[SAGEnhaft] This library does all post analysis on SAGE or is need another software for to do?
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@marcelo-luiz-de-laia-377
Last seen 9.6 years ago
Dear All, I have been downloaded the SAGEnhaft library an start to learn about it. I get the paper, as well. But, I am very confusing if I will need another software, eSAGE, SAGE2000, or another one, to do all post analysis on SAGE data set. I will have 4 data set from two experiments. Each experiments will generate two data set: one from leaves and another from stem. I read the section 2.5 from the paper and I suppose that SAGEnhaft do all analysis: extract tags, ditags, show a list with all tags, do a comparison between tow data set (leaves x stem, i.e) in some experiment... But, when I try the example in vignette i doesn't get this! I only get the errors plots. Could someone with more knowledge in this approach point me out what to do? Or how software I will need to do all analysis? Very thanks to you Marcelo
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Celine Carret ▴ 220
@celine-carret-1477
Last seen 9.6 years ago
Hi, I'm stuck remembering the way of subsetting an eset object (19 affy arrays) to accomodate only a defined list of genes that I'm interested in. I read.table(list) into R, transformed it as.matrix and use the functions: exprs(eset)[list] or exprs(eset)[as.character(list)] those functions recognize that I have 904 genes in that list, but gives me 904 NA What I would like to obtain is my 904 genes with the values for the 19 arrays, in order to assess the DE only on this subgroup as the other genes are not supposed to be expressed at this stage of the cultures I'm looking at. Could someone please point me in the right direction? Thank you very much Celine sessionInfo() Version 2.3.0 (2006-04-24) ia64-unknown-linux-gnu attached base packages: [1] "splines" "tools" "methods" "stats" "graphics" "grDevices" [7] "utils" "datasets" "base" other attached packages: affycoretools GOstats Category hgu95av2 KEGG "1.4.0" "1.6.0" "1.4.1" "1.12.0" "1.12.0" multtest genefilter survival xtable RBGL "1.10.2" "1.10.1" "2.24" "1.3-2" "1.8.1" annotate GO graph Ruuid limma "1.10.0" "1.12.0" "1.10.6" "1.9.2" "2.7.10" affy affyio Biobase "1.10.0" "0.99.3" "1.10.1" -- ---------------------------------------------------- Celine Carret PhD Pathogen Microarrays group The Wellcome Trust Sanger Institute Hinxton, Cambridge CB10 1SA, UK. tel. +44 (0)1223 494 940 fax. +44 (0)1223 494 919 email: ckc at sanger.ac.uk http://www.sanger.ac.uk/PostGenomics/PathogenArrays/
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On Thursday 05 October 2006 06:27, Celine Carret wrote: > Hi, > I'm stuck remembering the way of subsetting an eset object (19 affy > arrays) to accomodate only a defined list of genes that I'm interested in. > I read.table(list) into R, transformed it as.matrix and use the functions: > exprs(eset)[list] or > exprs(eset)[as.character(list)] > > those functions recognize that I have 904 genes in that list, but gives > me 904 NA > What I would like to obtain is my 904 genes with the values for the 19 > arrays, in order to assess the DE only on this subgroup as the other > genes are not supposed to be expressed at this stage of the cultures I'm > looking at. > Could someone please point me in the right direction? I think it might be best if you post the exact code that you used. There are several statements that will likely give errors. Can you send the input and (possibly abbreviated) output from R? Sean
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Sure, sorry: thank you C. >list <- read.table("list.txt", sep="") > class(list) [1] "data.frame" >list <- as.matrix(list) > intersect(exprs(eset), list) character(0) >intersect(exprs(eset), as.character(list)) character(0) >exprs(eset)[list] [1] NA NA NA NA .... ... [901] NA NA NA NA >dim(list) [1] 904 1 > exprs(eset)[as.character(list)] [1] NA NA NA NA .... ... [901] NA NA NA NA >head(list) V1 1 "PF11_0211" 2 "PF14_0749" 3 "PF10_0015" 4 "PFB0695c" 5 "PF14_0316" 6 "PF11_0039" Sean Davis wrote: >On Thursday 05 October 2006 06:27, Celine Carret wrote: > > >>Hi, >>I'm stuck remembering the way of subsetting an eset object (19 affy >>arrays) to accomodate only a defined list of genes that I'm interested in. >>I read.table(list) into R, transformed it as.matrix and use the functions: >>exprs(eset)[list] or >>exprs(eset)[as.character(list)] >> >>those functions recognize that I have 904 genes in that list, but gives >>me 904 NA >>What I would like to obtain is my 904 genes with the values for the 19 >>arrays, in order to assess the DE only on this subgroup as the other >>genes are not supposed to be expressed at this stage of the cultures I'm >>looking at. >>Could someone please point me in the right direction? >> >> > >I think it might be best if you post the exact code that you used. There are >several statements that will likely give errors. Can you send the input and >(possibly abbreviated) output from R? > >Sean > > > -- ---------------------------------------------------- Celine Carret PhD Pathogen Microarrays group The Wellcome Trust Sanger Institute Hinxton, Cambridge CB10 1SA, UK. tel. +44 (0)1223 494 940 fax. +44 (0)1223 494 919 email: ckc at sanger.ac.uk http://www.sanger.ac.uk/PostGenomics/PathogenArrays/
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On Thursday 05 October 2006 07:00, Celine Carret wrote: > Sure, sorry: > thank you > C. > > >list <- read.table("list.txt", sep="") > > class(list) > > [1] "data.frame" > > >list <- as.matrix(list) > > intersect(exprs(eset), list) > > character(0) > > >intersect(exprs(eset), as.character(list)) > > character(0) > > >exprs(eset)[list] exprs(eset)[as.character(list[,1]),] > [1] NA NA NA NA .... > ... > [901] NA NA NA NA > > >dim(list) > > [1] 904 1 > > > exprs(eset)[as.character(list)] > > [1] NA NA NA NA .... > ... > [901] NA NA NA NA > > >head(list) > > V1 > 1 "PF11_0211" > 2 "PF14_0749" > 3 "PF10_0015" > 4 "PFB0695c" > 5 "PF14_0316" > 6 "PF11_0039" These are not affy IDs, are they? If not, you will need to map these gene names back to affy IDs before you can use them for subsetting. It is probably worthwhile reading a bit of the Intro to R manual and, if you don't have it, consider getting a copy of the Bioconductor book. Sean
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Thanks Sean, unfortunately, it doesn't work, it says > exprs(eset)[as.character(list[,1]),] Error: subscript out of bounds as for the affy Ids, it's fine because those IDs replace the affy ID in our custom array, so these are present in the eset as stated. any other idea? best wishes, Celine >exprs(eset)[as.character(list[,1]),] > > > >>[1] NA NA NA NA .... >>... >>[901] NA NA NA NA >> >> >dim(list) >> >>[1] 904 1 >> >> > exprs(eset)[as.character(list)] >> >>[1] NA NA NA NA .... >>... >>[901] NA NA NA NA >> >> >head(list) >> >> V1 >>1 "PF11_0211" >>2 "PF14_0749" >>3 "PF10_0015" >>4 "PFB0695c" >>5 "PF14_0316" >>6 "PF11_0039" >> >> > >These are not affy IDs, are they? If not, you will need to map these gene >names back to affy IDs before you can use them for subsetting. > >It is probably worthwhile reading a bit of the Intro to R manual and, if you >don't have it, consider getting a copy of the Bioconductor book. > >Sean > > > -- ---------------------------------------------------- Celine Carret PhD Pathogen Microarrays group The Wellcome Trust Sanger Institute Hinxton, Cambridge CB10 1SA, UK. tel. +44 (0)1223 494 940 fax. +44 (0)1223 494 919 email: ckc at sanger.ac.uk http://www.sanger.ac.uk/PostGenomics/PathogenArrays/
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Hi, I suspect that your presumption about IDs is not correct. You cannot subscript from a list (and that is a really bad name for a variable) you can only subscript using vectors (any introductory material on R will tell you how to do that). There is no need to use as.character as you are doing, if the values are character strings there is no other representation possible. If your variable is a data.frame, then extract the first column which will be a character vector and will be suitable for subscripting. try using exprs(eset)[1:10,] to see what the row names really are. You can use grep on the row names (there are other functions like featureNames or geneNames that will extract these quantities so you can see them). best wishes Robert Celine Carret wrote: > Thanks Sean, > unfortunately, it doesn't work, it says > >> exprs(eset)[as.character(list[,1]),] > Error: subscript out of bounds > > as for the affy Ids, it's fine because those IDs replace the affy ID in our custom array, so these are present in the eset as stated. > > any other idea? > best wishes, > Celine > > > > >> exprs(eset)[as.character(list[,1]),] >> >> >> >>> [1] NA NA NA NA .... >>> ... >>> [901] NA NA NA NA >>> >>>> dim(list) >>> [1] 904 1 >>> >>>> exprs(eset)[as.character(list)] >>> [1] NA NA NA NA .... >>> ... >>> [901] NA NA NA NA >>> >>>> head(list) >>> V1 >>> 1 "PF11_0211" >>> 2 "PF14_0749" >>> 3 "PF10_0015" >>> 4 "PFB0695c" >>> 5 "PF14_0316" >>> 6 "PF11_0039" >>> >>> >> These are not affy IDs, are they? If not, you will need to map these gene >> names back to affy IDs before you can use them for subsetting. >> >> It is probably worthwhile reading a bit of the Intro to R manual and, if you >> don't have it, consider getting a copy of the Bioconductor book. >> >> Sean >> >> >> > -- Robert Gentleman, PhD Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 PO Box 19024 Seattle, Washington 98109-1024 206-667-7700 rgentlem at fhcrc.org
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Hi all, >You cannot subscript from a list (and that is a really bad name for a >variable) you can only subscript using vectors (any introductory >material on R will tell you how to do that). There is no need to use >as.character as you are doing, if the values are character strings there >is no other representation possible. If your variable is a data.frame, >then extract the first column which will be a character vector and will >be suitable for subscripting. Actually, her first column is probably not a character vector because the default for read.table() is to read character data in as factors - this tripped me up for a while before I figured it out. So you could change the call for read.table: gene.list <- read.table("list.txt", sep="", as.is=TRUE) Alternatively, switch to character when you extract it: gene.vector <- as.character(list[,1]) To double check whether your gene names match those in the Expression Set object, you could use: length(intersect(gene.vector, geneNames(eset)) #should be the same as length(gene.vector) Cheers, Jenny Jenny Drnevich, Ph.D. Functional Genomics Bioinformatics Specialist W.M. Keck Center for Comparative and Functional Genomics Roy J. Carver Biotechnology Center University of Illinois, Urbana-Champaign 330 ERML 1201 W. Gregory Dr. Urbana, IL 61801 USA ph: 217-244-7355 fax: 217-265-5066 e-mail: drnevich at uiuc.edu
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Hi Celine, This works for me: > exprs(eset.norm.loess)[c("1007_s_at","1053_at"),1:3] 1333_01_rep1.cel 1333_01_rep2.cel 1333_02_rep1.cel 1007_s_at 3.831777 4.275516 4.425432 1053_at 6.940475 7.138406 6.852670 So if your list of genes is a vector, I think you just put > exprs(eset)[your list,1:19] If you list is not a vector, as.vector might help. Thanks, Alex -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Celine Carret Sent: 05 October 2006 11:28 To: bioconductor at stat.math.ethz.ch Subject: [BioC] subsetting an eset object with a defined list Hi, I'm stuck remembering the way of subsetting an eset object (19 affy arrays) to accomodate only a defined list of genes that I'm interested in. I read.table(list) into R, transformed it as.matrix and use the functions: exprs(eset)[list] or exprs(eset)[as.character(list)] those functions recognize that I have 904 genes in that list, but gives me 904 NA What I would like to obtain is my 904 genes with the values for the 19 arrays, in order to assess the DE only on this subgroup as the other genes are not supposed to be expressed at this stage of the cultures I'm looking at. Could someone please point me in the right direction? Thank you very much Celine sessionInfo() Version 2.3.0 (2006-04-24) ia64-unknown-linux-gnu attached base packages: [1] "splines" "tools" "methods" "stats" "graphics" "grDevices" [7] "utils" "datasets" "base" other attached packages: affycoretools GOstats Category hgu95av2 KEGG "1.4.0" "1.6.0" "1.4.1" "1.12.0" "1.12.0" multtest genefilter survival xtable RBGL "1.10.2" "1.10.1" "2.24" "1.3-2" "1.8.1" annotate GO graph Ruuid limma "1.10.0" "1.12.0" "1.10.6" "1.9.2" "2.7.10" affy affyio Biobase "1.10.0" "0.99.3" "1.10.1" -- ---------------------------------------------------- Celine Carret PhD Pathogen Microarrays group The Wellcome Trust Sanger Institute Hinxton, Cambridge CB10 1SA, UK. tel. +44 (0)1223 494 940 fax. +44 (0)1223 494 919 email: ckc at sanger.ac.uk http://www.sanger.ac.uk/PostGenomics/PathogenArrays/ _______________________________________________ Bioconductor mailing list Bioconductor at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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