[BioC] comparison of two sets of developmental study

[Yan Zhou]

Steve,

Thank you for your suggestions. For my developmental data, the time 
between each stage are not measureable. I do know the sequence of 
development, but don't know the time it takes to go from stage 1 to 2, 
or 2 to 3 and so on. Can I still treat it like time course data?

You suggestions about the cor.test is pretty smart. I'll try that.

Thank you.

Yan

Steve Lianoglou wrote:

>Hi,
>
>On Mon, Apr 19, 2010 at 10:54 AM, Yan Zhou <Yan.Zhou at fccc.edu> wrote:
>  
>
>>Hi, Steve,
>>
>>Thank you for your reply. Sorry that I didn't make it clear. My interests
>>are two layers:
>>
>>1. Genes changing along development in tissue A  and B seperately; More
>>precisely, genes change in A along development; Same as in tissure B;
>>    
>>
>
>It sounds like you want to call genes that are differentially
>expressed along your time series.
>
>You can use limma for that, but there are also several BioC packages
>that specifically deal with timecourse data, such as:
>
>* maSigPro: http://bioconductor.org/packages/2.5/bioc/html/maSigPro.html
>and http://bioinformatics.oxfordjournals.org/cgi/content/full/22/9/1096
>
>* betr: http://bioconductor.org/packages/2.5/bioc/html/betr.html
>
>The vignettes that accompany them have references to publications you
>can read to figure out what others are doing.
>
>  
>
>>2. Anti-correlated expression patterns as you mentioned in the two tissues
>>in order to find key players which drive the two development differently.
>>    
>>
>
>Assuming you have expr.a, and expr.b, which are the normalized
>expression datasets (rows=genes, cols=times) for tissue a and b,
>respectively, I reckon you can simply run cor.test along each row-pair
>from the two matrices and look for highly negative correlation
>coefficients w/ significant p.values as a start, no? For example:
>
>R> cors <- lapply(1:nrow(expr.a), function(i) {
>  cor.test(expr.a[i,], expr.b[i,])
>})
>R> interesting <- which(sapply(cors, function(x) x$p.value < 0.05 &&
>x$estimate < 0))
>
>`interesting` will have the indices of rows in the expression matrix
>that have uncorrected p-values < 0.05 and are negative.
>
>-steve
>
>  
>