[BioC] GEOquery: getGEO() doesn\'t work (error \"invalid \'nlines\' argument\")
ecsi at gmx.net
ecsi at gmx.net
Tue May 29 17:45:20 CEST 2012
> So when you use system.file() you are specifically telling GEOquery to
> look for a file that is in your GEOquery library directory, rather
> than telling GEOquery the actual directory.
Thank you for explaining the system.file() thing, I didn't know that
this was about the package repository. I thought it would be necessary
to be able to access the downloaded files, but now I understand what's
> > mypath <- "C:/Users/bioinf_admin/Desktop/"
> > GSE19711 <- getGEO('GSE19711',destdir=mypath)
> This will result in a list of ExpressionSets
The problem is, that here I work with methylation data, so have to
create MethyLumiSets instead of ExpressionSets.
My idea was to create phenodata.txt files using the data I get from
> GSE19711 <- getGEO(filename="mypath/GSE19711_family.soft.gz")
(Btw, I always get warnings when doing this, but it seems to work anyway:
1: In readLines(con, n = chunksize) :
seek on a gzfile connection returned an internal error
And then accessing the information with some code like this for example:
 "ageatrecruitment: 68"
And extract the relevant substrings and create a data.frame with all the
information I need (age, sex, treatment, etc.). And all this in an apply
function for every GSE or something like this. Furthermore getting the
data matrices from the soft files as well and finally creating
MethyLumiSets out of the data matrices and the phenodata.txt files I
Maybe it would be better to first create ExpressionSets and convert them
into MethyLumiSets somehow, but I would have to manipulate the objects
anyway, because I can't use the phenodata information as it comes from
GEO in these cases. I need the phenodata to be the same style for all
the GEO sets I have to analyze, so in any case I'll have to do the work
to extract (only) the information I need for the different GEO sets.
But I'm still not quite sure about the best way to create the
MethyLumiSets efficiently ...
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