geWorkbench

The tutorials shown on this page provide a quick introduction to the most important features of geWorkbench. Additional information can be found in the User Guide and in the Online Help section of the program.

All data sets used in the tutorials are available from the download area of our site.

Using the basic framework of geWorkbench: Projects, files and data

Quick Start

A quick jump into the most important topics for learning to use geWorkbench.

Basics

An introduction to the use of geWorkbench.

Component Configuration Manager

Customize geWorkbench to your needs. geWorkbench comes initially configured with only basic components installed. Use the CCM to load additional available modules.

Projects

The Project Folders component is where data is loaded and analysis results are stored.

Project Details

Describes components use to record details of calculations and datasets.

Local Data Files

Covers loading data from files on your local computer.

File Formats

Details of several different file formats supported by geWorkbench.

Remote Data Sources (caArray)

How to download microarray data from caArray. geWorkbench can download "derived" data sets from caArray.

Data Subsets - Arrays

How to create and use sets of arrays for controlling data analysis.

Data Subsets - Markers

How to create and use sets of markers for controlling data analysis.

Viewing a Microarray Dataset

Survey of geWorkbench visualiztion tools for microarray data.

Filtering

geWorkbench provides numerous methods for filtering microarray data.

Normalization

geWorkbench provides numerous methods for normalizing microarray data.

Tutorial Data

Downloadable data used in the tutorials.

Individual analysis and visualization components

Analysis Framework

Most analysis routines are located in the command area located in the lower right quadrant of geWorkbench. This section describes a common framework for saving parameter settings that these components share.

ANOVA

How to set up and run Analysis of Variance.

ARACNE

Formal method for reverse Engineering - microarray datasets can be analyzed for interactions between genes. Now includes new ARACNe2, which implements the much faster Adaptive Partitioning algorithm and accurate parameter estimation.

BLAST

Submits BLAST jobs to the NCBI server and displays and allows further interaction with alignment results.

Cellular Networks KnowledgeBase

The CNKB component queries a database of protein-protein and protein-DNA interactions maintained at Columbia University.

Classification

Several classification components have been ported by the GenePattern development team to work with geWorkbench. These include K-nearest neighbors (KNN), Principle Component Analysis (PCA), Support Vector Machines (SVM) and Weighted Voting (WV).

Color Mosaic

Displays expression results as a heat map.

Cytoscape

Cytoscape is used to display network interaction diagrams (from adjacency matrices). It features two-way interaction with the geWorkbench Markers component.

Differential Expression (t-test)

Several variants of the t-test are available.

Expression Value Distribution

View and manipulate a histogram of the distribution of expression values for each array.

Gene Ontology Term Over-representation

Finds Gene Ontology terms that are over-represented in a list of genes of interest.

genSpace

GenSpace is a social networking tool which allows patterns of use (putative workflows) of geWorkbench components to be inferred and queried. If desired, (participation is entirely optional) it can be used to identify potential expert users of particular components who may be able provide advice.

Grid Services

A number of geWorkbench data analysis components have been implemented as services on the National Cancer Institute's caGrid. caGrid is an infrastructure component of the NCI's caBIG(R) program.

Hierarchical Clustering

geWorkbench implements its own agglomerative hierarchical clustering algorithm.

Jmol

Jmol is a molecular structure viewer for viewing PDB format files.

Marker Annotations

Marker annotations can be retrieved, including BioCarta pathway diagrams.

Pattern Discovery

Upstream seqeunce can be analyzed for conserved sequence patterns.

Promoter Analysis

Search a set of sequences against a promoter database.

Sequence Retrieval

Genomic sequences for markers can be retrieved for further analysis.

SOM

Clustering using Self-Organizing Maps.

Coming Soon

Tutorials for a number of components are under development, including:

• Expression Profiles
• Sequence (Viewer)
• genSpace
• SkyBase
• SkyLine
• Online Help
• NetBoost

Gene Pattern components:

• PCA (GenePattern) - Analysis and Viewer
• SVM 3.0 (GenePattern) - Analysis and Viewer - include, we need to develop online help and tutorial (Aris).