[BioC] limma: print-tip loess and empty spots

[Keith Satterley]

Hi Adrian

When you are using limmaGUI you can specify a set of parameters under the Linear 
Model Menu, either as A-B or B-A, which reverses the Fold Change sign in the 
TopTable. For example, My test Targets file is:
SlideNumber	FileName	Cy3	Cy5	Date
1	        slide1.gpr	B	A	11/07/2004
2	        slide2.gpr	B	A	11/07/2004
3	        slide3.gpr	B	A	11/07/2004
4	        slide4.gpr	B	A	11/07/2004
5	        slide5.gpr	B	A	11/07/2004
6	        slide6.gpr	B	A	11/07/2004

If my parameterisation is B minus A, The first two lines in my TopTable for the 
relevant columns are:
"Name"          "logFC"         "AveExpr"   "t"
"AA668821"	"-5.931"	"11.36"	    "-52.24"
"H87471"	"5.258"	        "10.52"	    "40.8"
whereas if my parameterisation is A minus B,  The first two lines in my TopTable 
for the relevant columns are:
"Name"          "logFC"         "AveExpr"   "t"
AA668821"	"5.931" 	"11.36"	    "52.24"
"H87471"	"-5.258"	"10.52"	    "-40.8

The LogFC values are reversed in sign.

Is this helpful, or is your problem something different?

I'm using R2.5.0, limma 2.10.4 and affylmGUI 1.12.0 on Windows for this test 
problem,

cheers,

Keith Satterley
===================
Maintainer:limmaGUI
Bioinformatics Division
The Walter and Eliza Hall Institute of Medical Research
Parkville, Melbourne,
Victoria, Australia
=======================

Adrian Steward wrote:
> Thank you Dr. Smyth.
> 
> Having processed some raw data in limma, I am seeing something peculiar.  I
> used Cy5 as reference and Cy3 as target, on the Axon platform using Gene Pix
> Pro (latest version) to produce genepix results files.
> 
> Using Limma GUI, regardless of what I set the 'targets' file to indicate, my
> raw log ratio data output always come out from limma as the opposite sign
> than it should be; in other words, what should be negative is positive, and
> vice versa.  I know I set the calculation 532/635 correctly in Genepix.
> 
> Is there something that I am missing?
> 
> Thanks,
> 
> Adrian
> 
> On 5/22/07, Gordon K Smyth <smyth at wehi.edu.au> wrote:
>> Dear Adrian,
>>
>> I assume that you're already read the limma User's Guide advice:
>>
>> "Print-tip loess is also unreliable for small arrays with less than, say,
>> 150 spots per print-tip
>> group. Even larger arrays may have particular print-tip groups which are
>> too small for printtip
>> loess normalization if the number of spots with non-missing M-values is
>> small for one or more of
>> the print-tip groups. In these cases one should either use global "loess"
>> normalization or else
>> use robust spline normalization"
>>
>> There are however special considerations for multispecies arrays, see
>>
>> Gilad, Y., Oshlack, A., Smyth, G. K., Speed, T. P., and White, K. P.
>> (2006). Expression profiling
>> in primates reveals a rapid evolution of human transcription factors.
>> Nature 440, 242-245.
>>
>> Oshlack, A., Smyth, G. K., and Gilad, Y. (2007). Using DNA microarrays to
>> study gene expression in
>> closely related species. Bioinformatics. (Published online 23 March 2007).
>>
>> and perhaps
>>
>> Oshlack, A., Emslie, D., Corcoran, L., and Smyth, G. K. (2007).
>> Normalization of boutique
>> two-color microarrays with a high proportion of differentially expressed
>> probes. Genome Biology 8,
>> R2.
>>
>> Best wishes
>> Gordon
>>
>> ------------- original message ----------------
>> Adrian Steward adrian.steward0405 at gmail.com
>> Mon May 21 19:52:56 CEST 2007
>>
>> Hi all,
>>
>> I am using the limma package to analyze a multi-species cDNA array,
>> 2-colour
>> reference design.  The problem is that because it is a multi-species (and
>> tissue) array, and I am querying only 1 tissue, only 1/3 of the 15,000
>> spots
>> appear to correspond to cDNA in my samples, and the number of spots that
>> actually get tested is around 3,500.  These spots are rather randomly
>> located across the slides because of many libraries used in construction
>> of
>> the array.
>>
>> Before I get too far into my analysis, I read in the limma guide that
>> print-tip loess within-slide normalization is not always a good choice for
>> data with 'small' print tip groups.  I am assuming that a global loess
>> normalization is the more appropriate approach in my case.
>>
>> Is my assumption reasonable?
>>
>> With thanks
>>
>> Adrian M.
>>
>>
>> PS - I'm running R 2.3.1, limma 2.7.3, and limma GUI version 1.8.1
>>
>>
> 
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