[BioC] Variance

[David martin]

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
>>
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