[BioC] NormalizeBetweenArrays

Jason Skelton jps at sanger.ac.uk
Thu Mar 11 12:43:02 MET 2004


Gordon Smyth wrote:

>
> This isn't built-in to limma but it is easy to do using the subset and 
> cbind operations defined for MAList objects. Suppose that 'design' is 
> the matrix you give above and 'MA' is your within-array normalized 
> data object.

Thankyou very much for this Gordon this is exactly what I wanted......
On a different note

since I changed to newer version of limma (1.5.1)
I receive the following message when I run dupcor.series or 
duplicateCorrelation

duplicateCorrelation(object,design=rep(1,ncol(M)),ndups=2,spacing=1,trim=0.15,weights=NULL)
dupcor.series(M,design=rep(1,ncol(M)),ndups=2,spacing=1,initial=0.8,trim=0.15,weights=NULL)


> NBAScaleMULTIcor <- dupcor.series(NBAScaleMULTI$M, SchistodesignMATRIX, ndups=2, spacing=544)

There were 12 warnings (use warnings() to see them)
 > warnings()
Warning messages:
1: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
2: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
3: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
4: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
5: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
6: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
7: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
8: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
9: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
10: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
11: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))
12: Max iterations exceeded in: glmgam.fit(dx, dy, start = c(mean(dy), 0))

Any ideas ?

cheers

Jason

-- 
--------------------------------
Jason Skelton
Pathogen Microarrays
Wellcome Trust Sanger Institute
Hinxton
Cambridge
CB10 1SA

Tel +44(0)1223 834244 Ext 7123
Fax +44(0)1223 494919



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