Hello Andreia,
ah, okay, I think I see now. HTqPCR was only submitted to
BioConductor last October, so it's in BioC 2.5, corresponding to
R-2.10. You're running R-2.9.2, which is why the automatic BioC
installation doesn't work - it'll only look for packages in BioC 2.4,
and therefore not find HTqPCR.
If you update your R to 2.10, you should be able to install HTqPCR
using
>source("
http://www.bioconductor.org/biocLite.R")
> biocLite("HTqPCR")
and get all the appropriate help functions.
Cheers
\Heidi
On 12 Jan 2010, at 10:41, Andreia Fonseca wrote:
> Hi Heidi
>
> I tried to install the package with biocLite("HTqPCR") but is was
> not working, so I downloaded the zip file of the package and
> installed it from there.
> Then I fixed it using the source code you've sent.
> the seesion info is below and the help files do not appear for any
> function.
>
> sessionInfo()
> R version 2.9.2 (2009-08-24)
> i386-pc-mingw32
>
> locale:
> LC_COLLATE=Portuguese_Portugal.1252;LC_CTYPE=Portuguese_Portugal.
> 1252;LC_MONETARY=Portuguese_Portugal.
> 1252;LC_NUMERIC=C;LC_TIME=Portuguese_Portugal.1252
>
> attached base packages:
> [1] stats graphics grDevices datasets utils methods base
>
> other attached packages:
> [1] HTqPCR_1.0.0 limma_2.18.3 RColorBrewer_1.0-2
> Biobase_2.4.1
>
> loaded via a namespace (and not attached):
> [1] affy_1.22.1 affyio_1.12.0 gdata_2.6.1
> [4] gplots_2.7.4 gtools_2.6.1 preprocessCore_1.6.0
>
> cheers
> Andreia
>
>
> On Mon, Jan 11, 2010 at 10:45 PM, Heidi Dvinge <heidi@ebi.ac.uk>
> wrote:
> Hello Andreia,
>
>
> > Dear Heidi,
> >
> > thanks for the message, why stratify="type" doesn't work with
> > plotCtOverview??.
>
> plotCtOverview was only designed to be used for a handful of genes
> individually across multiple samples. Using e.g. all Target or
> Endogenous
> Controls would often either result in hundreds of genes being
plotted.
> Alternatively, values could be summarised by taking the average
> across
> genes within each sample, but that probably wouldn't be so
> informative.
>
> Instead, plotCtOverview() comes with the parameter "genes" for
> selecting
> the genes of interest. This can either be i) a list of gene names
> present
> in featurenames, ii) a vector of the genes to choose, such as
> c(1,6,60,100), or iii) a TRUE/FALSE vector of the same length as
> number of
> features. So if you want t select e.g. all Endogenous Controls, a
> possible
> appraoch would be to say:
>
> > data(qPCRraw)
> > g <- featureType(qPCRraw)=="Endogenous Control"
> > plotCtOverview(qPCRraw, genes=g, xlim=c(0,10))
>
>
> > I also sent you the email because I am getting error
> > when
> > I try to see the help files:
> > ?filterCtData
> > Error in print.help_files_with_topic(x) :
> > No text help for 'filterCtData' is available:
> > corresponding file is missing
> > In addition: Warning message:
> > In
> > print.help_files_with_topic("C:/PROGRA~1/R/R-29~1.2/library/
> HTqPCR/chm/filterCtData")
> > :
> > No CHM help for 'filterCtData' in package 'HTqPCR' is available:
> > the CHM file for the package is missing
> >
> Hm, this definitely looks like some sort of windows-related issue.
> Can you
> perhaps send the exact commands you type in starting from loading
the
> package, along with the output of sessionInfo()? Is this just the
> case for
> this one function, or does it apply to all functions in HTqPCR?
>
> Cheers
> \Heidi
>
> > Thanks
> > Andreia
> >
> > On Mon, Jan 11, 2010 at 6:07 PM, Heidi Dvinge <heidi@ebi.ac.uk>
> wrote:
> >
> >> Hello Andreia,
> >>
> >> sure, if you want to remove some of the data points in HTqPCR
> you can
> >> use
> >> the function filterCtData(). If featureType of your genes are
e.g.
> >> "Endogenous Control" and "Target", you can remove all the target
> genes;
> >> filterCtData(qPCRset, remove.type=c("Target")). See ?
> filterCtData for
> >> more
> >> examples.
> >>
> >> Note that for many of the plotting functions this is actually not
> >> necessary, since you can automatically stratify the data based on
> >> various
> >> feature characteristics. If you're interested in different
> featureType()
> >> or
> >> featureClass(), you can for example say plotCtBoxes(qPCRset,
> >> stratify="type") or with stratify="class". For other plot types,
> such as
> >> scatter plots, features can be coloured differently depending on
> >> featureType
> >> or some other characteristics; e.g. plotCtScatter(qPCRset,
> col="type").
> >>
> >> Cheers
> >> \Heidi
> >>
> >>
> >>
> >> On 11 Jan 2010, at 16:37, Andreia Fonseca wrote:
> >>
> >> Hello Heidi,
> >>>
> >>> thanks for the code, until now everything seems to be o.k. I am
> trying
> >>> to
> >>> filter data and I was wondering if you have created functions
> to select
> >>> data, the reason is that I want to plot the Ct values just for
the
> >>> endogenous control targets to see if there are significant
> differences
> >>> between treatments, something like select.type??
> >>> Cheers
> >>> Andreia
> >>>
> >>> On Fri, Jan 8, 2010 at 4:45 PM, Heidi Dvinge <heidi@ebi.ac.uk>
> wrote:
> >>> Hello Andreia,
> >>>
> >>> I've attached a file with all the latest source code. I still
> need to
> >>> add
> >>> some things plus delete other and correct the documentation,
> before I
> >>> compile it together into a package. However, in your case it
> should
> >>> work
> >>> if you say:
> >>>
> >>> > library(HTqPCR) # To get the vignette and help files
available
> >>> > source("where.ever.you.place.the.file/
> source_functions_v1.1.1.R") #
> >>> Overwrite old functions with corrected ones.
> >>>
> >>> I don't have access to a windows machine right now so I can't
> test it,
> >>> but
> >>> if you still get errors when you try to run through the
> vignette, then
> >>> drop me a line. The sooner I get bugs corrected, the better :)
> >>>
> >>> Cheers
> >>> \Heidi
> >>>
> >>> > Hi Heidi,
> >>> >
> >>> > can you send me the sample data file, this way I can read it
> and
> >>> > continue.
> >>> > cheers
> >>> > Andreia
> >>> >
> >>> > On Fri, Jan 8, 2010 at 11:37 AM, Heidi Dvinge
<heidi@ebi.ac.uk>
> >>> wrote:
> >>> >
> >>> >> Hi Andreia,
> >>> >>
> >>> >> well, sadly enough that's because I'm a numpty!! When I
> wrote the
> >>> >> function(s), rather than defining file position using
> file.path, I
> >>> just
> >>> >> concatenated names with "/" because at that point I was only
> >>> intending
> >>> >> on
> >>> >> using this function for myself on my mac.
> >>> >>
> >>> >> On mac/linux this can be fixed for readCtData by having the
> data you
> >>> >> want
> >>> >> to read in a different directory than your current working
> >>> directory.
> >>> >> However, for windows you'll need a bug-fixed version of
> >>> readCtData(). I
> >>> >> have this available, but it hasn't been submitted to the
> BioC devel
> >>> >> repository yet - it's creeping rapidly higher up on my to-do
> list.
> >>> If
> >>> >> you
> >>> >> want, I can send you a version off-list.
> >>> >>
> >>> >> Cheers
> >>> >> \Heidi
> >>> >>
> >>> >> > Hi Heidi,
> >>> >> >
> >>> >> > Thanks for the advise. I am going through the HTqPCR
> documentation
> >>> but
> >>> >> I
> >>> >> > am
> >>> >> > getting the following error while trying to read the
> sample input
> >>> >> data:
> >>> >> >
> >>> >> > path <- system.file("exData", package = "HTqPCR")
> >>> >> >> head(read.delim(file.path(path, "files.txt")))
> >>> >> > Error in file(file, "r") : cannot open the connection
> >>> >> > In addition: Warning message:
> >>> >> > In file(file, "r") :
> >>> >> > cannot open file '/files.txt': No such file or directory
> >>> >> >> files <- read.delim(file.path(path, "files.txt"))
> >>> >> > Error in file(file, "r") : cannot open the connection
> >>> >> > In addition: Warning message:
> >>> >> > In file(file, "r") :
> >>> >> > cannot open file '/files.txt': No such file or directory
> >>> >> >
> >>> >> >
> >>> >> > I am working in a windows machine and using R 2.9.2
> >>> >> >
> >>> >> > thanks
> >>> >> > Andreia
> >>> >> >
> >>> >> > On Fri, Jan 8, 2010 at 8:44 AM, Heidi Dvinge
> <heidi@ebi.ac.uk>
> >>> wrote:
> >>> >> >
> >>> >> >> Hello Andreia,
> >>> >> >>
> >>> >> >> I'm not familiar with qpcrBatch objects, but <shameless self=""> >>> plug>
> >>> if
> >>> >> >> you're interested in testing for differential expression
> between
> >>> >> genes,
> >>> >> >> you could also consider the HTqPCR package. The raw data
> is read
> >>> into
> >>> >> a
> >>> >> >> qPCRSet object, which is similar to ExpressionSets used
for
> >>> >> microarray
> >>> >> >> data. The package performs various normalisations of the
> raw qPCR
> >>> >> data,
> >>> >> >> similar to qpcrNorm, along with some data visualisation
and
> >>> >> filtering.
> >>> >> >> Differential expression can be analysed using a standard
> t-test
> >>> or
> >>> >> with
> >>> >> >> a
> >>> >> >> limma-based approach, or if you want to do something else
> than
> >>> that
> >>> >> you
> >>> >> >> can extract all the values from your qPCRSet object using
> >>> exprs().
> >>> >> >> </shameless>
> >>> >> >>
> >>> >> >> Cheers
> >>> >> >> \Heidi
> >>> >> >>
> >>> >> >> > Dear list,
> >>> >> >> >
> >>> >> >> > I am trying to understand how qpcrNorm works, so I
> followed the
> >>> >> >> > documentation, so I understood how to normalize the
> data, but
> >>> now
> >>> I
> >>> >> >> want
> >>> >> >> > to
> >>> >> >> > test which genes are differentially expressed between
> batches
> >>> and
> >>> >> make
> >>> >> >> a
> >>> >> >> > Mann-Whitney U-test. How can I transform the normalized
> data
> >>> which
> >>> >> is
> >>> >> >> a
> >>> >> >> > object class qpcrBatch into a data.frame. Or else how
> can test
> >>> >> using
> >>> >> >> this
> >>> >> >> > kind of object.
> >>> >> >> > Thanks for the help
> >>> >> >> > Andreia
> >>> >> >> >
> >>> >> >> > [[alternative HTML version deleted]]
> >>> >> >> >
> >>> >> >> > _______________________________________________
> >>> >> >> > Bioconductor mailing list
> >>> >> >> > Bioconductor@stat.math.ethz.ch
> >>> >> >> >
https://stat.ethz.ch/mailman/listinfo/bioconductor
> >>> >> >> > Search the archives:
> >>> >> >> >
http://news.gmane.org/
> gmane.science.biology.informatics.conductor
> >>> >> >> >
> >>> >> >>
> >>> >> >>
> >>> >> >>
> >>> >> >
> >>> >>
> >>> >>
> >>> >>
> >>> >
> >>>
> >>>
> >>
> >
> >
> > --
> > --------------------------------------------
> > Andreia J. Amaral
> > Unidade de Imunologia Clínica
> > Instituto de Medicina Molecular
> > Universidade de Lisboa
> > email: andreiaamaral@fm.ul.pt
> > andreia.fonseca@gmail.com
> >
>
>
>
>
>
> --
> --------------------------------------------
> Andreia J. Amaral
> Unidade de Imunologia Clínica
> Instituto de Medicina Molecular
> Universidade de Lisboa
> email: andreiaamaral@fm.ul.pt
> andreia.fonseca@gmail.com
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