Series-files also contain tables describing extracted data, summary conclusions and analyses. Series-files are txt-files containing the definitions of a group of related samples and provides a focal point and description of the whole study. SOFT-files are simple line-based, plain text files that contain all the data and the descriptive information of a microarray experiment. The Workbench supports the GEO SOFT sample- and the GEO series-file formats. GEO is the largest public repository of microarray data. These may be imported from the Gene Expression Omnibus (GEO) database at NCBI (). 1.1 Importing array data The Workbench supports analysis of one-color expression arrays. A sample contains data (expression levels) for a number of features, usually genes. In the Workbench, a sample contains the expression values from either one array or from sequencing data of one sample. The main items to work with are samples, features and experiments. The result of this analysis can be imported and further analyzed in the CLC Main Workbench. This analysis has to be performed in the CLC Genomics Workbench. Note however, that the CLC Main Workbench is not able to calculate expression levels based on the raw sequence data. use annotations to categorize and interpret patterns among the DE genes in a biological context The methods shown in this tutorial will also work for gene expression data generated by high-throughput sequencing platforms (also known as Next-Generation Sequencing platforms). perform statistics and clustering to identify and visualize DE genes 4. import and set up the data in an experiment with two groups 2. In this tutorial, you will see how to: 1. The data comes from a study of gene expression in tissues from cardiac left ventricle and diaphragm muscle of rats (Lunteren et al., 2008). Tutorial 1: Microarray analysis This tutorial shows a straight-forward example of how to identify and interpret the differentially expressed (DE) genes in samples from two different tissues.
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