BioStar is a site for asking, answering and discussing bioinformatics question
s. We are members of the community and find it very useful. Often questions and answers arise at BioStar that are germane to our readers (end users of genomics resources). Every Thursday we will be highlighting one of those questions and answers here in this thread. You can ask questions in this thread, or you can always join in at BioStar.
Today’s question and answer is:
Recommend easy to use microarray clustering software
The most highly voted answer (was the author who posted the recommendation thread):
One of my favorites is the MEV micro-array data analysis tool. It is simple to use and it has a very large number of features.
Works well for any type of data. You can also load into it data from a file that is in a simple text format:
GENE1, value1, value2
GENE2, value1, value2
Feel free to post your favorite clustering tool.
Several other excellent tools were suggested, you can check them out here.
This week I’m returning to the exercise wherein I look at tools that analyze lists of genes. As before, I’m taking that list of genes I created some time ago. It was generated as a list of “disease” genes from UniProt. Today I’m taking that list to another resource: DAVID. DAVID is an unfortunate name to Google for this, but it stands for: Database for Annotation, Visualization and Integrated Discovery.
I have to say I was really impressed with the speed, ease, and results of this effort. It uploaded easily, automatically detected the species options, was quick to set for human as the focus, it offered 3 handy viewing option buttons really quickly, and provided informative output that would be really useful in further exploring my list. I had only chosen one of the possible options with default settings. There’s a lot more you can do with DAVID and we cover more of that in our full tutorial. But this quick start movie shows you something of the process and the outcome.
The citation for DAVID is:
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Reviewed by Glynn Dennis, Jr, Brad T Sherman, Douglas A Hosack, Jun Yang, Wei Gao, H Clifford Lane,2 and Richard A Lempicki. Genome Biol. 2003; 4(9): R60.
Well, actually, GOEAST young scientist. This week’s tip of the week builds on the data from my previous tip. I had generated a list of genes and I wanted to use that list at a variety of sites to analyze the features of my list. So this week I have tried that at GOEAST.
I used the first 1999 items in my UniProt disease list and uploaded them to GOEAST. The movie shows you the process and a quick look at the outcome.
This view is just a quick example of a basic list upload using their Batch tool. The Batch tool algorithm is somewhat different from the pre-loaded microarray gene analysis they say, because of the way the background is calculated. It outputs the GO terms and groups the genes that fit that GO term. There are a number of other features of GOEAST that look intriguing and helpful. It looks like they handle various microarray platforms easily. They have a variety of outputs (web, text file, graphical). I couldn’t get the graphical output to work sometimes (probably my list is too large). I also would have liked to do the list the other way–to have the list of my genes and have the terms associated with them. I haven’t figured out if there is a way to do that so far.
I’m not going to draw many conclusions from this yet–I want to try a variety of tools and think about the features and the quality of the results. But this tool seemed to effectively group my genes into buckets with GO terms that could be helpful for an analysis.
Check out their paper for more details:
Zheng Q, Wang XJ. Nucleic Acids Res. 2008 May 16. GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis. PMID: 18487275
If you are using cow or chicken microarrays–or intend to–you might want to participate in this survey from AgBase (described below). If you expect to need to use the databases, it is nice to help them out when they need input–it benefits you by influencing what they will focus on. This can aid your research later.
I’ll post the letter that came across the GO-Friends mailing list, which encouraged people to spread the word:
We are currently providing functional annotation (GO) for gene products represented on chicken & cow arrays. To prioritize our efforts, we would like know which arrays these communities are currently using.
You can help us by completing the polls found here: Chicken Array Usage
Bovine Array Usage http://doodle.ch/participation.html?pollId=ezwu46625934bzk4
These polls contain arrays in the Gene Expression Omnibus (GEO) Database.
If the array you are using is not represented, please tell us by adding a comment underneath on the page.
(If you are uncomfortable with adding your name, please feel free to use initials or etc.)
Please help by passing this email on to your colleagues using arrays who are not members of this newsgroup.
Help them out if you have some thoughts on this. Spread the word if you know researchers in these fields who would benefit.