[BioC] poe.mcmc - metaArra non-numeric matrix extent error

[Adrian Johnson]

I got it worked.  The answer is hidden in mergemaid function.
poe.mcmc(exprs(intersection(merged)),NN=m)


Sorry for another question.

How to select genes differentially expressed across all datasets from
poe.mcmc result?

 names(poeRes)
 [1] "alpha"        "mug"          "kappaposg"    "kappanegg"
"sigmag"       "piposg"       "pinegg"       "mu"
 [9] "tausqinv"     "gamma"        "lambda"       "pil.pos.mean"
"pil.pos.prec" "pil.neg.mean" "pil.neg.prec" "kap.pos.rate"
[17] "kap.neg.rate" "poe"          "accept"

Thanks
Adrian







On Sun, Oct 21, 2012 at 8:12 AM, Adrian Johnson
<oriolebaltimore at gmail.com> wrote:
> Hi:
>
> I am trying to replicate the code in metaArray package.
>
> The merged object after mergeExprs does not seem to work for poe.mcmc.
> Could anyone help me understand where the problem exist. Thanks in advance.
>
>> poe.mat <- poe.mcmc(merged,M=1000)
> Error in matrix(0, GG, TT) : non-numeric matrix extent
>
> I am using merged object from mergeExprs function from mergeMaid.
> Following is the code I used. This code is chunk1 from metaArray
> vignette ( october 1 2012)
>
> Thanks
> Adrian
>
>
>
> ## code chunk 1 ### from metaArray vignette
> library(metaArray)
> library(Biobase)
> library(MergeMaid)
> data(mdata)
> common <- intersect(rownames(chen.poe),rownames(garber.poe))
> common <- intersect(common, rownames(lapointe.poe))
> chen.poe <- chen.poe[match(common, rownames(chen.poe)),]
> garber.poe <- garber.poe[match(common, rownames(garber.poe)),]
> lapointe.poe <- lapointe.poe[match(common, rownames(lapointe.poe)),]
> vars <- list("var1","var2")
> names(vars) <- names(chen.spl)
> pdata1 <- new("AnnotatedDataFrame")
> pData(pdata1) <- chen.spl
> varLabels(pdata1) <- vars
> sample1 <- new("ExpressionSet", exprs=chen.poe, phenoData = pdata1)
> names(vars) <- names(garber.spl)
> pdata2 <- new("AnnotatedDataFrame")
> pData(pdata2) <- garber.spl
> varLabels(pdata2) <- vars
> sample2 <- new("ExpressionSet", exprs=garber.poe, phenoData = pdata2)
> names(vars) <- names(lapointe.spl)
> pdata3 <- new("AnnotatedDataFrame")
> pData(pdata3) <- lapointe.spl
> varLabels(pdata3) <- vars
> sample3 <- new("ExpressionSet", exprs=lapointe.poe, phenoData = pdata3)
> merged <- mergeExprs(sample1,sample2,sample3)