[BioC] Re: affy expression values

[Rafael A. Irizarry]

dear larry,

I hope laurent's note was helpful, here are some further thoughts. 

there are two things here: 1) the R package and 2) the expression measure. 
The  expression measures is described in a paper (to appear in 
biostatistics) that you can download from 
http://www.biostat.jhsph.edu/~ririzarr/papers/index.html

with the R package you can do anything you want. RMA (our meausre) is 
the default but there are many (infinite) options. if you are concerned 
about the use of multi-chip analysis you can easily 
alter the express function in the package as laurent pointed out. you can, 
for example, use apply(x,2,median) instead of median polish. this will 
make it chip indenpendent. you can also use normalization procedures that 
dont depend heavily on multiple chips. scaling for example.

some collaborators and myself, are currently writing a manuscript of the 
advantages of multichip analysis. keep your eyes open for that.

rafael




On Mon, 29 Jul 
2002, Larry wrote:

> Greetings Dr. Irizarry and Dr. Gautier,
> 
> I have a question regarding the affy procedures that I am hoping you can help me with.   I am in the process of exploring use of affy analysis as an alternative to using the Affymetrix expression values and in doing so I am trying to understand the process for generating expression values. Specifically, the medianpolish default procedure used by the express function.  
> 
> As I understand it, in calculating expression values for multiple chips,  medianpolish does not treat the chips independently. It runs through this process of removing row and column medians for all the chips then generates an overall value for all the chips with corrections for each chip.  The expression value generated is then calculated from these two values.  Does this then mean that I should expect different results depending on the number of chips I am analyzing? 
> 
>  For example, I've run a subset of data through the process, using chips hybridized with extract from untreated cells and cells exposed to various treatment.  I then analyzed the cells using 2 chips, 3 chips, 4 chips and 5 chips (ie. untreated + 1-4 treatments), and the results I obtained were different each time.  Below is the values generated for 10 genes in for the untreated condition only.
> 
>      gene 2 chips 3chips 4chips 5chips 
>       untreated 203307_at 8.47863 8.42976 8.213314 8.44459 
>      205793_x_at 9.063024 9.022368 8.84279 9.022368 
>      209168_at 7.840245 7.743475 7.584038 7.817369 
>      210260_s_at 10.42869 10.37537 10.02658 10.42127 
>      210373_at 8.373434 8.366322 8.076776 8.366322 
>      214692_s_at 8.729106 8.765005 8.457484 8.769177 
>      215294_s_at 6.884695 6.95363 6.691277 6.849249 
>      216017_s_at 8.90209 8.637539 8.472341 8.830136 
>      217431_x_at 7.288174 7.246028 6.960451 7.288174 
>      59437_at 7.960958 8.008521 7.547648 7.834895 
> 
> 
> I recognize that the values don't vary greatly, but I am concerned that having a treatment that causes profound effects to expression of certain genes may affect my results considerably  (with respect to not having had done that treatment).  
> 
> 
> I hope my question is clear and would very much appreciate your comments on this.
> 
> Regards
> Larry Heisler
> Dept of Laboratory Medicine and Pathobiology
> Program in Proteomics and Pathobiology
> University of Toronto
> Toronto, Ontario Canada
> l.heisler@rogers.com
> 
> 
>