Thanks, One extra question, do i need to compute an extra test to make sure that the lowest variance is significant (pvalue ??)??? thanks john seers (IFR) wrote: > Hi David > > Ah, yes. which.min is better. > > For instance, type in > >> myvars[which.min(myvars)] > geneA > 0.18827 > > > Regards > > > John > > > > -----Original Message----- > From: bioconductor-bounces at stat.math.ethz.ch > [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of David > martin > Sent: 22 June 2009 15:41 > To: bioconductor at stat.math.ethz.ch > Subject: Re: [BioC] Variance > > Thanks, > It's working. > To get he min value i run > min = which.min(myvars) > However, how do I know the calculated variance ?? as which.min returns > the index but not the variance. > > thanks > > > john seers (IFR) wrote: >> Hi >> >> Something like this? >> >> >> geneA<-c(-6.19, -5.74, -5.82, -5, -5.59) >> geneB<-c(-6.33, -5.32, -5.6, -4.88, -5.39) >> geneC<-c(-6.15, -6.07, -5.6, -4.88, -5.9) >> geneD<-c(-6.57, -6.11, -6.36, -5.36, -5.96) >> geneD<-c(-6.74, -6.2, -5.49, -5.35, -5.95) >> geneE<-c(-6.75, -6.24, -5.73, -5.63, -6.02) >> >> >> mygenes<-rbind(geneA, geneB, geneC, geneD, geneE) >> colnames(mygenes)<-c("CondA", "CondB", "CondC", "CondD", >> "CondE") >> >> myvars<-apply(mygenes, 1, var) >> >> myvars[which(min(myvars) == myvars)] >> >> >> # geneA >> #0.18827 >> >> Note that this needs a matrix so you will need to convert your > dataframe >> to work. (See ?data.matrix). Also I think using the min command will > not >> always work to index the myvars, but it shows the idea. >> >> See ?plot for plotting. >> >> Regards >> >> J >> >> >> >> >> -----Original Message----- >> From: bioconductor-bounces at stat.math.ethz.ch >> [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of David >> martin >> Sent: 22 June 2009 13:56 >> To: bioconductor at stat.math.ethz.ch >> Subject: [BioC] Variance >> >> Hello, >> I'm newbie with R. >> I have a dataframe as follows. The microarray data has been normalized > >> using spike in controls and the values shown are normalized log2 > values. >> CondA CondB CondC CondD CondE >> geneA -6.19 -5.74 -5.82 -5 -5.59 >> geneB -6.33 -5.32 -5.6 -4.88 -5.39 >> geneC -6.15 -6.07 -5.6 -4.88 -5.9 >> geneD -6.57 -6.11 -6.36 -5.36 -5.96 >> geneD -6.74 -6.2 -5.49 -5.35 -5.95 >> geneE -6.75 -6.24 -5.73 -5.63 -6.02 >> >> From this small subset (in fact i have a larger dataframe) i would > like >> to know which gene has the lowest variance. I would like to see is > some >> of these genes could be used as reference genes for RT-PCr > experiments. >> How can i plot and get the variance from this genes and see what would > >> the best candidates to be used as reference genes. >> >> thanks, >> >> david >> >> _______________________________________________ >> 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 >> >> _______________________________________________ >> 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 > > _______________________________________________ > 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 > > _______________________________________________ > 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 >