On Tue, Nov 29, 2011 at 10:04 AM, francesca casalino <
francy.casalino@gmail.com> wrote:
> Thank you so much for all your valuable information and help.
>
> The gwSnpTests now works, since I specified a function as you
suggested:
>
> f1 = gwSnpTests(probeId("10023813203")~GENDER, ss)
>
> However I still find myself having to limit the chromosome data at
the
> plink import stage to chromosome 19, and can't seem to be able to do
> this after the creation of the smlSet. As you say, the
gwSnpTeststakes
> uses all the SNPs in the smList(smlSet) to run the association, but
I
> am not getting a list organized by chromosome, and I think my
problem
> is the original sml_Set list, which I created doing this:
>
> ss<- make_smlSet(es, list("1"=snp.matrix$genotypes))
>
>
The above command will create an smlSet with smList of length one. If
you
want to be
able to separate out chromosomes of SNP, you should take
snp.matrix$genotypes and do a
little more work. The columns of this entity are SNP loci. You might
be
able to do the following.
Make a table, say CMAP, that has column 1 the snp IDs (usually rs
numbers,
perhaps something else) and column
2 the chromosome to which each SNP belongs. For simplicity make sure
that
each column is a character vector.
then create the list SMAP = split(CMAP[,1], CMAP[,2])
this will be a list with as many elements as there are chromosomes.
The
contents of each list element are the
snp residing on the corresponding chromosome, and the names(SMAP) is a
vector of chromosome names
Now, SLIST = lapply(SMAP, function(x) snp.matrix$genotypes[, x]) #
errors
can occur if SMAP has elements not in colnames ...
names(SLIST) = names(SMAP)
will create a list of SnpMatrix instances with one SnpMatrix per
chromosome. you can use SLIST as
the second argument to make_smlSet, and you can use chrnum() to select
specific element used in testing
with gwSnpTests.
> While I have SNPs from all chromosomes in the snp.matrix$genotypes,
I
> guess I am indicating wrongly here that I only have one chromosome.
Is
> it possible to create an smlSet with all the chromosomes, and then
> select only some using:
> chr19_20 <- getSS("GGtools", c("19", "20"))
>
> Also when I try to find the genesymbol APOE (which is present in the
> original plink files) I get:
>
> f2 = gwSnpTests(genesym("APOE")~GENDER, ss)
> character(0)
>
This is a convenience feature that will succeed if you have
annotation(ss)
= "[name of a bioconductor .db chip annotation package]" and the
symbol you
ask for is mapped.
> Failed with error: 'package' must be of length 1
> Error in revmap(get(paste(gsub(".db", "", annpack), "SYMBOL", sep
=
> ""))) :
> error in evaluating the argument 'x' in selecting a method for
> function 'revmap': Error in get(paste(gsub(".db", "", annpack),
> "SYMBOL", sep = "")) :
> object 'SYMBOL' not found
>
> Which could still be due to creating an incorrect sml_Set.
>
>
These error messages can be clarified, sorry about this.
> Thank you once more for your all your advices!
> -f
>
> 2011/11/29 Vincent Carey <stvjc@channing.harvard.edu>:
> >
> >
> > On Tue, Nov 29, 2011 at 5:20 AM, francy [guest]
<guest@bioconductor.org>
> > wrote:
> >>
> >>
> >> Hi all,
> >>
> >> I am trying to find eQTLs in or around a particular gene with
probe ID=
> >> "10023813203" (gene is APOE). I have first selected the SNPs on
only my
> >> chromosome of interest (chr19), then imported the plink files
only for
> this
> >> chromosome doing this:
> >>
> >> snp.matrix<-read.plink("plink.bed", "plink.bim",
> >> "plink.fam",select.snps=chr19)
> >>
> >> I was able to create an expression set (called 'es'), and a
sml_Set by
> >> doing this:
> >>
> >> ss<- make_smlSet(es, list("1"=snp.matrix$genotypes))
> >>
> >> but I can't seem to go beyond and use this sml_Set to perform the
> >> association.
> >>
> >> When I try this or other combinations of this (e.g. using 'APOE')
> >> f1 = gwSnpTests(probeId("10023813203"), ss)
> >>
> >> Error in function (classes, fdef, mtable) :
> >> unable to find an inherited method for function "gwSnpTests",
for
> >> signature "character", "smlSet", "missing", "missing"
> >>
> >
> > When you encounter an error of this sort, please check what
signatures
> are
> > supported:
> >
> >> showMethods("gwSnpTests")
> > Function: gwSnpTests (package GGtools)
> > sym="formula", sms="smlSet", cnum="cnumOrMissing", cs="missing"
> > sym="formula", sms="smlSet", cnum="snpdepth", cs="missing"
> >
> > This shows that the first argument should be a formula, and
suggests that
> > you can have only two arguments if you like.
> >
> > If you change your call to
> >
> > f1 = gwSnpTests(probeId("10023813203")~1, ss)
> >
> > I would expect it to succeed. Note the example code, from R 2.14,
which
> you
> > really should be using at this time:
> >
> >> hmceuB36.2021 <- getSS("GGtools", c("20", "21")) # construct
smlSet
> >> from prepackaged data
> >> hmFou = hmceuB36.2021[, which(hmceuB36.2021$isFounder)] #
filter
> samples
> >> to 'founders'
> >> f1 = gwSnpTests(genesym("CPNE1")~male, hmFou, chrnum(20)) #
execute
> >> simple set of tests
> >> f1 # there are 119921 tests, so have a concise
report
> > gwSnpScreenResult for gene CPNE1 [probe GI_23397697-A ]
> >> topSnps(f1) # get top results
> > p.val
> > rs17093026 3.735759e-10
> > rs1118233 1.272958e-09
> > rs12480408 1.360682e-09
> > rs6060535 1.360682e-09
> > rs11696527 1.360682e-09
> > rs6058303 1.360682e-09
> > rs6060578 1.360682e-09
> > rs2425078 1.360682e-09
> > rs1970357 1.360682e-09
> > rs7273815 1.806197e-09
> >
> >
> >
> >
> >>
> >> My first question is, why is the 'gwSnpTests' not working?
> >
> >
> > Please use a supported call sequence.
> >
> >>
> >> My second question is, do I have to select the chromosome I am
> interested
> >> in before creating the sml test? I would have liked to select
> chromosome 19
> >> after so that I could analyse more than this one chromosome if I
wanted
> >> toâ¦Is this possible?? It seems as the snp.matrix must be in the
form
> of a
> >> list, so maybe I have to create a list of all the chromosomes?
> >>
> >> THANK YOU VERY VERY MUCH FOR ANY HELP YOU COULD GIVE ME!! I
really
> >> appreciate it!
> >>
> >
> > The signatures show that you can omit the chromosome if you wish.
In
> this
> > case,
> >
> >> f2 = gwSnpTests(genesym("CPNE1")~male, hmFou)
> >> f2
> > gwSnpScreenResult for gene CPNE1 [probe GI_23397697-A ]
> >> topSnps(f2)
> > $`20`
> > p.val
> > rs17093026 3.735759e-10
> > rs1118233 1.272958e-09
> > rs12480408 1.360682e-09
> > rs6060535 1.360682e-09
> > rs11696527 1.360682e-09
> > rs6058303 1.360682e-09
> > rs6060578 1.360682e-09
> > rs2425078 1.360682e-09
> > rs1970357 1.360682e-09
> > rs7273815 1.806197e-09
> >
> > $`21`
> > p.val
> > rs2823672 3.024310e-05
> > rs4257464 4.340207e-05
> > rs16994832 4.340207e-05
> > rs2823676 4.340207e-05
> > rs2823677 4.340207e-05
> > rs8131686 4.340207e-05
> > rs2823683 4.340207e-05
> > rs238983 4.340207e-05
> > rs2828436 4.340207e-05
> > rs2828438 4.340207e-05
> >
> > gwSnpTests will operate on all the SNPs in the smList(smlSet) and
return
> > lists organized by
> > chromosome. Hence the "gw" -- it is possible to compute a genome-
wide
> > search for eQTL if the
> > smlSet contains SNP from all chromosomes. A few years ago this
was quite
> > reasonable when we
> > handled, say, 4 million SNP. Then it became less reasonable when
we
> started
> > to work with 8 million
> > SNP. So the infrastructure changed to deemphasize working with
all
> > chromosomes at once -- thus the
> > introduction of getSS() to construct the smlSet for a selected set
> > (typically only one) of chromosomes of SNP.
> >
> > Concisely computing and managing results from transcriptome x
genome
> > searches is addressed by
> > the eqtlTests function and by genewiseFDRtab ... these functions
are
> under
> > development to simplify these
> > tasks, which can be arduous as large imputed SNP panels come into
play.
> > Thus it is relevant to work with
> > the devel branch as you start hitting limits. I will provide more
news
> as
> > work proceeds. As the initial discussion
> > of this topic occurred on biostar list, I will note for other
readers
> that a
> > tutorial on using GGtools with R 2.14 is
> > available at ismb11gg.wordpress.com, and that the ggtut
experimental
> data
> > package underlies the tutorial. Of
> > note is that ggtut will not pass check with R devel, because some
> serialized
> > objects conflict with revised class
> > definitions. This will be sorted before too long.
> >
> >
> >>
> >> -- output of sessionInfo():
> >
> >
> > I strongly advise you to upgrade to R 2.14. My sessionInfo for
the runs
> > above is
> >
> > R version 2.14.0 Patched (2011-11-09 r57622)
> > Platform: x86_64-unknown-linux-gnu (64-bit)
> >
> > locale:
> > [1] LC_CTYPE=en_US.iso88591 LC_NUMERIC=C
> > [3] LC_TIME=en_US.iso88591 LC_COLLATE=en_US.iso88591
> > [5] LC_MONETARY=en_US.iso88591 LC_MESSAGES=en_US.iso88591
> > [7] LC_PAPER=C LC_NAME=C
> > [9] LC_ADDRESS=C LC_TELEPHONE=C
> > [11] LC_MEASUREMENT=en_US.iso88591 LC_IDENTIFICATION=C
> >
> > attached base packages:
> > [1] splines stats graphics grDevices datasets tools
utils
> > [8] methods base
> >
> > other attached packages:
> > [1] illuminaHumanv1.db_1.12.1 GGtools_4.1.8
> > [3] ff_2.2-3 bit_1.1-7
> > [5] GenomicRanges_1.6.2 org.Hs.eg.db_2.6.4
> > [7] rtracklayer_1.14.2 RCurl_1.7-0
> > [9] bitops_1.0-4.1 IRanges_1.12.1
> > [11] annotate_1.32.0 AnnotationDbi_1.16.2
> > [13] GGBase_3.15.2 genefilter_1.36.0
> > [15] RSQLite_0.10.0 DBI_0.2-5
> > [17] snpStats_1.4.0 Matrix_1.0-1
> > [19] lattice_0.20-0 survival_2.36-10
> > [21] BiocGenerics_0.1.0 Biobase_2.14.0
> > [23] weaver_1.20.0 codetools_0.2-8
> > [25] digest_0.5.1 BiocInstaller_1.2.1
> >
> > loaded via a namespace (and not attached):
> > [1] Biostrings_2.22.0 BSgenome_1.22.0 grid_2.14.0
Rsamtools_1.7.1
> > [5] XML_3.4-3 xtable_1.6-0 zlibbioc_1.0.0
> >
> >>
> >>
> >> > sessionInfo()
> >> R version 2.13.1 (2011-07-08)
> >> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
> >>
> >> locale:
> >> [1] en_GB.UTF-8/en_GB.UTF-8/C/C/en_GB.UTF-8/en_GB.UTF-8
> >>
> >> attached base packages:
> >> [1] tools splines stats graphics grDevices utils
datasets
> >> [8] methods base
> >>
> >> other attached packages:
> >> [1] GGtools_3.10.2 ff_2.2-3 bit_1.1-7
> >> [4] GenomicRanges_1.4.8 org.Hs.eg.db_2.5.0 rtracklayer_1.12.5
> >> [7] RCurl_1.6-10 bitops_1.0-4.1 IRanges_1.10.6
> >> [10] annotate_1.30.1 AnnotationDbi_1.14.1 GGBase_3.12.0
> >> [13] RSQLite_0.10.0 DBI_0.2-5 snpStats_1.2.1
> >> [16] Matrix_0.999375-50 lattice_0.19-33 survival_2.36-9
> >> [19] Biobase_2.12.2
> >>
> >> loaded via a namespace (and not attached):
> >> [1] Biostrings_2.20.4 BSgenome_1.20.1 grid_2.13.1
XML_3.4-3
> >> [5] xtable_1.5-6
> >>
> >>
> >> --
> >> Sent via the guest posting facility at bioconductor.org.
> >>
> >> _______________________________________________
> >> Bioconductor mailing list
> >> Bioconductor@r-project.org
> >>
https://stat.ethz.ch/mailman/listinfo/bioconductor
> >> Search the archives:
> >>
http://news.gmane.org/gmane.science.biology.informatics.conductor
> >
> >
>
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