GeneLinker™ Tour - Introduction

Welcome to GeneLinker™

Thank you for choosing GeneLinker™ as your gene expression analysis system. The GeneLinker™ family of products are designed to help you discover underlying patterns in the data generated by modern high-throughput gene expression measurement techniques; the first step in discovering new relationships among genes.

Introduction

This tour describes the GeneLinker™ main window and outlines the program's major functionality groups (e.g. data import, preprocessing, clustering, visualization, and for platinum - classification). The fastest way to learn to use GeneLinker™ is to finish this tour and then run the tutorials.

Some additional functions not covered in this tour are GeneLinker's Scripting and Meta-Scripting capability. These advanced features greatly enhance GeneLinker's ease-of-use by allowing repetitive actions to be performed automatically.

Terminology

Term	Definition
Dataset	A dataset is either a raw or preprocessed set of expression values for a number of genes over a number of samples. A dataset can have reliability measurements or variables associated with it. For a complete description see Datasets Overview and Reliability Measures. A standard dataset contains a single value for each gene for every sample (some may be replicate measurements within or between chips; in an incomplete dataset, one or more values are null or missing). A two-color dataset contains two values for each gene for every sample. One value is the treatment expression level and the other is the control expression level. See Two-Color Data.
Experiment	An experiment is a dataset that has had its gene or sample order organized by the application of an experiment process such as clustering.
Variable	In GeneLinker™, a variable is a column of data other than gene expression values used to differentiate samples. See Variables Overview. A variable can store: Phenotypic observations about the samples. e.g. malignant vs. benign. Predictions of phenotypes by a trained classifier. e.g. predicted malignant vs. predicted benign. Information about experimental conditions. e.g. high dose vs. low dose; time the sample was taken; animal A vs. animal B vs. animal C, etc.