressions tests. Plots are dynamically updated as filters change and analysis is done, which allows a very interactive exploration to test out new hypothesizes. Omics Explorer has an interface which makes it possible to use statistical functions created in "R" from inside Omics Explorer, so that you can use external statistical methods implemented in “R” like Limma/voom, Welch, Mann-Whitney, Kruskal-Wallis and also add you own "R" scripts. With machine learning algorithms (kNN, SVM and Random Trees) classification of samples in new data sets is simplified. The product has an inbuilt Gene Set Enrichment Analysis (GSEA) workbench for pathway analysis, a direct interface to GEO and an inbuilt Gene Ontology browser. The product has an import wizard to simplify data import. Aligned BAM files (RNA-seq) and microarray files (.cel files) can be directly imported, normalized and log transformed through import pipelines, and GEO soft files can be directly imported. Trough Qlucore Templates, based on “Python”, you can create scripts of commands that are executed by Qlucore Omics Explorer. You can create standardized analysis templates for standard analysis, and the integration with Python also opens up possibilities for customization. As an example, there is a TCGA mRNA dataset download Template that comes preinstalled. Qlucore NGS module is an optional add-on module to Qlucore Omics Explorer. The main components of the NGS module are an interactive and fast Genome Browser for many samples and many tracks per sample, a genome filter control component, a Project Manager for project set-up and a built in Variant Caller for short indels and variants. The options available for RNA-seq analysis really stand out. Utilizing the existing functionality in Qlucore Omics Explorer for expression data and combining it with the new functionality in Qlucore NGS Browser enables significantly increased analysis options. The Genome Browser content is dynamically updated when filters and filter cut-off are changed using sliders and check-boxes. If you are unable to attend in person, WebEx will be provided: https://cbiit.webex.com/cbiit/j.php?MTID=mfdae6115f8953fb2aeb00ff9c64e7b6f    

Files

• NCI-CCR-training-Feb-2020.zip: |
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