Annotation packages: Which Unigene Release?
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Aedin Culhane ▴ 310
@aedin-culhane-500
Last seen 10.3 years ago
Hi, I have searched the FAQ but can't find the answer to this question. How can I find out which Unigene Release was used in the creation of an annotation package. For example I am using hgu133plus2 release 1.8.4 (17th May 2005). Was this created with Unigene Release 183 or 184? Thanks a million Aedin
hgu133plus2 hgu133plus2 • 1.1k views
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John Zhang ★ 2.9k
@john-zhang-6
Last seen 10.3 years ago
>I have searched the FAQ but can't find the answer to this question. > >How can I find out which Unigene Release was used in the creation of an >annotation package. > >For example I am using hgu133plus2 release 1.8.4 (17th May 2005). Was >this created with Unigene Release 183 or 184? Unigene was used only for mapping probe ids to Entrez Gene ids for the ESTs and the release version is thus not recorded in the metadata packages. > >Thanks a million >Aedin > >_______________________________________________ >Bioconductor mailing list >Bioconductor@stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor Jianhua Zhang Department of Medical Oncology Dana-Farber Cancer Institute 44 Binney Street Boston, MA 02115-6084
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Thanks for the info on my last question. Can I please ask another ;-)) What do you recommend to use when mapping IMAGE ID's and Affy ID's. UniGene and locus link are returning some very strange results (not a surprise really :-)). I know match probes maps between Affy batches. Can I load IMAGE sequences into this to map to a Affy cdf package. Is there any example of this in the BioC help? Thanks again BioC for all your help, Aedin
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Hi Aedin, Aedin wrote: > Thanks for the info on my last question. Can I please ask another ;-)) > > What do you recommend to use when mapping IMAGE ID's and Affy ID's. > UniGene and locus link are returning some very strange results (not a > surprise really :-)). > It depends a lot on what you are trying to do. If you are trying to combine different data sets, then you probably want to match on sequence - which sounds like what you are suggesting below. You might also want to look at MergeMaid, and accompanying papers, as they have an interesting approach that might help. I don' think that there is an example of taking a sequence, say for a cDNA and then finding whether a corresponding affy probe set map to a similar region, but once you are done I'm sure you will contribute one :-) I would use Biostrings, and the corresponding Affy probe package - and do exact matching. If you end up with many-to-many or many-to-one matches I would match them all and then pick the best one. some code snippets, library(annotate) library(hgu95av2probe) ##here you would use the Acc. Num for the gen of interest myseq = getSEQ("D45132") ##here you would use the Affy probe id, for the putative match wp= hgu95av2probe$Probe.Set.Name == "316_g_at" myPr = hgu95av2probe[wp,] nchar(myseq) library(Biostrings) mybs = NucleotideString(myseq, "DNA") ##do this once for each of the probes - and count how many actually ##match match1 = matchDNAPattern(as.character(myPr[1,1]), mybs) as.matrix(match1) Does that help? Robert > I know match probes maps between Affy batches. Can I load IMAGE > sequences into this to map to a Affy cdf package. Is there any example > of this in the BioC help? > > Thanks again BioC for all your help, > Aedin > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor >
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> I don' think that there is an example of taking a sequence, say for a > cDNA and then finding whether a corresponding affy probe set map to a > similar region The following series of papers outlines how to do this and what the effects are: Most Recently- Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements. BMC Bioinformatics. 2005 Apr 25;6(1):107. PMID: 15850491 [PubMed - in process] Which builds upon- Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements. Nucleic Acids Res. 2004 May 25;32(9):e74. PMID: 15161944 [PubMed - indexed for MEDLINE]
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