[BioC] maanova background correction

[James MacDonald]

I think you have come across a relatively contentious issue, and I doubt
you will be able to get a consensus about background subtraction.
Additionally, each software/scanner uses a different method of
estimating background, so the usefulness of the background is largely
dependent on how it was estimated.

Personally, I look at background subtraction the same way I look at the
MM probes on an Affy chip. I am sure there is a reasonable way to use
these data, but I am not too sure that simply subtracting background
from foreground is a good idea. For instance, background is usually
estimated from portions of the slide that are blocked with something
other than cDNA. Anybody that has ever looked at a slide with negative
control cDNA spots can tell you that the intensity of the negative
control is almost always much smaller than background. In my opinion,
this indicates that the estimated background almost always overestimates
true background.

In addition, variability is additive, so if you subtract background
from foreground, you are adding the variability of your background
estimate to your new foreground estimate. Considering the inherent
variability of microarray data, this cannot be considered a good thing.

On the other hand, if you don't subtract background (or some ad hoc
estimate thereof), your data will be (possibly) upwardly biased.

So here is what I do; I simply use the raw signal and accept that the
data may be biased. This is certainly not the ideal situation, but I
think it is a reasonable trade off of bias for (hopefully) better
precision.

HTH,

Jim



James W. MacDonald
UMCCC Microarray Core Facility
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623

>>> "Brendan M. Heavey" <bmheavey at buffalo.edu> 06/24/03 02:56PM >>>
Hello-

I am using MAANOVA to analyze cDNA chips.  Does anybody know how to 
deal with background spot intensity?

Right now, I have about 4000 genes on an array, each spotted 3 times. 

I can input the raw signal strength for each of the 12,000 spots and 
run analysis on those.

I would like to subtract background intensity from each of the spots, 
but this leads to negative values in some spots (that haven't 
hybridized).  Maanova seems to not like negatives or missing values, 
which means I have to eliminate all 3 spots for each gene that produces

a single negative...which reduces my dataset to a pitiful number of 
genes.

I've considered:
1). Replacing the missing/negative value with a number very close to 
zero
2). Replacing the missing/negative value with the average of the other

two spots
3). Forgetting about background intensity completely and just using raw

signal strength

...but none of them seem like the right thing to do

any ideas?

thanks in advance

Brendan Heavey
Analyst Programmer
Center for Research in Cardiovascular Medicine
University at Buffalo

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