Genome

Other software

IPA from Ingenuity

Login: There are web started version https://analysis.ingenuity.com/pa and Java applet version https://analysis.ingenuity.com/pa/login/choice.jsp. We can double click the file <IpaApplication.jnlp> in my machine's download folder.

Features:

• easily search the scientific literature/integrate diverse biological information.
• build dynamic pathway models
• quickly analyze experimental data/Functional discovery: assign function to genes
• share research and collaborate. On the other hand, IPA is web based, so it takes time for running analyses. Once submitted analyses are done, an email will be sent to the user.

Start Here

Expression data -> New core analysis -> Functions/Diseases -> Network analysis
                                        Canonical pathways        |
                                              |                   |
Simple or advanced search --------------------+                   |
                                              |                   |
                                              v                   |
                                        My pathways, Lists <------+
                                              ^
                                              |
Creating a custom pathway --------------------+

Resource:

• http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf
• http://libguides.mit.edu/content.php?pid=14149&sid=843471
• http://people.mbi.ohio-state.edu/baguda/PathwayAnalysis/
• IPA 5.5 manual http://people.mbi.ohio-state.edu/baguda/PathwayAnalysis/ipa_help_manual_5.5_v1.pdf
• Help and supports
• Tutorials which includes
  • Search for genes
  • Analysis results
  • Upload and analyze example data
  • Upload and analyze your own expression data
  • Visualize connections among genes
  • Learn more special features
  • Human isoform view
  • Transcription factor analysis
  • Downstream effects analysis

Notes:

• In this prostate example data tutorial, the term 'fold change' was used to replace log2 gene expression. The tutorial also uses 1.5 as the fold change expression cutoff.
• The gene table contains columns 'Fold change', 'ID', 'Notes', 'Symbol' (with tooltip), 'Entrez Gene Name', 'Location', 'Types', 'Drugs'.

Screenshots: