[BioC] Limma and Names Assignment

[Ovokeraye Achinike-Oduaran]

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

> 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