The thing is that all those commercial pathway providers like Ingenuity and GeneGO offer a lot of content that they developed in house for specific fields. Ingenuity is quite good in the cardiovascular field and GeneGo’s Metacore is good Toxicology for instance (and more metabolite directed research in general). So if you did something specifically in Ingenuity or want to reproduce that you might not easily find an alternative. Although all the content they offer is based on knowledge freely available in other pathway databases (Ingenuity started with a lot of KEGG pathways) and the literature.
That being said there are a lot of freely available pathway analysis tools and pathways. Check out Pathwaycommons for a kind of integrated approach (that includes Reactome a.o). You might also want to try our own WikiPathways and the accompanying pathway analysis tool PathVisio. At the PathVisio download page we also offer converted KEGG pathways for many species that you could also analyze using PathVisio.
HumanCyc plus Pathway Tools provides another set of options. HumanCyc has well curated content on human metabolic pathways. The associated Pathway Tools software will let you paint gene expression, proteomics, or metabolomics data onto the HumanCyc pathway map, and Pathway Tools will also perform enrichment analysis. See BioCyc.org. The pathway painting is available through the web site, but to perform enrichment analysis you must download and install the software.
(My group develops these two tools.)
Course there are a lots of soft-wares you can use to perform a similar analysis: -network analysis and visualization Cytoscape, sure you have heard of it (lots of plugins) -pathway enrichment analysis with topological information, read the paper 10 years of pathway analysis. -ORA, MEA: DAVID -gene-disease association CTD database, DIsGeNET plugin from Cytoscape.
An important thing is that you design a workflow for the analysis of data that include all of the suggested tool (at least some of them).
Personally, I really enjoy interpreting comparative proteomics results with free tools. Never used IPA Cheers Teresa 😉
There have been a lot of good suggestions.
I would also recommend GATHER for a quick-function enrichment tool (for KEGG pathways) along with several other categories:
I also developed a tool called BD-Func, which includes some categories that people would probably consider “pathways” (such as transcriptional regulators and some signatures for signaling pathways):
http://sourceforge.net/projects/bdfunc/ (standalone version)
http://www.bioconductor.org/packages/release/bioc/html/sRAP.html (functions implemented in the sRAP package)
Of course, there are also tools like GSEA, FuncAssociate, DAVID, etc. (if you are more broad in what you define as a “pathway”)
Thanks to Kissaj for bringing this back to the top. It made me realize it’s time for an update about iPathwayGuide.
The application now accepts a wide variety of gene-expression data including:
- JMP Genomics
- Affy CEL files
- custom *.txt file (must have gene symbol, FC, p-value)
With these data we provide a free platform to look at your data in the context of Genes, GO Tems, Predicted miRNAs, Pathways, or Diseases. There are a number of advantages to using iPathwayGuide beyond it being 100% free to use, but the key difference is that we use Impact Analysis to score the pathways. This approach uses two forms of evidence to score pathways, enrichment and perturbation.
Some of the new features since my last post in this thread include:
Predicted miRNA Analysis – We offer evidence of possible active miRNAs based on gene-expression signatures
Meta-Analysis – Quickly compare unique or common significant elements between experiments.
Affy CEL file support – Upload your CEL files directly and find your DEGenes in a couple minutes
Here’s a link to an overview video. http://youtu.be/5maN9krw-nI
Below is a screenshot of the Meta-Analysis.
Moksiskaan (http://csbi.ltdk.helsinki.fi/moksiskaan/) is an integrative pathway analysis tookit, which supports data sources such as Ensembl, KEGG, PINA, PathwayCommons, DrugBank, GO, SNPs3D, COSMIC, WikiPathways, Tumourscape, and TSGene. Using the provided tools (http://csbi.ltdk.helsinki.fi/moksiskaan/anduril/index.html?q=Moksiskaan%20project), you can prepare all sorts of graph models representing genes, proteins, drugs, pathways, diseases, biological functions, etc. related to your data. Moksiskaan is an Anduril anduril.org) based open source project, which means that it can be used easily with other Anduril components to carry out complete analyses. Here’s one example outputhttp://csbi.ltdk.helsinki.fi/moksiskaan/archive/ProcessStudy.pdf, but you can find more from the web site and from the supplements of the articles.