Revision as of 13:40, 16 February 2006

Design and outline of tutorials for geWorkbench

Tutorial Design considerations - 1. Probably best not to use detailed section numbers, since we cannot autoupdate them in this wiki. Instead, rely on links? 2. Each section should list example data files needed, and these should be part of distribution.

Outline for tutorials

        2.1 Before You Begin
        2.2 Getting Started
             Is caWorkbench downloaded and installed?  Link to download and installation
             Important concepts:
                 Optional use of activated phenotype and marker panels throughout application.
                      What is default active set if no panels are active?
        2.3 Loading Data
             2.3.1 File types supported
                    Expression:
                       MAS5/GCOS
                       Matrix (.exp)
                       RMAExpress
                       GenePix
                    Sequence
                       Fasta
                    Pattern
                       ?????
             2.3.2 Loading MAS5/GCOS type files
                        Uses 10 cardiomyopathy files from Harvard.
             2.3.3 Merging loaded data
             2.3.4 Loading matrix format files
                        Include webmatrix2000G?, webmatrix4000G? and webmatrix.exp?
                    Note - explain matrix format in an appendix
             2.3.5 Other file types supportedLoading RMAExpress files
                    Must generate an example RMAExpress file, start with harvard cardio files?
        2.4 Working with Marker and Phenotype Panels
               2.4.1 Creating Phenotype Panels
               2.4.2 Assigning Case/Control status
               2.4.3 Activating a phenotype panel
               2.4.4 Creating Gene/Marker Panels
               2.4.5 Activating a phenotype panel
               
                 

         o 2.5 Visualize Gene Expression
         o 2.6 Filter and Normalize Data
               + 2.6.1 Normalize
               + 2.6.2 Filter
         o 2.7 Clustering Gene Expression Data
         o 2.8 Differential Expression
               + 2.8.1 T Test
         o 2.9 Regulatory Network
         o 2.10 Integrated Annotation Information
         o 2.11 Enrichment Analysis
         o 2.12 Sequence Analysis
         o 2.13 Pattern Discovery
         o 2.14 Promoter Analysis