Use on microarrays in life science in on the rise. A very common question asked by life science researchers is which tool they should be using to correlate microarray data. The ideal solution is depends on your computer skills, time constraints, ability to buy licensed software and most importantly the correlation you intend to establish. Following is a list of the best solutions available.

- EBI Expression Profiler
- R Language with Bioconductor Package
- EisenSoftware and visualization with Maple Tree of Java Tree View
- SAM: Significance Analysis of Microarrays
- Agilent GeneSpring GX Software
- Partek
- BRB Array Tools

In my opinion, the best solution is R language with Bioconductor Package. A novice would require at most 20 hours to gain sufficient working knowledge of this solution. Partek (licensed software) and SAM are user-friendly software but they are not as powerful as Bioconductor. If you work frequently with microarray data, it is advised that you try all of the above-mentioned solutions as none is perfect.