Hi Guido,

you may benefit from avoiding the SQL interface...

How about:

library(oligo)
rawData = read.celfiles(list.celfiles())
affy.probesets = c("AFFX-BkGr17-GC10_st","AFFX-BkGr17-GC11_st")
fields = c('man_fsetid', 'fid', 'x', 'y')
probeInfo = getProbeInfo(rawData, fields, subset=man_fsetid %in%
affy.probesets)
head(probeInfo)

'man_fsetid' is the manufacturer featureset id (i.e., probeset name)
'fid' is the feature id (which coincides with the row number in the
*FeatureSet object for that given probe)
'x' and ''y' are the physical x/y coordinates

note that the 'subset=man_fsetid %in% affy.probesets' expression above
corresponds to the subset= argument in the subset() command. As '...' for
getProbeInfo() you can pass any argument for the subset() command.

If you prefer to use the SQL interface, the featureSet table contains the
*probeset* information; the pmfeature table contains the *probe*
information. In your case, you want to INNER JOIN featureSet and pmfeature
tables and subset using man_fsetid...

HTH, b



2014/1/21 Hooiveld, Guido <guido.hooiveld@wur.nl>

> Hello,
> I would like to extract the probes that belong to a set of probesets from
> a PdInfo database, but despite searching the archives I got stuck... I
> would appreciate some hints.
>
> To be specific: I am working with an Affymetrix miRNA 3.1 dataset. I would
> like to extract all probes that belong to e.g. a set of affy control
> probesets, such as e.g. AFFX-BkGr17-GC10_st and AFFX-BkGr17-GC11_st.
> This is my approach:
> > library(pd.mirna.3.1)
> > con <- db(pd.mirna.3.1)
>
> > affy.probesets <- c("AFFX-BkGr17-GC10_st","AFFX-BkGr17-GC11_st")
> > affy.probesets
> [1] "AFFX-BkGr17-GC10_st" "AFFX-BkGr17-GC11_st"
> >
>
> > #check available tables/information
> > dbGetQuery(con, "select name, sql from sqlite_master where type='table'")
>         name
>                                                      sql
> 1  type_dict                                                        CREATE
> TABLE type_dict (type INTEGER PRIMARY KEY, type_id TEXT)
> 2 featureSet         CREATE TABLE featureSet (fsetid INTEGER PRIMARY KEY,
> man_fsetid TEXT, type INTEGER REFERENCES type_dict(type))
> 3  pmfeature CREATE TABLE pmfeature (fid INTEGER, fsetid INTEGER
> REFERENCES featureSet(fsetid), atom INTEGER, x INTEGER, y INTEGER)
> 4  mmfeature CREATE TABLE mmfeature (fid INTEGER, fsetid INTEGER
> REFERENCES featureSet(fsetid), atom INTEGER, x INTEGER, y INTEGER)
> 5 table_info
>  CREATE TABLE table_info \n( tbl TEXT,\n\trow_count INTEGER \n)
> >
>
> So far so good.
> However, how now to continue?
> For arrays for which a CDF is available, for e.g. the miRNA 1.0 array I
> would do something like this (although now only the probes for the 1st
> probeset in affy.probesets would be extracted, but that's now not the main
> question) :
> > get(affy.probesets, mirna10cdf)
>          pm mm
> [1,] 34705 NA
> [2,] 46085 NA
> [3,] 20445 NA
> [4,] 26368 NA
> <<snip>>
>
> Main question: how could I achieve this when using a PdInfo object?
>
> Related to this, how can I get more info on what the various keys
> represent? E.g. what does 'man_fsetid' represent?
> [From the mailing list I meanwhile now these represent the Affymetrix
> "probeset_name", and the 'fsetid' the Affymetrix "probeset_id"].
>
>
> -->> Reason I am asking all this is because I would like to analyze
> (normalize) my miRNA 3.1 dataset using the normexp-by-control background
> correction (nec function in limma), essentially as described in:
> http://www.pubmed.org/23709276.
>
> Thanks,
> Guido
>
> ---------------------------------------------------------
> Guido Hooiveld, PhD
> Nutrition, Metabolism & Genomics Group
> Division of Human Nutrition
> Wageningen University
> Biotechnion, Bomenweg 2
> NL-6703 HD Wageningen
> the Netherlands
> tel: (+)31 317 485788
> fax: (+)31 317 483342
> email:      guido.hooiveld@wur.nl
> internet:   http://nutrigene.4t.com
> http://scholar.google.com/citations?user=qFHaMnoAAAAJ
> http://www.researcherid.com/rid/F-4912-2010
>
>
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>
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