Question: Detection of genes expressed above background for Gene ST Arrays (as opposed to Exon ST Arrays)
2
gravatar for komal.rathi
4.7 years ago by
komal.rathi3.4k
Children's Hospital of Philadelphia, Philadelphia, PA
komal.rathi3.4k wrote:

I have worked on a lot of Gene Chips and used several methods to define genes that make up the background (genes that are not expressed):

1. filter out genes where mean expression is below mean expression of eset (normalized expression set)

2. filter out genes where expression is below mean expression of eset in 50% or 80% of samples,

3. filter out genes where expression is below mean expression of eset in 50% or 80% of either cases or controls etc. 

4. Use the mean expression of the antigenomic probes (which are considered to be background) as a cutoff for main probes (real genes)

But I don't know which is the best way to go about detecting genes that are expressed above background (or to define genes that make up the background, for that matter). I know there is a function paCalls() in the oligo package for exon level expression but are there are any functions that could do the same thing for gene level expression? Some function that would give you a p-value at gene-level as opposed to at exon-level as in the paCalls() function. Any suggestions would be appreciated. 

ADD COMMENTlink modified 4.5 years ago by Sean Davis25k • written 4.7 years ago by komal.rathi3.4k
1
gravatar for Sean Davis
4.5 years ago by
Sean Davis25k
National Institutes of Health, Bethesda, MD
Sean Davis25k wrote:

Have a look at:

http://barcode.luhs.org/

The paper is here:

http://nar.oxfordjournals.org/content/42/D1/D938.full

The method is available in the Bioconductor fRMA package.

ADD COMMENTlink modified 4.5 years ago • written 4.5 years ago by Sean Davis25k

This looks promising. I will definitely read the paper and give it a try! Thanks!

ADD REPLYlink written 4.5 years ago by komal.rathi3.4k

I didn't answer your other questions as directly.  For non-specific filtering, you are probably best just as well of using variance as a threshold (probably better) rather than using some arbitrary proportion of expressed genes.

ADD REPLYlink written 4.5 years ago by Sean Davis25k
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