[BioC] Variance

[john seers (IFR)]

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

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