[BioC] GEO and Limma

[Ovokeraye Achinike-Oduaran]

Thanks Sean.

Avoks

On Tue, Oct 4, 2011 at 8:08 PM, Sean Davis <sdavis2 at mail.nih.gov> wrote:
> On Tue, Oct 4, 2011 at 2:04 PM, Ovokeraye Achinike-Oduaran
> <ovokeraye at gmail.com> wrote:
>> Thanks a bunch, Johannes and Sean. I'll try the GSE data again as soon
>> as I  get in front of a comp. About the first question on creating a
>> model matrix  for a 3x2 factorial dataset like gds3715, any ideas?
>
> You'll probably need a contrast matrix in there somewhere to pull out
> contrasts of interest.  I'm not sure which you are interested in.
>
> Sean
>
>
>> Thanks again.
>>
>> Avoks
>>
>> On 10/4/11, Sean Davis <sdavis2 at mail.nih.gov> wrote:
>>> On Tue, Oct 4, 2011 at 10:28 AM, Ovokeraye Achinike-Oduaran
>>> <ovokeraye at gmail.com> wrote:
>>>> Hi all,
>>>>
>>>> I've been struggling a bit with GEO and limma. I've come up with 2
>>>> questions that I'ld appreciate some input on.
>>>>
>>>> Question 1:
>>>> I have a design matrix with 6columns for an expression set with 3
>>>> columns(3 levels, 2 agents). How do I create a model matrix to fit my
>>>> design matrix for this dataset (eg. gds3715 below)? For a straight
>>>> forward single factor analysis eg. gds161, the code below seems to
>>>> work fine.
>>>>
>>>> gds161dat = getGEO('GDS161',destdir=".")
>>>> gds161eset = GDS2eSet(gds161dat, do.log2=TRUE)
>>>> m = pData(gds161eset)$metabolism
>>>> design_gds161 = createDesignMatrix(gds161eset)
>>>> design_gds161 = model.matrix(~m)
>>>> fit = lmFit(gds161eset, design_gds161)
>>>> fit2 = eBayes(fit)
>>>> results = topTable(fit2, adjust ="BH", number = nrow(gds161eset))
>>>> excel = write.table(results, file = file.choose(), sep = ",")
>>>>
>>>> gds3715dat = getGEO('GDS3715',destdir=".")
>>>> gds3715eset = GDS2eSet(gds3715dat, do.log2=TRUE)
>>>> DIR = paste(pData(gds3715eset)$disease.state,
>>>> pData(gds3715eset)$agent, sep =".")
>>>> m = data.frame("fac1" = pData(gds3715eset)$disease.state, "fac2" =
>>>> pData(gds3715eset)$agent)
>>>> design_gds3715 = createDesignMatrix(gds3715eset)
>>>> design_gds3715 = model.matrix(~m)
>>>> fit = lmFit(gds3715eset, design_gds3715)
>>>> fit2 = eBayes(fit)
>>>> results = topTable(fit2, adjust ="BH", number = nrow(gds3715eset))
>>>> excel = write.table(results, file = file.choose(), sep = ",")
>>>>
>>>> Question 2:
>>>> How can I run a similar (limma) analysis with GSE files?
>>>> I can hardly figure out how to get from the expression set to the
>>>> analysis...I've read the Using the GEOquery Package documentation
>>>> several times over. I'm just have a hard time getting it to work.
>>>>
>>>> gse25724dat = getGEO('GSE25724', GSEMatrix = TRUE)
>>>
>>> Hi, Avoks.  The return value from this call is a LIST of
>>> ExpressionSets, not a single ExpressionSet.  You probably want the
>>> first ExpressionSet from the list and can get that:
>>>
>>> gse25724eSet = gse25724dat[[1]]
>>>
>>> GEOquery works this way because many GSEs (so-called superseries) have
>>> multiple series included within them, so returning a list is necessary
>>> to be general.
>>>
>>> Sean
>>>
>>>
>>>> This is supposed to give me an expressionset, I can't seem to figure
>>>> out how to analyze it with limma.
>>>>
>>>> Please help.
>>>>
>>>> Thanks.
>>>>
>>>> Avoks
>>>>
>>>> sessionInfo()
>>>> R version 2.13.1 (2011-07-08)
>>>> Platform: i386-pc-mingw32/i386 (32-bit)
>>>>
>>>> locale:
>>>> [1] LC_COLLATE=English_xxx. LC_CTYPE=English_xxx
>>>> [3] LC_MONETARY=English_xxx LC_NUMERIC=C
>>>> [5] LC_TIME=English_xxx
>>>>
>>>> attached base packages:
>>>> [1] stats     graphics  grDevices utils     datasets  methods   base
>>>>
>>>> other attached packages:
>>>> [1] puma_2.4.0      mclust_3.4.10   affy_1.30.0     limma_3.8.3
>>>> [5] GEOquery_2.19.4 Biobase_2.12.2
>>>>
>>>> loaded via a namespace (and not attached):
>>>> [1] affyio_1.20.0         preprocessCore_1.14.0 RCurl_1.6-10.1
>>>> [4] tools_2.13.1          XML_3.4-2.2
>>>>
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>>>>
>>>
>>
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>