[BioC] kOverA(k, A=100, na.rm=TRUE)

[Robert Gentleman]

Hi,
  That behavior seems somewhat unusual.
Could you perhaps see which genes are selected for
kOverA(2,7) and which for kOverA(2,6)?  And then look at the expression 
values to see what might be going on..

Also please include the output of sessionInfo, as requested in the 
posting guide.

  Robert


Roberts, Raymond wrote:
> Dear List,
> 
>  
> 
> I'm using genefilter and Limma to analyze the human exon array.  I did
> my preprocessing with aroma.affymetrix and then loaded it into limma and
> used genefilter to isolate the significant genes.  At least that is what
> I think I am doing.  Here is my script starting at the function I have
> the question about
> 
>  
> 
>  
> 
> ##Filter for differentialy expressed genes
> 
> f1<-kOverA(2,7)
> 
> ffun<-filterfun(f1)
> 
> which<-genefilter(exprs(RMASet), ffun)
> 
> rma_no<-summary(which)
> 
> rmafiltset<-RMASet[which,]
> 
>  
> 
>  
> 
>  
> 
> grps <- paste(pData(rmafiltset)$hours)
> 
> lev <- c("time0", "time3", "time6", "time12", "time24", "time48")
> 
> f <- factor(grps, levels = lev)
> 
> design <- model.matrix(~ 0 + f)
> 
> colnames(design) <- lev
> 
> rmafit <- lmFit(rmafiltset, design)
> 
>  
> 
>  
> 
>  
> 
> contrast.matrix <- makeContrasts("time3-time0", "time6-time3",
> "time12-time6", "time24-time12", "time48-time24", "time6-time0",
> "time12-time0", "time24-time0", "time48-time0", levels=design)
> 
> rmafit2 <- contrasts.fit(rmafit, contrast.matrix)
> 
> rmafit3 <- eBayes(rmafit2)
> 
>  
> 
>  
> 
> pval<-0.05
> 
> l2foldch<-  0.58496250072
> 
>  
> 
> rmaresults<-decideTests(rmafit3, p.value=pval, lfc=l2foldch)
> 
>  
> 
>  
> 
> rmalist1 <- rmaresults[,1]!=0
> 
> rmalist2 <- rmaresults[,2]!=0
> 
> rmalist3 <- rmaresults[,3]!=0
> 
> rmalist4 <- rmaresults[,4]!=0
> 
> rmalist5 <- rmaresults[,5]!=0
> 
> rmalist6 <- rmaresults[,6]!=0
> 
> rmalist7 <- rmaresults[,7]!=0
> 
> rmalist8 <- rmaresults[,8]!=0
> 
> rmalist9 <- rmaresults[,9]!=0
> 
>  
> 
> rmagroup1 <- rmafiltset[rmalist1,]
> 
> rmagroup2 <- rmafiltset[rmalist2,]
> 
> rmagroup3 <- rmafiltset[rmalist3,]
> 
> rmagroup4 <- rmafiltset[rmalist4,]
> 
> rmagroup5 <- rmafiltset[rmalist5,]
> 
> rmagroup6 <- rmafiltset[rmalist6,]
> 
> rmagroup7 <- rmafiltset[rmalist7,]
> 
> rmagroup8 <- rmafiltset[rmalist8,]
> 
> rmagroup9 <- rmafiltset[rmalist9,]
> 
>  
> 
> rmaglist1 <- featureNames(rmagroup1)
> 
> rmaglist2 <- featureNames(rmagroup2)
> 
> rmaglist3 <- featureNames(rmagroup3)
> 
> rmaglist4 <- featureNames(rmagroup4)
> 
> rmaglist5 <- featureNames(rmagroup5)
> 
> rmaglist6 <- featureNames(rmagroup6)
> 
> rmaglist7 <- featureNames(rmagroup7)
> 
> rmaglist8 <- featureNames(rmagroup8)
> 
> rmaglist9 <- featureNames(rmagroup9)
> 
>  
> 
> rmaunion <- union(rmaglist1, union(rmaglist2, union(rmaglist3,
> union(rmaglist4, union(rmaglist5, union(rmaglist6, union(rmaglist7,
> union(rmaglist8, rmaglist9))))))))
> 
>  
> 
> rmaunionset <- rmafiltset[rmaunion,]
> 
>  
> 
> plotdata2 <- exprs(rmaunionset)
> 
> colnames(plotdata2) <- paste(pData(RMASet)$label)
> 
>  
> 
>  
> 
> I go on to create a heatmap and html output of significant genes.   My
> problem is that when I change kOverA(2, 7) to, say, kOverA(2, 6), I get
> fewer genes, I thought this should increase the number of genes I'm
> seeing in the final output.  If I increase from 7 to 8 I still get a
> shorter list.  It seems like 7 is the value that generates the maximum
> output.  If anyone could explain why this is happening I would really
> appreciate it.   If I should post more information please just let me
> know.
> 
>  
> 
>  
> 
> Ray Roberts
> 
>  
> 
> Lovelace Respiratory Research Institute
> 
>  
> 
> 
> 	[[alternative HTML version deleted]]
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
> 

-- 
Robert Gentleman, PhD
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M2-B876
PO Box 19024
Seattle, Washington 98109-1024
206-667-7700
rgentlem at fhcrc.org