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@mayte-suarez-farinas-694
Last seen 9.6 years ago
Hi ! I got the following message while running AnnBPkgBuilder function. Couls somebody tell me what is going on ??? Warning message: cannot open: HTTP status was `404 Not Found' Error in loadFromUrl(srcUrl) : URL http://www.genome.ucsc.edu/goldenPath/hg17/da tabase/refLink.txt.gz is incorrect or the target site is not responding! Error in ABPkgBuilder(baseName = file.path(myDir, "AnnTh"), srcUrls = getSrcUrl( "ALL", : Failed to parse Golden Path data because of: Error in loadFromUrl(srcUrl) : URL http://www.genome.ucsc.edu/goldenPath/hg17/d atabase/refLink.txt.gz is incorrect or the target site is not responding! -- Mayte Suarez Farinas The Rockefeller University 1230 York Avenue, Box 212 New York, NY 10021 phone: 1-212-327-8186 fax: 1-212-327-7422
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@pjaresclinicubes-798
Last seen 9.6 years ago
Hi! I am a new user of affypackage and limma. When I run rma or mas in affy package I get the following messages: Bacground correcting.....error=cannot allocate vector of size 75249kb In addition:warning messages: 1: "multiget" is deprecated use "mget" instead 2 Reached total allocation of 511B: see help (memory.size) Anybody could give some advice ? Thank you Pedro Jares, Ph.D. Genomics Unit, IDIBAPS Barcelona University C/ Villarroel 170, 08036 .Barcelona, Spain Telf. 93 2275400, Ext 2184 o 2129 Fax 93 2275717
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@james-w-macdonald-5106
Last seen 3 hours ago
United States
Hi Pedro, That error means you are running out of memory. If you are using a windows system, you may simply need to allocate more RAM to R by adding --max-mem-size=<amount of="" ram="" you="" have="" in="" megabytes="">M to the target field for your R shortcut. For instance, I have 2 Gb RAM, so I have --max-mem-size=2000M. If you are on some unix-type system (including Mac OSX), then you simply need to get more RAM, or if that is not possible, try justRMA(), which uses much less RAM. Best, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> <pjares@clinic.ub.es> 06/07/04 08:42AM >>> Hi! I am a new user of affypackage and limma. When I run rma or mas in affy package I get the following messages: Bacground correcting.....error=cannot allocate vector of size 75249kb In addition:warning messages: 1: "multiget" is deprecated use "mget" instead 2 Reached total allocation of 511B: see help (memory.size) Anybody could give some advice ? Thank you Pedro Jares, Ph.D. Genomics Unit, IDIBAPS Barcelona University C/ Villarroel 170, 08036 .Barcelona, Spain Telf. 93 2275400, Ext 2184 o 2129 Fax 93 2275717 _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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Simon Kidd ▴ 180
@simon-kidd-706
Last seen 9.6 years ago
Hi, We are CLI challenged so we have been using affylmgui for our analysis. Our analysis has been to make three comparisons and then to look at the genes which are in common between the three. Affylmgui allows one to visually see the result of the comparison with a Venn diagram, we would like to get a list of the genes (and appropriate statistics) in the various intersections. Is there a way of doing this? thanks, Simon
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Hi Simon, No sorry, there is no way at the moment to get a list of genes from the venn diagram in affylmGUI, but depending on how "CLI challenged" you are, you could ask on this mailing list about doing this using the limma functions classifyTestsF and vennCounts and combining this information with your list of probe set IDs from the CDF package or gene names from the annotation package. It is certainly possible to extract this information (at the command-line) from affylmGUI data objects, but I don't have time to try this out right now, so if you ask on the mailing list about how to do it at the command-line with limma and affy, then I can easily explain how to translate the solution for use with affylmGUI. You might want to look at the extract.pdf vignette in affylmGUI. Regards, James On Wed, 16 Jun 2004, Simon Kidd wrote: > Hi, > > We are CLI challenged so we have been using affylmgui for our > analysis. Our analysis has been to make three comparisons and then to > look at the genes which are in common between the three. Affylmgui > allows one to visually see the result of the comparison with a Venn > diagram, we would like to get a list of the genes (and appropriate > statistics) in the various intersections. Is there a way of doing > this? > > thanks, > > Simon > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor > -- ---------------------------------------------------------------------- ---- James Wettenhall Tel: (+61 3) 9345 2629 Division of Genetics and Bioinformatics Fax: (+61 3) 9347 0852 The Walter & Eliza Hall Institute E-mail: wettenhall@wehi.edu.au of Medical Research, Mobile: (+61 / 0 ) 438 527 921 1G Royal Parade, Parkville, Vic 3050, Australia http://www.wehi.edu.au
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At 10:29am +1000 17/6/04, James Wettenhall wrote: >Hi Simon, > >No sorry, there is no way at the moment to get a list of genes >from the venn diagram in affylmGUI, but depending on how >"CLI challenged" you are, you could ask on this mailing list >about doing this using the limma functions classifyTestsF and >vennCounts and combining this information with your list of >probe set IDs from the CDF package or gene names from the >annotation package. James, Do the p values that affylmgui uses to calculate the venn diagram correspond to those given in the toptable lists? If this is so we should be able to get the same results by exporting the toptable lists into Filemaker and doing various sorts there. thanks. Simon
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On Thu, 17 Jun 2004, Simon Kidd wrote: > Do the p values that affylmgui uses to calculate the venn diagram > correspond to those given in the toptable lists? No, not exactly. (But I'm not an expert on this, so others may wish to correct me or clarify this further.) See the p.value argument in ?classifyTestsF and compare with the p.value in the object returned by eBayes (see ?eBayes). > If this is so we > should be able to get the same results by exporting the toptable > lists into Filemaker and doing various sorts there. Of course, you are welcome to export topTables and manually find genes which are above a certain cutoff in more than one topTable, but this will generally underestimate the number of genes in the intersection. classifyTestsF/vennCounts uses a more sophisticated method to count the genes in the intersection. Imagine a plot where you have a moderated t statistic for one contrast on a horizontal axis, and a moderated t statistic for another moderated t statistic on the other axis. If you want genes which are up-regulated in both contrats, you could just look for genes with t1 > 4 and t2 > 4, so the selected region on the t1,t2 plot would have a rectangular boundary. Whereas the classifyTestsF/vennCounts approach uses a curved boundary to decide which genes are up-regulated in both conditions. Thanks Anthony for the quick example of some venn diagram code in R, which was probably a response to my last post. But I was looking for something which actually used limma's classifyTestsF and vennCounts. The example in the help for ?vennCounts is: tstat <- matrix(rt(300,df=10),100,3) tstat[1:33,] <- tstat[1:33,]+2 clas <- classifyTestsF(tstat,df=10,p.value=0.05) a <- vennCounts(clas) So in your case, you need to get the tstat from affylmGUI. Let's say you have saved an .RData file from File-Save As in affylmGUI, called "affyDataContrastsComputed.lma" Now, load this file into a new R session: load("affyDataContrastsComputed.lma") Then extract the moderated t statistics of interest, after reading extract.pdf in the doc/ subdirectory of affylmGUI, in particular, please read the following lines: For example, the moderated t statistics can be obtained as follows: > ContrastParameterizationList[[1]]$eb$t tstat <- ContrastParameterizationList[[1]]$eb$t Then you can use the ?vennCounts example above. After you have computed your vennCounts object (called 'a' above), you can combine it with your probe set IDs as follows: geneIDs <- ls(getCdfInfo(RawAffyData)) where RawAffyData is an AffyBatch object. class(a) <- "matrix" data.frame(geneIDs=geneIDs,a) This should give you the list of genes in the intersection. Apologies for using the old limma style of storing the empirical bayes statistics in a separate object "eb" rather than "fit", but generally this sort of thing is updated much more gradually in the GUI compared with limma. Hope this helps, James ---------------------------------------------------------------------- ---- James Wettenhall Tel: (+61 3) 9345 2629 Division of Genetics and Bioinformatics Fax: (+61 3) 9347 0852 The Walter & Eliza Hall Institute E-mail: wettenhall@wehi.edu.au of Medical Research, Mobile: (+61 / 0 ) 438 527 921 1G Royal Parade, Parkville, Vic 3050, Australia http://www.wehi.edu.au
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At 12:57pm +1000 18/6/04, James Wettenhall wrote: >On Thu, 17 Jun 2004, Simon Kidd wrote: >> Do the p values that affylmgui uses to calculate the venn diagram > > correspond to those given in the toptable lists? > >class(a) <- "matrix" >data.frame(geneIDs=geneIDs,a) > >This should give you the list of genes in the intersection. Thanks, This worked right upto the end where it gave me the following error message: > data.frame(geneIDs=geneIDs,a) Error in data.frame(geneIDs = geneIDs, a) : arguments imply differing number of rows: 14010, 8 Iam wondering is this because we have only three contrasts set up encompassing four targets but the targets file contains additional target entries? Another possibility is that we are using probeID's, there seems to be no corresponding geneID's for Drosophila. Simon
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On Fri, 18 Jun 2004, Simon Kidd wrote: > >class(a) <- "matrix" > >data.frame(geneIDs=geneIDs,a) > This worked right upto the end where it gave me the following error message: > > > data.frame(geneIDs=geneIDs,a) > Error in data.frame(geneIDs = geneIDs, a) : > arguments imply differing number of rows: 14010, 8 Sorry, my mistake. What you need to use in the data.frame is the 'clas' object from classifyTestsF, not the 'a' object from vennCounts. clas <- classifyTestsF(tstat,df=10,p.value=0.05) class(clas) <- "matrix" data.frame(geneIDs=geneIDs,clas) Hope this helps, James
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At 11:51am +1000 19/6/04, James Wettenhall wrote: >On Fri, 18 Jun 2004, Simon Kidd wrote: >> >class(a) <- "matrix" >> >data.frame(geneIDs=geneIDs,a) > >> This worked right upto the end where it gave me the following error message: >> >> > data.frame(geneIDs=geneIDs,a) >> Error in data.frame(geneIDs = geneIDs, a) : >> arguments imply differing number of rows: 14010, 8 > >Sorry, my mistake. What you need to use in the data.frame is >the 'clas' object from classifyTestsF, not the 'a' object >from vennCounts. > >clas <- classifyTestsF(tstat,df=10,p.value=0.05) >class(clas) <- "matrix" >data.frame(geneIDs=geneIDs,clas) With this I get a slightly different error message, here is what I typed and the error message: -------------- load("rma.lma") tstat <- ContrastParameterizationList[[1]]$eb$t tstat <- matrix(rt(300,df=10),100,3) tstat[1:33,] <- tstat[1:33,]+2 clas <- classifyTestsF(tstat,df=10,p.value=0.05) a <- vennCounts(clas) geneIDs <- ls(getCdfInfo(RawAffyData)) class(clas) <- "matrix" data.frame(geneIDs=geneIDs,clas) Error in data.frame(geneIDs = geneIDs, clas) : arguments imply differing number of rows: 14010, 100 ------------- I dont know if it matters but I have eight targets of which only four are used for contrasts, will that make a difference? thanks for your help. Simon
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Simon, Please check your steps one and a time and find out where the '100' comes from. I would suspect that you have accidentally defined tstat from the ?vennCounts example in limma instead of using: tstat <- ContrastParameterizationList[[1]]$eb$t as described in affylmGUI/doc/extract.pdf. Here's an example where I run classifyTestsF on a file "EstrogenContrastsComputed.lma" which I have saved from affylmGUI: > library(affy) # for getCdfInfo method > load("EstrogenContrastsComputed.lma") > tstat <- ContrastParameterizationList[[1]]$eb$t > nrow(tstat) [1] 12625 > clas <- classifyTestsF(tstat,df=10,p.value=0.05) > nrow(clas) [1] 12625 > clas[1:10,] # Just look at the first ten rows. Contrast1 Contrast2 Contrast3 [1,] 0 0 0 [2,] 0 0 0 [3,] 0 0 0 [4,] 0 0 0 [5,] 0 0 0 [6,] 0 0 0 [7,] -1 -1 -1 [8,] 0 0 0 [9,] 0 0 0 [10,] 0 0 0 We see that the 7th gene (out of 12625) is down-regulated in all three contrasts. To find out which gene that is look at geneIDs, e.g. defined from getCdfInfo(RawAffyData) or use data.frame(geneIDs,clas) to combine the geneIDs with the classification. Hope this helps, James On Sat, 19 Jun 2004, Simon Kidd wrote: > >Sorry, my mistake. What you need to use in the data.frame is > >the 'clas' object from classifyTestsF, not the 'a' object > >from vennCounts. > > > >clas <- classifyTestsF(tstat,df=10,p.value=0.05) > >class(clas) <- "matrix" > >data.frame(geneIDs=geneIDs,clas) > > With this I get a slightly different error message, here is what I > typed and the error message: > -------------- > load("rma.lma") > tstat <- ContrastParameterizationList[[1]]$eb$t > tstat <- matrix(rt(300,df=10),100,3) > tstat[1:33,] <- tstat[1:33,]+2 > clas <- classifyTestsF(tstat,df=10,p.value=0.05) > a <- vennCounts(clas) > geneIDs <- ls(getCdfInfo(RawAffyData)) > class(clas) <- "matrix" > data.frame(geneIDs=geneIDs,clas) > > Error in data.frame(geneIDs = geneIDs, clas) : arguments imply > differing number of rows: 14010, 100 > > ------------- > > I dont know if it matters but I have eight targets of which only four > are used for contrasts, will that make a difference? > > thanks for your help. > > Simon > > >
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