Thank you > From: Marc Carlson <mcarlson at="" fhcrc.org=""> > Date: Fri, 10 Jul 2009 08:46:36 -0700 > To: Loren Engrav <engrav at="" u.washington.edu=""> > Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at="" stat.math.ethz.ch=""> > Subject: Re: [BioC] Changes in annotations? > > Hi Loren, > > I am working on this right now. But it is really not as simple as it > sounds. I hope to have more to say about this very soon. > > > Marc > > > > Loren Engrav wrote: >> Thank you >> >> Why is it not "best" to include everything Affy includes? All the synonyms >> and IDs >> >> Or is this not software possible? >> >> >> >> >>> From: "James W. MacDonald" <jmacdon at="" med.umich.edu=""> >>> Date: Thu, 09 Jul 2009 09:36:46 -0400 >>> To: Alex Sanchez <asanchez at="" ub.edu=""> >>> Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at="" stat.math.ethz.ch=""> >>> Subject: Re: [BioC] Changes in annotations? >>> >>> Hi Alex, >>> >>> We have taken this up as an internal topic of discussion and hopefully >>> will be able to come up with a solution that is a bit better than what >>> we are doing right now. >>> >>> However, some of this is going to be unavoidable. The chips were based >>> on UniGene build 133 (and we are now on build 219), so things are going >>> to tend to move around. But I don't think this is the main reason for >>> what you are seeing, as the latest Affy annotation file is still based >>> on UCSC build hg18 (which is based on NCBI build 36.1), so these data >>> are over three years old. >>> >>> Instead, it appears that Affy have changed something about how they are >>> annotating things. Some of this is an improvement, and some not so much. >>> >>> For instance, 203315_at does interrogate NCK2: >>> >>> http://genome.ucsc.edu/cgi- bin/hgTracks?insideX=115&revCmplDisp=0&hgsid=1365 >>> 10 >>> 693&hgt.out3=10x&position=chr2%3A105876577-105876826&hgtgroup_map_ close=0&hg >>> tg >>> roup_phenDis_close=1&hgtgroup_genes_close=0&hgtgroup_rna_close=0&h gtgroup_ex >>> pr >>> ession_close=1&hgtgroup_regulation_close=0&hgtgroup_compGeno_close =0&hgtgrou >>> p_ >>> varRep_close=0&hgtgroup_encodeGenes_close=1&hgtgroup_encodeTxLevel s_close=1& >>> hg >>> tgroup_encodeChip_close=1&hgtgroup_encodeChrom_close=1&hgtgroup_en codeCompAn >>> dV >>> ar_close=1 >>> >>> whereas 232583_at does not: >>> >>> http://genome.ucsc.edu/cgi- bin/hgTracks?insideX=115&revCmplDisp=0&hgsid=1365 >>> 10 >>> 693&hgt.out3=10x&position=chr2%3A105752637-105752886&hgtgroup_map_ close=0&hg >>> tg >>> roup_phenDis_close=1&hgtgroup_genes_close=0&hgtgroup_rna_close=0&h gtgroup_ex >>> pr >>> ession_close=1&hgtgroup_regulation_close=0&hgtgroup_compGeno_close =0&hgtgrou >>> p_ >>> varRep_close=0&hgtgroup_encodeGenes_close=1&hgtgroup_encodeTxLevel s_close=1& >>> hg >>> tgroup_encodeChip_close=1&hgtgroup_encodeChrom_close=1&hgtgroup_en codeCompAn >>> dV >>> ar_close=1 >>> >>> so in this case they have improved their annotations. >>> >>> In the case of 238900_at, they seem to have added in a bunch of EG IDs >>> that are based on a model rather than being actual reviewed genes. In >>> addition, that probeset seems to hit an intron, so adding in all this >>> other annotation appears pointless: >>> >>> http://genome.ucsc.edu/cgi- bin/hgTracks?insideX=115&revCmplDisp=0&hgsid=1365 >>> 11 >>> 081&hgt.out3=10x&position=chr6%3A32653723-32653972&hgtgroup_map_cl ose=0&hgtg >>> ro >>> up_phenDis_close=1&hgtgroup_genes_close=0&hgtgroup_rna_close=0&hgt group_expr >>> es >>> sion_close=1&hgtgroup_regulation_close=0&hgtgroup_compGeno_close=0 &hgtgroup_ >>> va >>> rRep_close=0&hgtgroup_encodeGenes_close=1&hgtgroup_encodeTxLevels_ close=1&hg >>> tg >>> roup_encodeChip_close=1&hgtgroup_encodeChrom_close=1&hgtgroup_enco deCompAndV >>> ar >>> _close=1 >>> >>> What this really comes down to is the fact that you can't take anything >>> for granted. Not only do you have to validate a set of significant >>> results using some other technology, you also need to ensure that the >>> chip you are using is actually measuring what you think prior to doing >>> the validation. >>> >>> It should be relatively painless to set up a pipeline where you could >>> use the BSgenome.Hsapiens.UCSC.hg18 package along with functions from >>> BSgenome/Biostrings to map probesets to the genome and then use the >>> org.Hs.eg.db package to see if a given probeset is even interrogating >>> the gene it is supposed to. One could then use rtracklayer to visualize >>> things in the UCSC genome browser to make sure you weren't interrogating >>> an intron. >>> >>> Best, >>> >>> Jim >>> >>> >>> >>> >>> Alex Sanchez wrote: >>> >>>> Hi James and thanks for the help. >>>> >>>> I know, of course, that what Bioconductor does is to take the >>>> annotations from public data sources. >>>> I will now turn to affymetrix to see if someone there, or in their >>>> forums, can explain why so many annotations have been turned into "NA's" >>>> >>>> There seem to be two problems here >>>> - The first one, pointed by Loren in his message today is synonims. For >>>> instance the first probeset in my list was 238900_at, >>>> In the first version I used (BioC 1.9) the Gene Symbol provide by >>>> getSymbol was HLA-DRB1 whereas now (BioC 2.4) it is LOC100133484 >>>> However the original symbol is still in the Affymetrix annotation file >>>> "HG-U133_Plus_2.na28.annot.csv". It seems as if the new symbol is intended >>>> to show the relation with the new Entrez ID (100133484). >>>> In any case it is ennoying but it can be assumed. >>>> - What seems worse is what happens to some annotations: If, for >>>> instance, I take the second probeset in my list, 232583_at, and I look >>>> for it in the affy annotations file I find that apart some links to >>>> databases as genebank it does not have a gene symbol or an entrez (or >>>> most annotations anymore). >>>> In the previous version of the annotations this probeset was one of two >>>> associated with gene NCK2 (232583_at;203315_at) . >>>> The problem is that the second probeset (203315_at) was not selected by >>>> the analysis. That is the only evidence suggesting that gene NCK2 was >>>> differentially expressed (232583_at) does not suggest it anymore. >>>> >>>> Last, but in any case least, this is not happening to a few probesets. >>>> My original list had 417 probesets. 210 have changed/synonimized their >>>> gene symbols, but from these 210, 160 have become NA's >>>> >>>> Seems too many to feel comfortable :-( >>>> >>>> Thanks for the help >>>> >>>> Alex >>>> >>>> ................................................................. .......... >>>> .. >>>> .................................. >>>> >>>> Dr. Alex S?nchez. >>>> Associate Professor. Statistics Department. University of Barcelona. >>>> Facultat de Biologia UB. Avda Diagonal 645. 08028 Barcelona. Spain >>>> asanchez_at_ub.edu >>>> Statistics and Bioinformatics Unit >>>> Institut de Recerca. Hospital Universitari Vall 'Hebron >>>> Passeig Vall d'Hebron 112-119. 08034 Barcelona >>>> asanchez_at_ir.vhebron.net >>>> ................................................................. .......... >>>> .. >>>> .................................. >>>> >>>> >>>> >>>> >>>> >>>> ----- Original Message ----- From: "James W. MacDonald" >>>> <jmacdon at="" med.umich.edu=""> >>>> To: "Alex Sanchez" <asanchez at="" ub.edu=""> >>>> Cc: <bioconductor at="" stat.math.ethz.ch=""> >>>> Sent: Monday, July 06, 2009 3:58 PM >>>> Subject: Re: [BioC] Changes in annotations? >>>> >>>> >>>> >>>>> Hi Alex, >>>>> >>>>> This is a question that comes up on the Bioc list fairly regularly, >>>>> and the answer is in two parts: >>>>> >>>>> First, the annotations supplied in the various metadata packages >>>>> supplied by BioC are *not* our annotations, but are simply a >>>>> re-packaging of data we collect from various sources. As an example, >>>>> we use the mappings of Affymetrix Probe ID to Entrez Gene ID from the >>>>> annotation csv files you can download from the Affy website. We then >>>>> map the Entrez Gene IDs to other annotation using primarily NCBI data. >>>>> So if you go to Affy's netaffx site (free registration required) and >>>>> query on say, 238900_at, you get this: >>>>> >>>>> https://www.affymetrix.com/analysis/netaffx/fullrecord.affx?pk =HG-U133_PLU >>>>> S_ >>>>> 2%3A238900_AT >>>>> >>>>> >>>>> And you will note that the first Entrez Gene ID listed there is >>>>> 100133484, which happens to be a defunct ID. However, this is the >>>>> first of many listed there (and we need a one-to-one mapping), so we >>>>> chose that one. A more likely Entrez Gene ID can be found further down >>>>> the list, but we simply don't have the resources to figure out if >>>>> there is a better choice in that list (for every reporter on every >>>>> Affy chip we annotate). Nor do we have the resources to ensure that >>>>> any of the mappings that Affy make are reasonable to begin with. We >>>>> have to trust that they (with *way* more resources that us) are doing >>>>> a reasonable job. >>>>> >>>>> The second part of the answer has to do with the 'moving target' >>>>> aspect of Biological annotations. These data change all the time, and >>>>> there is the recurring question of whether one should do an analysis >>>>> and 'freeze' it to that point in time, or should the annotations be >>>>> updated on a regular basis, with the realization that things can and >>>>> will change? >>>>> >>>>> Without looking at each reporter ID you list, I can't say if the >>>>> changes are due to Affy changing their annotation csv files, or to >>>>> changing knowledge of the genome, but I suspect it is a combination of >>>>> the two. >>>>> >>>>> Best, >>>>> >>>>> Jim >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> Alex Sanchez wrote: >>>>> >>>>>> Hello >>>>>> >>>>>> I have had to review recently an analysis I did some time ago. This >>>>>> was done on affymetrix hgu133plus2 chips with R 2.4 and BioC 1.9 I >>>>>> have re-run the analyses using R 2.9 and BioC 2.4 (sessionInfo below). >>>>>> I have been surprised by the changes in the annotations: Many >>>>>> probesets that had had an annotation have become NA's whereas some >>>>>> have changed their symbol and their Entrez gene. >>>>>> >>>>>> To be specific I summarize my question with the top genes of my list >>>>>> >>>>>> The list I obtained 2 years ago is: >>>>>> >>>>>> probeset locuslink symbol >>>>>> 238900_at 3123 HLA-DRB1 >>>>>> 232583_at 8440 NCK2 >>>>>> 236307_at 60468 BACH2 >>>>>> 223620_at 2857 GPR34 >>>>>> 219759_at 64167 LRAP >>>>>> 201702_s_at 5514 PPP1R10 >>>>>> 232882_at 2308 FOXO1A >>>>>> 213446_s_at 8826 IQGAP1 >>>>>> 234033_at 9693 RAPGEF2 >>>>>> 243006_at 2534 FYN >>>>>> 244648_at 54520 CCDC93 >>>>>> 243691_at 23142 DCUN1D4 >>>>>> 239264_at 60412 EXOC4 >>>>>> 243546_at 143686 SESN3 >>>>>> 205239_at 374 AREG >>>>>> 1565703_at 55520 ELAC1 >>>>>> 244061_at 55843 ARHGAP15 >>>>>> 230505_at 26037 SIPA1L1 >>>>>> 242688_at 9320 TRIP12 >>>>>> 1556474_a_at 285097 FLJ38379 >>>>>> 232614_at 596 BCL2 >>>>>> 1565689_at 3839 KPNA3 >>>>>> 236685_at NA NA >>>>>> 225173_at 93663 ARHGAP18 >>>>>> 241893_at 4249 MGAT5 >>>>>> >>>>>> I used the following code to reproduce the issue with the annotations: >>>>>> >>>>>> >>>>>> ##################################################################### >>>>>> ## Verification using R 2.9 & BioC 2.4 >>>>>> ##################################################################### >>>>>> >>>>>> >>>>>>> probes<-c("238900_at" , "232583_at", "236307_at" ,"223620_at" , >>>>>>> "219759_at" , >>>>>>> >>>>>> + "201702_s_at" , "232882_at" , "213446_s_at", "234033_at", >>>>>> "243006_at" , + "244648_at" , "243691_at" , "239264_at" , >>>>>> "243546_at" , "205239_at" , >>>>>> + "1565703_at" , "244061_at" , "230505_at" , "242688_at" , >>>>>> "1556474_a_at", >>>>>> + "232614_at" , "1565689_at" , "236685_at" , "225173_at" , >>>>>> "241893_at") >>>>>> >>>>>>> library(hgu133plus2.db) >>>>>>> library(annotate) >>>>>>> >>>>>>> entrezs<- getEG(probes, "hgu133plus2") >>>>>>> symbols<- getSYMBOL(probes, "hgu133plus2") >>>>>>> sel2<- cbind(probes, entrezs, symbols) >>>>>>> sel2 >>>>>>> >>>>>> probes entrezs symbols 238900_at >>>>>> "238900_at" "100133484" "LOC100133484" >>>>>> 232583_at "232583_at" NA NA 236307_at >>>>>> "236307_at" NA NA 223620_at "223620_at" >>>>>> "2857" "GPR34" 219759_at "219759_at" "64167" >>>>>> "ERAP2" 201702_s_at "201702_s_at" "5514" "PPP1R10" >>>>>> 232882_at "232882_at" NA NA 213446_s_at >>>>>> "213446_s_at" "8826" "IQGAP1" 234033_at "234033_at" >>>>>> NA NA 243006_at "243006_at" NA NA >>>>>> 244648_at "244648_at" NA NA 243691_at >>>>>> "243691_at" NA NA 239264_at "239264_at" >>>>>> NA NA 243546_at "243546_at" NA NA >>>>>> 205239_at "205239_at" "374" "AREG" 1565703_at >>>>>> "1565703_at" "4089" "SMAD4" 244061_at "244061_at" >>>>>> NA NA 230505_at "230505_at" "145474" "LOC145474" >>>>>> 242688_at "242688_at" NA NA 1556474_a_at >>>>>> "1556474_a_at" "285097" "FLJ38379" 232614_at "232614_at" >>>>>> NA NA 1565689_at "1565689_at" NA NA >>>>>> 236685_at "236685_at" NA NA 225173_at >>>>>> "225173_at" "93663" "ARHGAP18" 241893_at "241893_at" >>>>>> NA NA >>>>>> >>>>>>> sessionInfo() >>>>>>> >>>>>> R version 2.9.0 (2009-04-17) i386-pc-mingw32 locale: >>>>>> LC_COLLATE=English_United States.1252;LC_CTYPE=English_United >>>>>> States.1252;LC_MONETARY=English_United >>>>>> States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 >>>>>> >>>>>> attached base packages: >>>>>> [1] stats graphics grDevices utils datasets methods base >>>>>> other attached packages: >>>>>> [1] annotate_1.22.0 hgu133plus2.db_2.2.11 RSQLite_0.7-1 >>>>>> DBI_0.2-4 AnnotationDbi_1.6.0 Biobase_2.4.1 >>>>>> loaded via a namespace (and not attached): >>>>>> [1] xtable_1.5-5 >>>>>> ############################################# >>>>>> >>>>>> Many probesets seem to have changed. >>>>>> Can someone explain to me what is happening (or what may I be doing >>>>>> wrong)? >>>>>> >>>>>> The same code does not work with R 2.4 but if I change hgu133plus2.db >>>>>> by hgu133plus2 and getEG by getLL I obtain the original results: >>>>>> >>>>>> ############################################### >>>>>> ### Review of annotatons with R 2.4 and BioC 1.9 >>>>>> ############################################### >>>>>> >>>>>> ### This code is executed on a clean new session with R 2. and BioC 1.9 >>>>>> >>>>>> >>>>>>> probes<-c("238900_at" , "232583_at", "236307_at" ,"223620_at" , >>>>>>> "219759_at" , >>>>>>> >>>>>> + "201702_s_at" , "232882_at" , "213446_s_at", "234033_at", >>>>>> "243006_at" , + "244648_at" , "243691_at" , "239264_at" , >>>>>> "243546_at" , "205239_at" , >>>>>> + "1565703_at" , "244061_at" , "230505_at" , "242688_at" , >>>>>> "1556474_a_at", >>>>>> + "232614_at" , "1565689_at" , "236685_at" , "225173_at" , >>>>>> "241893_at") >>>>>> >>>>>>> LLs<- getLL(rownames(sel), "hgu133plus2") >>>>>>> symbols<- getSYMBOL(rownames(sel), "hgu133plus2") >>>>>>> sel1<- cbind(probes, LLs, symbols) >>>>>>> sel1 >>>>>>> >>>>>> probes LLs symbols 238900_at >>>>>> "238900_at" "3123" "HLA-DRB1" 232583_at "232583_at" "8440" >>>>>> "NCK2" 236307_at "236307_at" "60468" "BACH2" 223620_at >>>>>> "223620_at" "2857" "GPR34" 219759_at "219759_at" "64167" >>>>>> "ERAP2" 201702_s_at "201702_s_at" "5514" "PPP1R10" 232882_at >>>>>> "232882_at" "2308" "FOXO1" 213446_s_at "213446_s_at" "8826" >>>>>> "IQGAP1" 234033_at "234033_at" "9693" "RAPGEF2" 243006_at >>>>>> "243006_at" "2534" "FYN" 244648_at "244648_at" "54520" >>>>>> "CCDC93" 243691_at "243691_at" "23142" "DCUN1D4" 239264_at >>>>>> "239264_at" "60412" "EXOC4" 243546_at "243546_at" "143686" >>>>>> "SESN3" 205239_at "205239_at" "374" "AREG" 1565703_at >>>>>> "1565703_at" "4089" "SMAD4" 244061_at "244061_at" "55843" >>>>>> "ARHGAP15" 230505_at "230505_at" "145474" "LOC145474" >>>>>> 242688_at "242688_at" "9320" "TRIP12" 1556474_a_at >>>>>> "1556474_a_at" "285097" "FLJ38379" 232614_at "232614_at" "596" >>>>>> "BCL2" 1565689_at "1565689_at" "3839" "KPNA3" 236685_at >>>>>> "236685_at" NA NA 225173_at "225173_at" >>>>>> "93663" "ARHGAP18" 241893_at "241893_at" "4249" "MGAT5" >>>>>> >>>>>>> sessionInfo() >>>>>>> >>>>>> R version 2.4.1 (2006-12-18) i386-pc-mingw32 locale: >>>>>> LC_COLLATE=Spanish_Spain.1252;LC_CTYPE=Spanish_Spain.1252;LC_MO NETARY=Spa >>>>>> ni >>>>>> sh_Spain.1252;LC_NUMERIC=C;LC_TIME=Spanish_Spain.1252 >>>>>> >>>>>> >>>>>> attached base packages: >>>>>> [1] "tools" "stats" "graphics" "grDevices" >>>>>> [5] "utils" "datasets" "methods" "base" other attached >>>>>> packages: >>>>>> annotate Biobase hgu133plus2 "1.12.1" "1.12.2" "1.14.0" >>>>>> ######################################################## >>>>>> >>>>>> In summary. If I use R 2.4/BioC 1.9 I obtain the same results I >>>>>> ibtained 2 years ago, but If I do the same steps using R2.9/BioC2.4 >>>>>> the results change dramatically. >>>>>> I have repeated the analyses using BioC 2.01 in R 2.7 and BioC 2.2 in >>>>>> R 2.8 (results not shown here). BioC 2.0 yield the same as 1.9 and >>>>>> BioC 2.2 the same as 2.4, >>>>>> >>>>>> Any help to understand what's happening would be appreciated >>>>>> >>>>>> Alex Sanchez >>>>>> >>>>>> --------------------------------------------------------------- ---------- >>>>>> -- >>>>>> -------------------------- >>>>>> >>>>>> Dr. Alex S?nchez. Statistics Department. University of Barcelona. >>>>>> Facultat de Biologia UB. Avda Diagonal 645. 08028 Barcelona. Spain >>>>>> asanchez_at_ub.edu >>>>>> Statistics and Bioinformatics Unit >>>>>> Institut de Recerca. Hospital Universitari Vall 'Hebron >>>>>> Passeig Vall d'Hebron 112-119. 08034 Barcelona >>>>>> asanchez_at_ir.vhebron.net >>>>>> --------------------------------------------------------------- ---------- >>>>>> -- >>>>>> ------------------------- >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> [[alternative HTML version deleted]] >>>>>> >>>>>> >>>>>> >>>>>> --------------------------------------------------------------- --------- >>>>>> >>>>>> _______________________________________________ >>>>>> 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 >>>>>> >>>>> -- >>>>> James W. MacDonald, M.S. >>>>> Biostatistician >>>>> Douglas Lab >>>>> University of Michigan >>>>> Department of Human Genetics >>>>> 5912 Buhl >>>>> 1241 E. Catherine St. >>>>> Ann Arbor MI 48109-5618 >>>>> 734-615-7826 >>>>> >>>>> >>>> >>> -- >>> James W. MacDonald, M.S. >>> Biostatistician >>> Douglas Lab >>> University of Michigan >>> Department of Human Genetics >>> 5912 Buhl >>> 1241 E. Catherine St. >>> Ann Arbor MI 48109-5618 >>> 734-615-7826 >>> >>> _______________________________________________ >>> 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 >>> >> >> _______________________________________________ >> 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 >> >> >