TAMALPAIS and promoter arrays

TAMALPAIS NimbleGen Promoter Arrays Array Analysis Problems Mark Bieda

I’ve been receiving some questions on TAMALPAIS usage for promoter arrays via email.

On the TAMALPAIS website, I say “Do not use this for promoter arrays.

This is actually not quite true; there are a limited number of cases in which TAMALPAIS will perform well for promoter arrays. In this post, I discuss this.

When TAMALPAIS is ok for promoter arrays:
In short:
1. If your factor only binds to a tiny portion of the promoters (<5%), then TAMALPAIS will perform ok.
2. More correct – and important – if only a small number of probes on the array are within binding sites for your factor, then you are ok. So: for promoter array designs with long promoters, you might have 15% of the promoters with a binding site. But only a small number of probes in the binding sites. (Hopefully this makes sense.)

Why do I say “Do not use TAMALPAIS for promoter arrays”?
If you have a factor that binds to (or exists in) a lot of promoter regions – like POLII or some histone modifications – then TAMALPAIS will give you bad results. I don’t want that to happen. Right now, study of histone mods and POLII are a big deal, so I don’t want people to be unhappy.

If not TAMALPAIS, then what?
There are a number of options. I developed maxfour to score promoters (see Krig et al. 2007 in JBC). I will be releasing an easy to use version of this software by the fall 2008 (planned, not a promise). This is really the best option with NimbleGen’s current crop of designs, in my opinion. Someone else may have some great promoter array analysis software; I’m not aware of this right now – feel free to email me or leave comments. I don’t mean to be unfair to other bioinformaticians with this.

What about the promoter array analysis server?
Ah, yes. This does very limited analysis – see my post on it in this blog (click the promoter array category button on the sidepanel).

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