[BioC] help

[James MacDonald]

I believe the main problem is that you switch your variable name from a
to b without carrying anything over. Maybe something like this would
work?

a <-is.na(M.object)
zero <- apply(a,1,sum) == 0

Then continue on from there.

HTH,

Jim



James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623

>>> Michael Stapelberg <msberg at med.usyd.edu.au> 07/08/04 11:00PM >>>
Hi,

I hope someone can help me out.

I am using Bioconductor and limma to examine my microarrat data. What I
 
am trying to do is eliminate any spots that have an NA between arrays 

before applying the design matrix in limma and applying the eBayes  
function. Even after I have  done this elimination process and have  
checked it, by having a look at the M values of the top genes in the  
topTable list, some of the genes still have an NA value for one array, 

but designated M values for the rest of the arrays in the group.

This is what I am typing into the workspace after normalisation and  
scalenormalisation:

A.object<-maA(objectscalenormalisation)
M.object<-maM(objectscalenormalisation)
Library(limma)
a<-is.na(M.object)
a<-apply(a,1,sum)
b[b==0]
which[b==0]
zero<-which(b==0)
x<- 
list(A=maA(objectscalenormalisation)[zero,],M=maM(objectscalenormalisati

on)[zero,]
x.lmFit<-lmFit(x,c(1,-1,1,-1))
x.lmFit.Bayes<-eBayes(x.lmFit)
plot(x.lmFit.Bayes$coef,x.lmFit.Bayes$lods)
topTable(x.lmFit.Bayes,n=100)
On Wednesday, July 7, 2004, at 04:15  PM, James Wettenhall wrote:

Why might this not be working ?


Michael.