Hi Fiona, It's not you. The function is set up with the assumption that you will be using ensembl data, not flybase. I'll take a look and see if I can make the requisite changes. Best, Jim On 3/29/2013 8:09 AM, Fiona Ingleby wrote: > Hi Jim, > > Thanks very much for pointing that out - it seems mirna2mrna is > exactly what I was after, I don't know how I managed to overlook it?. > > I'm a bit puzzled about the results I'm getting, however, and so if > you have a minute to think this through then I'd be really > grateful. The help pages are pretty clear, and so I've managed to get > the function to run with my data without any problems?.but I'm getting > 'named list()' as output. Which might simply suggest that there are no > correlations between the miRNAs and mRNAs in my data (?). But I'm not > convinced and I'm wondering if I've done something wrong somewhere > along the way (I'm looking at 39 differentially expressed miRNAs along > with 2638 differentially expressed mRNAs, so I'd be surprised if there > were none that correlate with each other). > > I'm wondering if I'm doing something daft like using RNA IDs in the > wrong format (which might be one explanation for getting 0 matches > returned from the database?). At the moment I'm just taking character > vectors directly from the ExpressionSet. So I have 2 ExpressionSets, > each representing only the probes which are significantly > differentially expressed in each dataset - I've called these sigmRNA > (2638 x 12 samples) and sigmiRNA (39 x 12 samples) for mRNA and miRNA > respectively. > > >featureNames(sigmRNA) > [1] "1622906_at" "1622915_at" "1622917_a_at" "1622920_at" > "1622926_at" "1622932_s_at" "1622935_at" "1622940_at" "1622946_at" > [10] "1622952_at" "1622956_at" "1622959_at" "1622960_at" > "1622965_s_at" "1622974_at" "1622975_at" "1622978_at" "1622992_at" > [19] "1623002_at" "1623004_a_at" "1623008_at" "1623019_a_at" > "1623022_at" "1623025_at" "1623026_a_at" "1623030_at" "1623031_a_at" > > ?and so on for 2638 entries. > > >featureNames(sigmiRNA) > [1] "dme-miR-1002_st" "dme-miR-1004_st" "dme-miR-1017_st" > "dme-miR-124_st" "dme-miR-2500_st" "dme-miR-286_st" > [7] "dme-miR-2a_st" "dme-miR-306_st" "dme-miR-310_st" > "dme-miR-311_st" "dme-miR-312_st" "dme-miR-313_st" > > ?etc. So I'm using mirna2mrna like this: > > test<-mirna2mrna(miRNAids=featureNames(sigmiRNA), > miRNAannot="v5.txt.drosophila_melanogaster", #downloaded from the > rbi website and saved in the working directory > mRNAids=featureNames(sigmRNA), > orgPkg="org.Dm.eg.db",chipPkg="drosophila2.db", > sanger=T,miRNAcol=NULL,mRNAcol=NULL,transType="ensembl") > > and then I get: > > > test > named list() > > I've put the sessionInfo() output at the bottom of the email. I also > looked through the source code on the Bioconductor code search > website, pulled out the 'convertIDs' function, and ran this as an > independent function on the lists of RNAs to check to see what it was > doing, but I can't see anything that looks odd to me - it removes the > '_st'/'_at' as I expected. > > So I'm a bit stuck. I'm sure I've misunderstood something, but can't > pick out what it is myself. I suppose it's totally possible that the > analysis is fine and there are just no correlations between the miRNAs > and mRNAs of interest in my data - but I thought I would check. If you > (or anyone) has any ideas, I'd really appreciate the help. > > Thanks again, > > Fiona > > Dr Fiona C Ingleby > > Postdoctoral Research Fellow > University of Sussex > > Email: F.Ingleby at sussex.ac.uk <mailto:f.ingleby at="" sussex.ac.uk=""> > Website: fionaingleby.weebly.com <http: fionaingleby.weebly.com=""> > Tel: +44(0)1273678559 > > > sessionInfo() > R version 2.15.2 (2012-10-26) > Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) > > locale: > [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] drosophila2.db_2.8.1 org.Dm.eg.db_2.8.0 RSQLite_0.11.2 > DBI_0.2-5 AnnotationDbi_1.20.7 Biobase_2.18.0 > [7] BiocGenerics_0.4.0 > > loaded via a namespace (and not attached): > [1] IRanges_1.16.6 parallel_2.15.2 stats4_2.15.2 tools_2.15.2 > > > > On 28 Mar 2013, at 16:43, James W. MacDonald <jmacdon at="" uw.edu=""> <mailto:jmacdon at="" uw.edu="">> wrote: > >> Hi Fiona, >> >> I have a function called mirna2mrna (yeah, I know, lame function >> name...) in my affycoretools package that does this, based on the >> sanger microcosm targets data that you can download here: >> >> http://www.ebi.ac.uk/enright-srv/microcosm/cgi- bin/targets/v5/download.pl >> >> there is also a function makeHmap() that will create a heatmap with >> the miRNA/mRNA pairs, where the color of the cells is based on the >> correlation between the two RNA species (with the intent to show >> negative correlations, indicating that the miRNA is hypothetically >> causing premature degradation of the mRNA). >> >> I think the help pages for these two functions are reasonable, but >> please let me know if you have any questions. >> >> Best, >> >> Jim >> >> >> >> On 3/28/2013 12:30 PM, Fiona Ingleby wrote: >>> Hi everyone, >>> >>> I am working with mRNA data from Affy 'drosophila2' arrays and miRNA >>> data from Affy 'mirna3' arrays. I have identified a list of >>> differentially expressed mRNAs and miRNAs. I'm having a bit of >>> trouble with some downstream analyses and I'm hoping someone might >>> be able to offer some help. >>> >>> I would like to use my list of differentially expressed miRNAs to >>> access online databases (e.g. miRBase, microRNA.org?) and extract >>> the names of all the potential target mRNAs. Then I'd like to use >>> this list of mRNAs to look through my mRNA expression data. I'm >>> aware of packages like 'RmiR' and 'microRNA' which have built-in >>> functions for finding miRNA targets, but as far as I can tell, >>> 'RmiR' uses miRNA databases for humans only and 'microRNA' works >>> with human and mouse data only. So is there a package I am unaware >>> of (or another application of 'RmiR'/'microRNA' that I am unaware >>> of) for looking at drosophila data? >>> >>> So far I have also considered the 'biomaRt' package to see if the >>> database query function on there can help me, but I haven't had much >>> luck. For instance, if I try an example list of miRNAs: >>> >>> mirna<-c("dme-miR-1002","dme-miR-312","dme-miR-973") >>> library(biomaRt) >>> ensembl<-useMart("ensembl",dataset="dmelanogaster_gene_ensembl") >>> getBM(attributes="mirbase_accession",filters="mirbase_id",values=m irna,mart=ensembl) >>> >>> then 'logical(0)' is returned, as if there are no records for those >>> miRNAs - but by searching the database manually I know the records >>> are there. >>> >>> Alternatively I can try: >>> >>> miRNA<- getBM(c("mirbase_accession","mirbase_id", "ensembl_gene_id", >>> "start_position", "chromosome_name"), filters = c("with_mirbase"), >>> values = list(T), mart = ensembl) >>> >>> which returns a table of various bits of information on miRNAs, but >>> I cannot adapt this command to just look at my list of miRNAs of >>> interest (ie. the 'mirna' vector above). I've included the >>> sessionInfo() output for these at the bottom of the email, but I >>> suspect my problem is more to do with the fact I'm not going about >>> this the right way (as opposed to a problem with package versions >>> and coding etc.). I'm not even sure that using 'biomaRt' will give >>> me the information I eventually want (the target mRNAs of these >>> miRNAs), I was just trying it out, to see what it was capable of in >>> terms of querying these databases. So I apologise for the >>> vagueness. Since I haven't managed to get very far by myself then >>> it's difficult to be more specific, but I'd really appreciate it if >>> anyone could offer some advice, even just to point me in the >>> direction of a useful package which might have gone unnoticed by me. >>> >>> Many thanks, >>> >>> Fiona >>> >>> Dr Fiona C Ingleby >>> Postdoctoral Research Fellow >>> University of Sussex >>> Email: F.Ingleby at sussex.ac.uk >>> Website: fionaingleby.weebly.com >>> >>> >>>> sessionInfo() >>> R version 2.15.2 (2012-10-26) >>> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) >>> >>> locale: >>> [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8 >>> >>> attached base packages: >>> [1] stats graphics grDevices utils datasets methods base >>> >>> other attached packages: >>> [1] biomaRt_2.14.0 affy_1.36.1 Biobase_2.18.0 >>> BiocGenerics_0.4.0 >>> >>> loaded via a namespace (and not attached): >>> [1] affyio_1.26.0 BiocInstaller_1.8.3 grid_2.15.2 >>> lattice_0.20-14 Matrix_1.0-11 MCMCglmm_2.17 >>> [7] preprocessCore_1.20.0 RCurl_1.95-4.1 tools_2.15.2 >>> XML_3.95-0.2 zlibbioc_1.4.0 >>> [[alternative HTML version deleted]] >>> >>> >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at r-project.org >>> 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 >> University of Washington >> Environmental and Occupational Health Sciences >> 4225 Roosevelt Way NE, # 100 >> Seattle WA 98105-6099 >> >> > -- James W. MacDonald, M.S. Biostatistician University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099

Hi Fiona, Probably the easiest way to do this is to convert the flybase_cg ids to ensembl IDs. ## read sanger data in ## there is some weird cruft in line 4685, best to just remove the thirteenth column dat <- read.table("v5.txt.drosophila_melanogaster", sep = "\t", stringsAsFactors = FALSE)[,-13] library(drosophila.db) ## map flybase_cg IDs to ensembl x <- select(org.Dm.eg.db, gsub("-[A-Z]+", "",dat[,12]), c("ENSEMBL"), "FLYBASECG") ## there are some duplicates here, but I don't think it will matter ## merge back together and write back out dat$merge <- gsub("-[A-Z]+", "",dat[,12]) dat2 <- merge(dat, x, by.x="merge", by.y=1, all.x = TRUE) write.table(dat2, "v5.txt.drosophila_melanogaster2", sep = "\t", col.names = FALSE, row.names = FALSE, quote = FALSE) ## note that I say the file is not sanger, and then tell mirna2mrna() which columns to use. test <- mirna2mrna(miRNA, "v5.txt.drosophila_melanogaster2", mRNA, "org.Dm.eg.db","drosophila2.db", FALSE, 2,14) With the truncated mRNA and miRNA probe IDs you give below, I get no mappings, but I assume you have way more mRNA transcripts. Let me know if this works for you. Best, Jim On 3/29/2013 8:09 AM, Fiona Ingleby wrote: > Hi Jim, > > Thanks very much for pointing that out - it seems mirna2mrna is > exactly what I was after, I don't know how I managed to overlook it?. > > I'm a bit puzzled about the results I'm getting, however, and so if > you have a minute to think this through then I'd be really > grateful. The help pages are pretty clear, and so I've managed to get > the function to run with my data without any problems?.but I'm getting > 'named list()' as output. Which might simply suggest that there are no > correlations between the miRNAs and mRNAs in my data (?). But I'm not > convinced and I'm wondering if I've done something wrong somewhere > along the way (I'm looking at 39 differentially expressed miRNAs along > with 2638 differentially expressed mRNAs, so I'd be surprised if there > were none that correlate with each other). > > I'm wondering if I'm doing something daft like using RNA IDs in the > wrong format (which might be one explanation for getting 0 matches > returned from the database?). At the moment I'm just taking character > vectors directly from the ExpressionSet. So I have 2 ExpressionSets, > each representing only the probes which are significantly > differentially expressed in each dataset - I've called these sigmRNA > (2638 x 12 samples) and sigmiRNA (39 x 12 samples) for mRNA and miRNA > respectively. > > >featureNames(sigmRNA) > [1] "1622906_at" "1622915_at" "1622917_a_at" "1622920_at" > "1622926_at" "1622932_s_at" "1622935_at" "1622940_at" "1622946_at" > [10] "1622952_at" "1622956_at" "1622959_at" "1622960_at" > "1622965_s_at" "1622974_at" "1622975_at" "1622978_at" "1622992_at" > [19] "1623002_at" "1623004_a_at" "1623008_at" "1623019_a_at" > "1623022_at" "1623025_at" "1623026_a_at" "1623030_at" "1623031_a_at" > > ?and so on for 2638 entries. > > >featureNames(sigmiRNA) > [1] "dme-miR-1002_st" "dme-miR-1004_st" "dme-miR-1017_st" > "dme-miR-124_st" "dme-miR-2500_st" "dme-miR-286_st" > [7] "dme-miR-2a_st" "dme-miR-306_st" "dme-miR-310_st" > "dme-miR-311_st" "dme-miR-312_st" "dme-miR-313_st" > > ?etc. So I'm using mirna2mrna like this: > > test<-mirna2mrna(miRNAids=featureNames(sigmiRNA), > miRNAannot="v5.txt.drosophila_melanogaster", #downloaded from the > rbi website and saved in the working directory > mRNAids=featureNames(sigmRNA), > orgPkg="org.Dm.eg.db",chipPkg="drosophila2.db", > sanger=T,miRNAcol=NULL,mRNAcol=NULL,transType="ensembl") > > and then I get: > > > test > named list() > > I've put the sessionInfo() output at the bottom of the email. I also > looked through the source code on the Bioconductor code search > website, pulled out the 'convertIDs' function, and ran this as an > independent function on the lists of RNAs to check to see what it was > doing, but I can't see anything that looks odd to me - it removes the > '_st'/'_at' as I expected. > > So I'm a bit stuck. I'm sure I've misunderstood something, but can't > pick out what it is myself. I suppose it's totally possible that the > analysis is fine and there are just no correlations between the miRNAs > and mRNAs of interest in my data - but I thought I would check. If you > (or anyone) has any ideas, I'd really appreciate the help. > > Thanks again, > > Fiona > > Dr Fiona C Ingleby > > Postdoctoral Research Fellow > University of Sussex > > Email: F.Ingleby at sussex.ac.uk <mailto:f.ingleby at="" sussex.ac.uk=""> > Website: fionaingleby.weebly.com <http: fionaingleby.weebly.com=""> > Tel: +44(0)1273678559 > > > sessionInfo() > R version 2.15.2 (2012-10-26) > Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) > > locale: > [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] drosophila2.db_2.8.1 org.Dm.eg.db_2.8.0 RSQLite_0.11.2 > DBI_0.2-5 AnnotationDbi_1.20.7 Biobase_2.18.0 > [7] BiocGenerics_0.4.0 > > loaded via a namespace (and not attached): > [1] IRanges_1.16.6 parallel_2.15.2 stats4_2.15.2 tools_2.15.2 > > > > On 28 Mar 2013, at 16:43, James W. MacDonald <jmacdon at="" uw.edu=""> <mailto:jmacdon at="" uw.edu="">> wrote: > >> Hi Fiona, >> >> I have a function called mirna2mrna (yeah, I know, lame function >> name...) in my affycoretools package that does this, based on the >> sanger microcosm targets data that you can download here: >> >> http://www.ebi.ac.uk/enright-srv/microcosm/cgi- bin/targets/v5/download.pl >> >> there is also a function makeHmap() that will create a heatmap with >> the miRNA/mRNA pairs, where the color of the cells is based on the >> correlation between the two RNA species (with the intent to show >> negative correlations, indicating that the miRNA is hypothetically >> causing premature degradation of the mRNA). >> >> I think the help pages for these two functions are reasonable, but >> please let me know if you have any questions. >> >> Best, >> >> Jim >> >> >> >> On 3/28/2013 12:30 PM, Fiona Ingleby wrote: >>> Hi everyone, >>> >>> I am working with mRNA data from Affy 'drosophila2' arrays and miRNA >>> data from Affy 'mirna3' arrays. I have identified a list of >>> differentially expressed mRNAs and miRNAs. I'm having a bit of >>> trouble with some downstream analyses and I'm hoping someone might >>> be able to offer some help. >>> >>> I would like to use my list of differentially expressed miRNAs to >>> access online databases (e.g. miRBase, microRNA.org?) and extract >>> the names of all the potential target mRNAs. Then I'd like to use >>> this list of mRNAs to look through my mRNA expression data. I'm >>> aware of packages like 'RmiR' and 'microRNA' which have built-in >>> functions for finding miRNA targets, but as far as I can tell, >>> 'RmiR' uses miRNA databases for humans only and 'microRNA' works >>> with human and mouse data only. So is there a package I am unaware >>> of (or another application of 'RmiR'/'microRNA' that I am unaware >>> of) for looking at drosophila data? >>> >>> So far I have also considered the 'biomaRt' package to see if the >>> database query function on there can help me, but I haven't had much >>> luck. For instance, if I try an example list of miRNAs: >>> >>> mirna<-c("dme-miR-1002","dme-miR-312","dme-miR-973") >>> library(biomaRt) >>> ensembl<-useMart("ensembl",dataset="dmelanogaster_gene_ensembl") >>> getBM(attributes="mirbase_accession",filters="mirbase_id",values=m irna,mart=ensembl) >>> >>> then 'logical(0)' is returned, as if there are no records for those >>> miRNAs - but by searching the database manually I know the records >>> are there. >>> >>> Alternatively I can try: >>> >>> miRNA<- getBM(c("mirbase_accession","mirbase_id", "ensembl_gene_id", >>> "start_position", "chromosome_name"), filters = c("with_mirbase"), >>> values = list(T), mart = ensembl) >>> >>> which returns a table of various bits of information on miRNAs, but >>> I cannot adapt this command to just look at my list of miRNAs of >>> interest (ie. the 'mirna' vector above). I've included the >>> sessionInfo() output for these at the bottom of the email, but I >>> suspect my problem is more to do with the fact I'm not going about >>> this the right way (as opposed to a problem with package versions >>> and coding etc.). I'm not even sure that using 'biomaRt' will give >>> me the information I eventually want (the target mRNAs of these >>> miRNAs), I was just trying it out, to see what it was capable of in >>> terms of querying these databases. So I apologise for the >>> vagueness. Since I haven't managed to get very far by myself then >>> it's difficult to be more specific, but I'd really appreciate it if >>> anyone could offer some advice, even just to point me in the >>> direction of a useful package which might have gone unnoticed by me. >>> >>> Many thanks, >>> >>> Fiona >>> >>> Dr Fiona C Ingleby >>> Postdoctoral Research Fellow >>> University of Sussex >>> Email: F.Ingleby at sussex.ac.uk >>> Website: fionaingleby.weebly.com >>> >>> >>>> sessionInfo() >>> R version 2.15.2 (2012-10-26) >>> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) >>> >>> locale: >>> [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8 >>> >>> attached base packages: >>> [1] stats graphics grDevices utils datasets methods base >>> >>> other attached packages: >>> [1] biomaRt_2.14.0 affy_1.36.1 Biobase_2.18.0 >>> BiocGenerics_0.4.0 >>> >>> loaded via a namespace (and not attached): >>> [1] affyio_1.26.0 BiocInstaller_1.8.3 grid_2.15.2 >>> lattice_0.20-14 Matrix_1.0-11 MCMCglmm_2.17 >>> [7] preprocessCore_1.20.0 RCurl_1.95-4.1 tools_2.15.2 >>> XML_3.95-0.2 zlibbioc_1.4.0 >>> [[alternative HTML version deleted]] >>> >>> >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at r-project.org >>> 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 >> University of Washington >> Environmental and Occupational Health Sciences >> 4225 Roosevelt Way NE, # 100 >> Seattle WA 98105-6099 >> >> > -- James W. MacDonald, M.S. Biostatistician University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099