[BioC] Interspecies differential expression of orthologs with Edger

[Gordon K Smyth]

That doesn't look helpful to me.  I suggested that you incorporate gene 
lengths into the offsets, not do quantile normalization of cpms.

Sorry, I just don't have time to develop a code example for you.  I hope 
someone else will help.

The whole topic of interspecies differential expression is a can of worms. 
Even if you adjust for gene length, there will still be differences in gc 
content and mappability between the species.

Gordon


On Wed, 27 Aug 2014, assaf www wrote:

> Dear Gordon thanks,
>
> Suppose I start with the following matrices:
>
> # 'counts' is the Rsem filtered counts
>> counts[1:4,]
>                     h0  h1  h2  n0  n1  n2
> ENSRNOG00000000021   36  17  20  10  25  38
> ENSRNOG00000000024 1283 615 731 644 807 991
> ENSRNOG00000000028   26  12  11  18  23  28
> ENSRNOG00000000029   22  13  12  16  17  15
>
> # 'geneLength' is the species-specific gene lengths, for species 'h' and
> 'n':
>> geneLength[1:3,]
>                   h0.length h1.length h2.length n0.length n1.length
> n2.length
> ENSRNOG00000000021      1200      1200      1200      1303      1303
> 1303
> ENSRNOG00000000024      1050      1050      1050      3080      3080
> 3080
> ENSRNOG00000000028      1047      1047      1047      1121      1121
> 1121
>
>
> does the following code look correct, and may allow allows across species
> analysis ?:
> (technically it works, I checked)
>
> # quantile normalization: (as in here:
> http://davetang.org/wiki/tiki-index.php?page=Analysing+digital+gene+expression
> )
>
> x1 = counts*1000/geneLength
> library(limma)
> x2 = normalizeBetweenArrays(data.matrix(x1),method="quantile")
> offset = log(counts+0.1)-log(x2+0.1)
>
> ...
>
> y <- estimateGLMCommonDisp(y,design,offset=offset)
> y <- estimateGLMTrendedDisp(y,design,offset=offset)
> y <- estimateGLMTagwiseDisp(y,design,offset=offset)
> fit <- glmFit(y,design,offset=offset)
>
> ...
>
>
> Thanks in advance for any help..,
> Assaf
>

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