Hi,
Thanks again. Now the path is OK and it is no problem until the
image creating.
When I library(EBImage), I got the following error:
> library(EBImage)
Error in inDL(x, as.logical(local), as.logical(now), ...) :
unable to load shared library
'D:/PROGRA~2/R/R-29~1.0/library/EBImage/libs/EBImage.dll':
LoadLibrary failure: The specified module could not be found.
Error: package/namespace load failed for 'EBImage'
I found the file in
D:\Program Files (x86)\R\R-2.9.0\library\EBImage\libs\EBImage.dll
and I have installed *ImageMagick* and GTK+ Runtime Environment in
default directory. My OS is vista x64. How can I deal with this problem.
Best,
jiang
On Thu, May 14, 2009 at 3:36 PM, Lakshmanan Iyer <lax...@gmail.com> wrote:
> Hi
> If you change the working directory to the proper one under which you have
> put all these directories and files, and source the script from there it
> should automatically recognize it and work fine. Give it a spin and tell me
> what you get.
>
> As for patient answers, others have done more for my ignorance!
> My only hope is that I am not misleading you :-)
> -Best
> -Lax
>
>
>
> On Thu, May 14, 2009 at 4:21 PM, chunjiang he <camel...@gmail.com> wrote:
>
>> Thanks so much for the patient answers.
>>
>> I think there are some problems with my environment path. I have put all
>> my data and CDF in directories strictly as yours. But the problem is also
>> the same. I checked my CDF files.
>> I put 5 files in the /annotationData/chipTypes/MoGene-1_0-st-v1:
>>
>> MoEx-1_0-st-v1,coreR1,A20080718,MR.cdf
>> MoEx-1_0-st-v1,extendedR1,A20080718,MR.cdf
>> MoEx-1_0-st-v1,fullR1,A20080718,MR.cdf
>> MoEx-1_0-st-v1,U-Ensembl50,G-Affy,EP.cdf
>> MoEx-1_0-st-v1.cdf
>>
>> I think the *,monocell.cdf may be created automatically when I run the
>> scripts.
>>
>> And i put all the CEL files in /rawData/JunXu/MoGene-1_0-st-v1. So I think
>> it is no problem. But does the script can recognize the path automatically,
>> or I must indicate it in R scripts?
>> On Thu, May 14, 2009 at 2:38 PM, Lakshmanan Iyer <lax...@gmail.com>wrote:
>>
>>> Hi
>>> Put the raw data, CEL files in,
>>> C:/Documents and Settings/rawData/JunXu/MoGene-1_0-st-v1
>>>
>>> and annotatino file, CDF files, in
>>> C:/Documents and Settings/annotationData/chipTypes/MoGene-1_0-st-v1
>>>
>>> Copy the R-script below in note book and save it as "myscript.R"
>>>
>>> Now Launch R
>>> Change Working directory to C:/Documents and Settings
>>> use the R command:
>>> source ("myscript.R")
>>> to execute the commands and it should work.
>>>
>>> I am afraid, I am making this up from my previous experience working with
>>> PCs.
>>>
>>> -Best
>>> -Lax
>>>
>>>
>>> On Thu, May 14, 2009 at 3:00 PM, chunjiang he <camel...@gmail.com>wrote:
>>>
>>>> Thanks very much,
>>>> But how could I set my data path and array path in windows. I mean how
>>>> to set it when I use R.
>>>> when I run this:
>>>>
>>>> > cdf<-AffymetrixCdfFile$fromChipType(chipType)
>>>>
>>>> I got the error:
>>>>
>>>> Error in list(`AffymetrixCdfFile$fromChipType(chipType)` =
>>>> <environment>, :
>>>>
>>>> [2009-05-14 13:57:50] Exception: Could not locate a file for this chip
>>>> type: MoGene-1_0-st-v1
>>>> at throw(Exception(...))
>>>> at throw.default("Could not locate a file for this chip type: ",
>>>> paste(c(chipT
>>>> at throw("Could not locate a file for this chip type: ",
>>>> paste(c(chipType, tag
>>>> at byChipType.UnitNamesFile(static, ...)
>>>> at byChipType(static, ...)
>>>> at method(static, ...)
>>>> at AffymetrixCdfFile$fromChipType(chipType)
>>>>
>>>> Best,
>>>> Jiang
>>>>
>>>> On Thu, May 14, 2009 at 12:45 PM, Lakshmanan Iyer
>>>> <lax...@gmail.com>wrote:
>>>>
>>>>> Hi,
>>>>> Hope this helps!
>>>>> Here is how I ran a Affy, MoGene-1_0-st chip analysis on a ubuntu/linux
>>>>> box:
>>>>> Please double check the code to make sure that it is fine! I have not
>>>>> looked at it for a long time.
>>>>> -Best
>>>>> -Lax
>>>>> ________________________________________________________________
>>>>> The CEL file (JC1.CEL JC2.CEL NC1.CEL NC2.CEL) are in:
>>>>> /home/laxman/Projects/Analysis/rawData/JunXu/MoGene-1_0-st-v1
>>>>>
>>>>> The annotation files, CDF files, (MoGene-1_0-st-v1.cdf
>>>>> MoGene-1_0-st-v1,monocell.CDF) are in:
>>>>>
>>>>> /home/laxman/Projects/Analysis/annotationData/chipTypes/MoGene-1_0-st-v1
>>>>>
>>>>> Directory in which I am running the jobs. Contains the R script file,
>>>>> see below:
>>>>> /home/laxman/Projects/Analysis
>>>>> Pay attention to the line following: #<<<<<<<<<<<<<<<<<
>>>>>
>>>>> The results would be found in:
>>>>> /home/laxman/Projects/Analysis/Results/JunXu
>>>>>
>>>>> #####################################################################
>>>>> # Script to calculate probeset level/gene level intensities
>>>>> #Based on
>>>>> http://groups.google.com/group/aroma-affymetrix/web/human-exon-array-analysis
>>>>> #Load the library
>>>>> library(aroma.affymetrix)
>>>>> verbose <- Arguments$getVerbose(-8)
>>>>> timestampOn(verbose)
>>>>> #
>>>>> #<<<<<<<<<<<<<<<<<
>>>>> #setup the CDF explicitly as:
>>>>> chipType <- "MoGene-1_0-st-v1"
>>>>> cdf <- AffymetrixCdfFile$fromChipType(chipType)
>>>>> #
>>>>> #Next we setup the CEL set with the above custom CDF:
>>>>> ##<<<<<<<<<<<<
>>>>> cs <- AffymetrixCelSet$fromName("JunXu", cdf=cdf)
>>>>> setCdf(cs,cdf)
>>>>> #
>>>>> #In order to do RMA background correction, we setup a correction method
>>>>> and runs it by:
>>>>> #
>>>>> bc <- RmaBackgroundCorrection(cs)
>>>>> csBC <- process(bc,verbose=verbose)
>>>>> #Note that this is the first step where we will create new files,
>>>>> #so we have put in a tag that should follow through the rest of the
>>>>> analysis.
>>>>> #
>>>>> #We then setup a quantile normalization method:
>>>>> qn <- QuantileNormalization(csBC, typesToUpdate="pm")
>>>>> print(qn)
>>>>> #
>>>>> #and we then run it by:
>>>>> csN <- process(qn, verbose=verbose)
>>>>> print (csN)
>>>>> #
>>>>> #You can check associated CSF with the command
>>>>> getCdf(csN)
>>>>> #
>>>>> #To fit a summary of the entire transcript (i.e. estimate the overall
>>>>> expression for the transcript), do
>>>>> plmTr <- ExonRmaPlm(csN, mergeGroups=TRUE)
>>>>> print(plmTr)
>>>>> #
>>>>> #Otherwise, to fit exon-by-exon, change the value of mergeGroups to
>>>>> FALSE in the ExonRmaPlm() call above.
>>>>> #
>>>>> # plmEx <- ExonRmaPlm(csN, mergeGroups=FALSE)
>>>>> # print(plmEx)
>>>>> #
>>>>> #To fit the PLM to all of the data, do:
>>>>> #
>>>>> fit(plmTr, verbose=verbose)
>>>>> #
>>>>> #or similarly for plmEx.
>>>>> # fit(plmEx, verbose=verbose)
>>>>> #
>>>>> #Quality assessment of PLM fit
>>>>> #
>>>>> #To calculate the residuals from the PLM fit, do:
>>>>> #
>>>>> rs <- calculateResiduals(plmTr, verbose=verbose)
>>>>> #
>>>>> #To browse spatial false-colored images of the residuals, do:
>>>>> ae <- ArrayExplorer(rs)
>>>>> setColorMaps(ae, c("log2,log2neg,rainbow",
>>>>> "log2,log2pos,rainbow"))
>>>>> process(ae, interleaved="auto", verbose=verbose)
>>>>> # display(ae)
>>>>> #
>>>>> #To examine NUSE and RLE plots, do
>>>>> #Note that this can be done to fits based on the transcript level
>>>>> #or exon level depending on which plm you chose and can give different
>>>>> interpretations.
>>>>> qamTr <- QualityAssessmentModel(plmTr)
>>>>> # save plots in pdf file
>>>>> pdf(file="/home/laxman/Projects/Analysis/Results/JunXu/NusePlot.pdf");
>>>>> plotNuse(qamTr)
>>>>> pdf(file="/home/laxman/Projects/Analysis/Results/JunXu/RlePlot.pdf");
>>>>> plotRle(qamTr)
>>>>> dev.off()
>>>>> # turned pdf off
>>>>> #
>>>>> #
>>>>> #To extract the estimates (transcript or probeset)
>>>>> #use either extractMatrix() or extractDataFrame() on the ChipEffectSet
>>>>> that corresponds to the plm object:
>>>>> #This will give a data.frame with three rows, each row corresponding to
>>>>> a unit/transcript
>>>>> #
>>>>> cesTr <- getChipEffectSet(plmTr)
>>>>> trFit <- extractDataFrame(cesTr, addNames=TRUE)
>>>>> write.table
>>>>> (trFit[,c(1,6:9)],"/home/laxman/Projects/Analysis/Results/JunXu/trFit.tsv",
>>>>> sep="\t", quote=F)
>>>>>
>>>>> #
>>>>> #To get estimates of the probesets/exons
>>>>> #you must choose mergeGroups=FALSE as described
>>>>> #above when you define your plm object, and then extract the estimates
>>>>> from it.
>>>>> #
>>>>> # cesEx <- getChipEffectSet(plmEx)
>>>>> # exFit <- extractDataFrame(cesEx,units=1:3,addNames=TRUE)
>>>>> #
>>>>> #Alternative Splicing Analysis (FIRMA)
>>>>> firma <- FirmaModel(plmTr)
>>>>> fit(firma, verbose=verbose)
>>>>> fs <- getFirmaScores(firma)
>>>>> x <- extractDataFrame(fs)
>>>>>
>>>>> On Thu, May 14, 2009 at 12:25 PM, chunjiang he <camel...@gmail.com>wrote:
>>>>>
>>>>>> Hi all,
>>>>>> I am sorry I cannot understand the path of data directory of
>>>>>> aroma.affymetrix. Such as
>>>>>>
>>>>>> annotationData/chipTypes/<chip type>/
>>>>>>
>>>>>> what does this sentence mean? where I can put mouse CDF files? I am
>>>>>> using windows vista.
>>>>>>
>>>>>> And what is the following mean:
>>>>>>
>>>>>>
>>>>>> <data set path> = <path>/<data set name>(,tag)*/
>>>>>> <array set path> = <data set path>/<chip type>/
>>>>>>
>>>>>> where I can set them?
>>>>>>
>>>>>> Thanks very much.
>>>>>>
>>>>>> jiang
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>>
>>>
>>>
>
> >
>
--~--~---------~--~----~------------~-------~--~----~
When reporting problems on aroma.affymetrix, make sure 1) to run the latest
version of the package, 2) to report the output of sessionInfo() and
traceback(), and 3) to post a complete code example.
You received this message because you are subscribed to the Google Groups
"aroma.affymetrix" group.
To post to this group, send email to aroma-affymetrix@googlegroups.com
To unsubscribe from this group, send email to
aroma-affymetrix-unsubscr...@googlegroups.com
For more options, visit this group at
http://groups.google.com/group/aroma-affymetrix?hl=en
-~----------~----~----~----~------~----~------~--~---
