[BioC] Input regarding sorting out candidate genes from edgeR results

[Steve Lianoglou]

Hi,

Comments in line:

On Mon, Mar 10, 2014 at 11:07 AM, Sindre Lee <sindre.lee at studmed.uio.no> wrote:
> Hi!
> I have been asked to make a candidate list of genes for downstream analysis.
> We are going to look for secreted proteins into plasma from muscle tissue. I
> started by picking out genes coding for secretory proteins.

Good start.

> Then I sorted by fold change

Fold change between what types of samples?

> and prediction score

What's a prediction score?

>, but then I started
> wondering what actually gives a huge fold change,

What did you come up with?

> and now Im not so sure if
> this is the best approach?

What concerns do you have?

> Do anyone here have experience with this and have
> some good ideas? Maybe run GSEA,

Well, you've already defined a list of secreted proteins relevant to
your sample, you can use that gene set and test for enrichment using,
eg. camera or roast.

> cluster genes with same expression profile

What patterns would be interesting to you?

> etc?

yes, perhaps.

> The reason I ask is to try and save money spent on ELISA kits.

I think you need to provide more detail regarding what you're trying
to study and what data you have to do that with.

Is purifying the plasma and running MS on it to identify proteins of
interest not a viable option? Is it too expensive? How much is your
time worth?

-- 
Steve Lianoglou
Computational Biologist
Genentech