[BioC] Normalization for different amts of RNA in limma
Naomi Altman
naomi at stat.psu.edu
Sun May 16 17:39:36 CEST 2004
Here is my go at it:
1. The biggest worry is that in the more intense sample there will be more
saturation. The level of differential expression cannot be determined from
the saturated spots.
2. If differential expression is really a ratio, then the amount of RNA in
the sample should not affect measures of differential expression - i.e.
(10R/10G)=R/G. Clearly the ratio idea is not exact, but taking logarithms
before doing the analysis is based on this idea.
3. If you are using ANOVA or limma to do the computations, if (2) is
correct and if you have an array effect in your model, your measures of
differential expression should be OK. Alternatively, you could put "RNA
amount" as a factor in the model and you should be OK.
4. I agree that you should normalize between arrays. I am not very
familiar with the limma routines - you will want to normalize both the mean
and the variance. Normalizing the variance should help reduce effects due
to the amount of RNA in the sample.
5. If you are using an analysis that does not involve taking the
difference in logarithms, points 2-4 will not help you. In that case, you
need to know the relationship between amount in the sample and
hybridization intensity.
--Naomi
At 05:04 PM 5/10/2004, Helen Cattan wrote:
>
>Hi all,
>
>Firstly thanks for all the help in the past!
>
>Now, I have biological replicate arrays for which different amounts of
>RNA have been used (3 micrograms and 4 micrograms). So a fairly big
>difference of over 30%.
>
>I am performing normalizeWithinArrays and then normalizeBetweenArrays in
>limma. The between array normalization is necessary since the arrays
>were scanned at different PMT settings (both in the linear scale) but I
>also need to normalize for the different amounts of RNA if this is
>possible. I imagine that the relationship between the amount of RNA
>added to a slide and the amount that hybridizes to the array is not a
>linear relationship, probably sigmoidal but I haven't tested this. If
>this is so, would normalizeBetweenArrays account for this? Is there a
>different type of normalization that would? Or could I transform the
>data in some way so that it would work for both different RNA amounts
>and different scanning settings?
>
>
>
>
> [[alternative HTML version deleted]]
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
Naomi S. Altman 814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics 814-863-7114 (fax)
Penn State University 814-865-1348 (Statistics)
University Park, PA 16802-2111
More information about the Bioconductor
mailing list