[BioC] Limma and Names Assignment

[Ovokeraye Achinike-Oduaran]

Hi Sean,

Thanks a bunch!

Regards,

Avoks

On Fri, Oct 14, 2011 at 11:03 AM, Sean Davis <sdavis2 at mail.nih.gov> wrote:
> On Fri, Oct 14, 2011 at 4:40 AM, Ovokeraye Achinike-Oduaran
> <ovokeraye at gmail.com> wrote:
>>
>> Hi all,
>>
>> In trying to create a contrast matrix of interest, I thought it would
>> be easier to assign one-word names to the different disease states. I
>> seem to have gotten it to work for the GDS3715 data set that happens
>> to be a 3x2 factorial experiment, I think. But for the seemingly less
>> complex GDS3665, I  can't seem to get it right. It keeps giving me
>> these errors(below). Any ideas as to what I could possibly be doing
>> wrong? Any help will be greatly appreciated.
>>
>> Thanks.
>>
>> -Avoks
>>
>>
>>
>> >gds3665dat = getGEO('GDS3665',destdir=".")
>> >gds3665eset = GDS2eSet(gds3665dat, do.log2=TRUE)
>> > groups= pData(gds3665eset)$disease.state
>> > groups
>>  [1] diabetes diabetes diabetes diabetes diabetes control  control  control
>>  [9] control  control
>> Levels: control diabetes
>>
>> > groups[groups=="control"]="Control"
>> Warning message:
>> In `[<-.factor`(`*tmp*`, groups == "control", value = "Control") :
>>  invalid factor level, NAs generated
>> > groups[groups=="diabetes"]="T2D"
>> Warning message:
>> In `[<-.factor`(`*tmp*`, groups == "diabetes", value = "T2D") :
>>  invalid factor level, NAs generated
>
> Hi, Avoks.
>
> "groups" above is a factor, not a character vector.  They look the
> same, but they are different.  In the case below, you used paste()
> which creates a character vector; hence, the behavior is different.
> If you convert to a character vector first, things will work as
> expected.
>
> groups <- as.character(groups)
>
> Alternatively, you can use levels() to change the levels for the
> factor.  Check the help for levels, relevel, factor, and as.character
> for details.
>
> Sean
>
>
>> > groups
>>  [1] <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
>> Levels: control diabetes
>>
>> This, however, works just fine.
>>
>> gds3715dat = getGEO('GDS3715',destdir=".")
>> gds3715eset = GDS2eSet(gds3715dat, do.log2=TRUE)
>> groups = paste(pData(gds3715eset)$disease.state,
>> pData(gds3715eset)$agent, sep =".")
>> groups[groups=="insulin sensitive.untreated"]= "IS.U"
>> groups[groups=="insulin resistant.untreated"]= "IR.U"
>> groups[groups=="diabetic.untreated"]= "T2D.U"
>> groups[groups=="insulin sensitive.insulin"]= "IS.T"
>> groups[groups=="insulin resistant.insulin"]= "IR.T"
>> groups[groups=="diabetic.insulin"]= "T2D.T"
>> > sessionInfo()
>> R version 2.13.2 (2011-09-30)
>> 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] XML_3.4-2.2     RCurl_1.6-10.1  bitops_1.0-4.1  puma_2.4.0
>> [5] mclust_3.4.10   affy_1.30.0     limma_3.8.3     GEOquery_2.19.4
>> [9] Biobase_2.12.2
>>
>> loaded via a namespace (and not attached):
>> [1] affyio_1.20.0         preprocessCore_1.14.0 tools_2.13.2
>>
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>