User:Smith
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? The menu bar - point out that some commands are available both from the menu bar and by right-clicking on a dataset....
2.3 Loading Data 2.3.1 File types supported Expression Affymetrix MAS5/GCOS (text files output by Affymetrix software) Affymetrix File Matrix (.exp)(a geWorkbench defined format) RMAExpress Processed File GenePix Note - the type "Normalized no-confidence expression matix" has switched the phenotype and gene labels -don't use until fixed. Genotypic Genotypic data files - is this working? Sequence Fasta Pattern Detection Pattern Files
2.3.2 Loading MAS5/GCOS type files Use the 10 cardiomyopathy files from Harvard. What happens the first time a new chip-type is loaded - how long does it take, what is happening, what internal files are being built? 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 Use the cardiomyopathy dataset created in 2.3 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 2.5 Saving data files Use the cardiomyopathy dataset annotated in 2.4 2.5.1 Save to matrix file
2.5 Visualize Gene Expression 2.6 Filter and Normalize Data 2.6.1 Normalize 2.6.2 Filter 2.7 Clustering Gene Expression Data 2.8 Differential Expression 2.8.1 T Test 2.9 Regulatory Network 2.10 Integrated Annotation Information 2.11 Enrichment Analysis 2.12 Sequence Analysis 2.13 Pattern Discovery 2.14 Promoter Analysis