[BioC] ANOVA p value calculation

[Adaikalavan Ramasamy]

Assumin that columns 1-3 represents the first cell line, columns 4-6 
represents second cell line etc, then you can try something like

  cellline <- factor( paste("type_", rep(1:17, each=3), sep="") )
  apply( Data, 2, function(gene) anova(lm(gene ~ cellline))$"Pr(>F)"[1] )

However, in the context of microarray experiements, it is far better to 
use the functions in limma package.

Regards, Adai



Sean Davis wrote:
> On Wed, Mar 11, 2009 at 1:19 PM, Antony <gasparj at uni-koeln.de> wrote:
> 
>> Dear Sir/Madam,
>>
>> I wish to do ANOVA p value computation with Bioconductor.
>>
> 
> You might want to look at the limma package, though there are a number of
> others.
> 
> 
>> I have RMA normalized dataset in tab delimited text.
>>
>> Data<-read.table("RMA-normalized.txt",row.names=1,sep="\t",header=TRUE,dec
>> = ".",as.is =TRUE,na.strings = "NA",
>>                colClasses = NA,check.names = FALSE,strip.white = FALSE,
>> blank.lines.skip = TRUE,
>>                allowEscapes = FALSE, flush = FALSE,encoding = "unknown")
>>
>> dim(Data)
>> [1] 31528    51
>>
>> 17 * 3 = 51 There are 17 different cell line type samples with 3 biological
>> replicates.
>>
>> I wish to do ANOVA - p value calculation for finding out the differentially
>> expressed genes.
>>
>> Kindly help me out to use the right Bioconductor package. Using multtest
>> package I tried to do F stat but could not. When I try
>> the R console window goes off. Could be due to many number of couloumns?.
>>
> 
> You'll probably need to read the posting guide to get a bit better help.  In
> particular, you would need to provide at least your code and the output,
> error messages, and sessionInfo().
> 
> 
>> Please help me out to find a solution.
>>
>> Thanking you in advance,
>>
>>
>> With kind regards,
>> antony
>>
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