Entering edit mode
Dear Noah,
Only one level of duplication can be handled using the
duplicateCorrelation() technique. I
suggest that you average over the most highly correlated duplicate
level, which is the
side-by-side, then use duplicateCorrelation() for the top and bottom
half. E.g.,
MA2 <- avedups(MA,ndups=2,spacing=1)
corfit <-
duplicateCorrelation(MA2,design,ndups=2,spacing="topbottom")
fit <-
lmFit(MA2,design,ndups=2,spacing="topbottom",cor=corfit$consensus)
etc
Best wishes
Gordon
> Date: Mon, 09 Oct 2006 18:12:53 -0500
> From: "Noah Cohen" <ncohen at="" cvm.tamu.edu="">
> Subject: [BioC] cDNA array with 2 levels of duplication
> Content-Type: text/plain
>
> Hi - I am looking for help with how to account for duplication at 2
> levels in analysis using lmFit in limma of data from a 2-channel
cDNA
> microarray (for which ImaGene software was used for analysis). The
> array is a 4 x 4 block of 24 rows x 24 columns of spots. The array>
has
> been duplicated on the top half and the bottom half of the slide.
> Furthermore, the spots themselves have been duplicated side-by-side.
> Thus, each slide has 4 replications of the same EST, occuring in 2
> adjacent pairs that are equally separated. My reading of the limma
> vignette and elsewhere on within-array duplicate spots hasn't
yielded a
> solution. I've tried using the ndups options in lmFit and
> duplicateCorrelation. While I have been successful with accounting
for
> duplicate spots, I haven't been able to find a solution for the
> replication of the arrays on the same slide, where each array has
> within-array replication.
>
> Does anyone have any experience or advice? Thanks - Noah Cohen
>
>
> Noah D. Cohen, VMD, MPH, PhD, DACVIM
> Professor
> Department of Large Animal Clinical Sciences
> College of Veterinary Medicine and Biomedical Sciences
> Texas A&M University
> College Station, Texas 77843-4475
> Telephone: 979-845-3541
> Fax: 979-847-8863
> e-mail: ncohen at cvm.tamu.edu