Analysis Services
Gene Expression Analysis Services
In addition to providing the infrastructure for generation of gene expression data, using one of the available technologies, the facility also coordinates support for the analysis of data that derives from these assays. The analysis services are performed on a consulting basis, with assistance provided by an individual associated with the facility operating on a fee-for-service basis. Investigators interested in analysis support should submit a one page summary of the experimental design and analysis goals of the project to microarray@duke.edu prior to a consultation meeting in which analysis services will be discussed. Analysis services include the following:
Basic services (~2-5 hrs depending on scope of project)
- Data quality assessment
- Data normalization (lowess, quantile or RMA) and filtering
- Determination of differential gene expression by ANOVA, SAM and fold change
- Hierarchical clustering
- Annotation of differential gene list (GATHER, Genespring, and Ingenuity)
- Generation of web pages for presentation of data and results
Advanced services (>4 hours depending on scope of project)
- Supervised analysis of expression data in relation to experimental phenotypes (Makes use of Duke-developed analysis programs)
- Support Vector Machine analysis (SVM) to find clinically predictive expression patterns
- Characterization of expression data for Duke-developed patterns of pathway activation and other relevant expression-based characterizations
For Data Analysis Request, please submit a online submission. (same as any other microarray services we provide)
- Link to online submission form
- Select New Submissions -> Data Analysis
- Fill up contact information and submit.
- The submission form will allow us to upload analysis result up to the data repository for downloading and allow us to create an invoice for the data analysis charging.
Download the template Summary of Experimental Design and Analysis Goals (Word Doc)
Download the Data Analysis General Workflow and Analysis Options (ppt)