Question: LIMMA help: how to choose correct weight for flagged spots??
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gravatar for daniela.marconi@libero.it
13.7 years ago by
Hi limma users!!! Does anyone know why and how a different weight value for flagged spot vastly influence significance levels(for both p-value and log odds) and order in topTable() list? I flagged spot with a self-made script for genePix(taking into acconunt some quality parameter like Signal to noise ratio and so on...) After I've used different values as weight (in wtflags(): 1, 0, 0.1, 0.5, 0.01) obtaining really different results. For example with 0 and 1 ...I obtained no significant adjusted p-values (P>=0.05) For Weight=0.01 I obtained very signhificant P-value: for more or less 300 genes in the topTable list I have P-value in the range of E-20 to E-10 I'm wondering what is the correct choice for weights? Thanks for any help and suggestion Daniela PS: (Below I attached my R script in wich the only change is in read.maimages(...,wt.fun=wtflag(???)) Marconi Daniela Phd Student Bologna University Physics Department Viale Berti P. 6/2 40137 Bologna tel: +39 0512095136 e-mail: daniela.marconi at bo.infn.it ########Reading data >library(limma) >memory.limit(4000) >Targets<-readTargets() >RG<-read.maimages(Targets$file.name,source="genepix",wt.fun=wtflags(0 .01)) >RG$printer<-getLayout(RG$genes) >MA<-normalizeWithinArrays(RG,bc.method="minimum") >MAlast<-normalizeBetweenArrays(MA,method="quantile") >MAlast$targets<-Targets >Targets 1 013.gpr nsM linf B 2 015.gpr UM linf B 3 018.gpr UM linf B 4 021.gpr UM linf B 5 022.gpr UM linf B 6 032.gpr UM linf B 7 039.gpr UM linf B 8 047.gpr UM linf B 9 049.gpr nsM linf B 10 067.gpr sM linf B 11 068.gpr nsM linf B 12 079.gpr sM linf B 13 080.gpr nsM linf B 14 098.gpr sM linf B 15 107.gpr sM linf B 16 119.gpr UM linf B 17 127.gpr sM linf B 18 128.gpr UM linf B 19 129.gpr nsM linf B 20 149.gpr UM linf B 21 164.gpr nsM linf B 22 181.gpr sM linf B 23 185.gpr sM linf B 24 186.gpr sM linf B 25 188.gpr nsM linf B 26 191.gpr UM linf B 27 195.gpr UM linf B 28 245.gpr UM linf B 29 257.gpr sM linf B 30 258.gpr nsM linf B 31 286.gpr nsM linf B 32 287.gpr sM linf B 33 288.gpr nsM linf B 34 304.gpr nsM linf B 35 305.gpr sM linf B 36 313.gpr nsM linf B 37 316.gpr sM linf B 38 318.gpr sM linf B 39 320.gpr sM linf B 40 323.gpr nsM linf B 41 325.gpr sM linf B 42 326.gpr nsM linf B 43 328.gpr UM linf B 44 329.gpr sM linf B 45 331.gpr UM linf B 46 332.gpr sM linf B 47 334.gpr sM linf B 48 337.gpr sM linf B 49 338.gpr sM linf B 50 340.gpr sM linf B 51 344.gpr UM linf B 52 345.gpr UM linf B 53 346.gpr nsM linf B 54 354.gpr UM linf B 55 369.gpr nsM linf B 56 378.gpr nsM linf B 57 382.gpr nsM linf B ####################### ####################### LIMMA ####################### >group<-factor(c("M",rep("UM",7),"M","M","M","M","M",rep("M",2),"UM"," M","UM","M","UM","M", rep("M",3),"M",rep("UM",3),"M",rep("M",2),"M",rep("M",2),"M","M",rep(" M",3),"M","M","M", "UM","M","UM",rep("M",5),rep("UM",2),"M","UM",rep("M",3)),levels=c("UM ","M")) >design<-model.matrix(~0+group) >colnames(design)<-c("M","UM") >dupcor <- duplicateCorrelation(MAlast,design=design) >fitCOR <- lmFit(MAlast,ndup=2,correlation=dupcor$consensus.correlatio n,design=design,weights=RG$weights) >cont.matrix<-makeContrasts(UM.M=UM-M,levels=design) >fit2COR<-contrasts.fit(fitCOR,cont.matrix) >fit2COR<-eBayes(fit2COR) >result<-topTable(fit2COR,n=300,sort.by="P",adjust.method="fdr") >write.table(result,file="limmaUMvsMflag0.txt",quote = FALSE, row.names = FALSE,sep="\t")
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ADD COMMENTlink written 13.7 years ago by daniela.marconi@libero.it100
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