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Revision as of 17:43, 8 March 2011
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.
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.
MarkUs
The MarkUs component assists in the assessment of the biochemical function for a given protein structure. The component in geWorkbench provides an interface to the MarkUs web server at Columbia. MarkUs identifies related protein structures and sequences, detects protein cavities, and calculates the surface electrostatic potentials and amino acid conservation profile.
Marker Annotations
Marker annotations can be retrieved, including BioCarta pathway diagrams.
Master Regulator Analysis
The Master Regulator Analysis (MRA) component attempts to identify transcription factors which control the regulation of a set of differentially expressed target genes (TGs). Differential expression is determined using a t-test on microarray gene expression profiles from 2 cellular phenotypes, e.g. experimental and control.
MatrixREDUCE
MatrixREDUCE is a tool for inferring the binding specificity and nuclear concentration of transcription factors from microarray data.
MINDy
MINDy identifies modulators of gene regulation using conditional ARACNe calculations.
Pattern Discovery
Upstream seqeunce can be analyzed for conserved sequence patterns.
Promoter Analysis
Search a set of sequences against a promoter database.
Pudge
Pudge provides an interface to a protein structure prediction server (Honig lab) which integrates tools used at different stages of the structural prediction process.
Sequence Retrieval
Genomic sequences for markers can be retrieved for further analysis.
SOM
Clustering using Self-Organizing Maps.
SVM
Classification using Support Vector Machines.
Coming Soon
Tutorials for a number of components are under development, including:
- Expression Profiles
- Sequence (Viewer)
- SkyBase
- SkyLine
- Online Help
Gene Pattern components:
- PCA (GenePattern) - Analysis and Viewer
