Howdy, On Fri, Nov 9, 2012 at 12:15 PM, James W. MacDonald <jmacdon at="" uw.edu=""> wrote: [snip] > So I wonder if we are just doing something because we can't do what we > really want to do, and doing nothing isn't an option. You can't get grants > by sitting around waiting for the right technique to arrive, now can you? [/snip] The right thing has arrived: have your collaborator(s) do some CLIP (HITS-CLIP/PAR-CLIP) against Ago2 in two conditions: (1) Condition X (2) Conditions X with your miRNA of interest somehow shut off (KO'd? or maybe w/ antisense LNA's to your miRNA(?)) (3) and likely coupled w/ some rna-seq in both conditions so you can decouple differential ago binding from differential mRNA (target) expression. You can then work on more interesting problems that will arise in this scenario, but at least you won't be guessing where your miRNA is binding ... (sorry if that's not what we're talking about since I only did a cursory scan of this thread ;-) -steve -- Steve Lianoglou Graduate Student: Computational Systems Biology | Memorial Sloan-Kettering Cancer Center | Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact

Hi Stephen and James, a comment concerning the use (mature) microRNA names below. On 09/11/12 17:15, James W. MacDonald wrote: > Hi Stephen, > > On 11/9/2012 10:27 AM, Stephen Turner wrote: >> Thanks Jim. Yes, that is the initial goal, looking for differentially >> expressed miRNAs. Perhaps downstream some target prediction is likely >> in order, or perhaps some pathway analysis based on targets of >> differentially regulated miRNAs (e.g. something like >> http://www.ncbi.nlm.nih.gov/pubmed/22649059). > > Well that appears to be the state of the art right now for these arrays, > but I find it wholly unsatisfying. Predicting mRNAs or pathways that > *might* be targeted by one or more miRNA transcripts is a far cry from > being able to say that something is in fact happening. > > We have actually processed a fair number of these arrays in our core, > and I'm on the fence. There are usually only a handful that are > differentially expressed, but when you map them to the hypothetically > targeted transcripts, you can end up with some huge fraction of the > transcriptome. > > What we have been doing is to pair miRNA and mRNA analysis on the same > samples, looking for genes that are differentially expressed and > negatively correlated to the miRNA expression. But this is somewhat > limited, as the correlation can only be due to mRNA being destabilized > by miRNA (or targeted for premature degradation). But I wonder if the > real interesting correlation is between miRNA expression and mRNA > translation, which you can't get at with an expression array. > > So I wonder if we are just doing something because we can't do what we > really want to do, and doing nothing isn't an option. You can't get > grants by sitting around waiting for the right technique to arrive, now > can you? > > >> >> But correct - right now, it's only differentially regulated miRNAs >> that the PI is after. I'll have to take a look at Affy's QC tool - >> I've always used BioC, never Affy's software. This is likely a one- off >> analysis, as not many folks here are using these chips, so it might >> not be worth building a reproducible R script if I won't be doing >> these very often. However, it would be nice to be able to annotate >> these results with links to the miRbase page, sort of like what I do >> with Entrez IDs for Gene ST arrays. > > That shouldn't be too difficult. Note that the search page can be > accessed by appending the correct ID to the end of > > http://www.mirbase.org/cgi-bin/query.pl?terms= > > and you can create HTML tables using the xtable package, but you have to > pass in the correct data to get a working URI. > > Something like > > fun <- function(x){ > paste("", x, "", sep = "") > } > > then you can use affycoretools:::convertIDs() to change to mirBase IDs > > Fake up some stuff: > > library(pd.mirna.3.0) > con <- db(pd.mirna.3.0) > ids <- head(grep("^hsa", dbGetQuery(con, "select man_fsetid from > featureSet;")[,1], value = TRUE)) > links <- fun(affycoretools:::convertIDs(ids)) > > fc <- rnorm(6) > print(xtable(data.frame(miRbaseIDs = links, FoldChange = fc)), type = > "html", include.rownames = FALSE, > sanitize.text.function = function(x) x, file = "tmp.html") > > Or you can use the R2HTML package. these mature miRNA names are the ones used at the time of the chip design/production by Affymetrix and inevitably change over time. I notice many contain a * in their name which removed from the the miRBase nomenclature in 2011 (http://www.mirbase.org/blog/2011/04/whats- in-a-name/). A quick check with the mirbase.db package indicates that nearly a third are "lost" (ie have been renamed, or even removed, or changed species etc. as more data about them get accumulated). library(mirbase.db) library(pd.mirna.3.0) con <- db(pd.mirna.3.0) ids <- grep("^hsa", dbGetQuery(con, "select man_fsetid from featureSet;")[,1], value = TRUE) length(ids) #[1] 1733 matureIDs <- toTable(mirbaseMATURE)[['mature_name']] 100 * (1 - (sum(affycoretools:::convertIDs(ids) %in% matureIDs) / length(ids))) #[1] 28.04385 Ideally one would need the sequences used to design the probes which I think are available from Affymetrix to map these to the latest release of miRBase, I couldn't find it a GPL for this array on GEO. Best, J. > >> >> So if not RMA, what alternative is better for processing the affybatch >> into an expressionset? > > I forget what the miRNA QC tool does as the default, and I can't get it > to run on my 64-bit Windows box to see. The manual doesn't appear to say > what the default is, although it may well be RMA. I don't recall there > being much difference between the two, and having no way to say what the > truth is, any claim of 'better' would be pure conjecture. My point was > simply that RMA is sort of silly in this case, as all of the probes are > identical, and measure the same thing. > > Best, > > Jim > > >> >> Thanks, >> >> Stephen >> >> On Thu, Nov 8, 2012 at 6:01 PM, James W. MacDonald<jmacdon at="" uw.edu=""> >> wrote: >>> Hi Stephen, >>> >>> >>> On 11/8/2012 5:25 PM, Stephen Turner wrote: >>>> Thanks much. I used read.celfiles() and rma() worked perfectly at this >>>> point. I will definitely take you up on help getting this to gel with >>>> the rest of my workflow. >>>> >>>> My next step with gene ST arrays is to annotate the expressionset >>>> object with fData, such that when I use topTable() later on, all my >>>> results are annotated. E.g.: >>>> >>>> ## Which annotation package are you using? >>>> eset at annotation >>>> annodb<- "hugene10sttranscriptcluster.db" >>>> >>>> ## Annotate the features >>>> ls(paste("package:", annodb, sep="")) >>>> ID<- featureNames(eset) >>>> Symbol<- as.character(lookUp(ID, annodb, "SYMBOL")) >>>> Name<- as.character(lookUp(ID, annodb, "GENENAME")) >>>> Entrez<- as.character(lookUp(ID, annodb, "ENTREZID")) >>>> tmp<- data.frame(ID=ID, Entrez=Entrez, Symbol=Symbol, Name=Name, >>>> stringsAsFactors=F) >>>> tmp[tmp=="NA"]<- NA >>>> fData(eset)<- tmp >>>> >>>> But I'm not sure what to do here because ls("package:pd.mirna.3.0") >>>> doesn't return what the typical hu/mogene10sttranscriptcluster.db DBs >>>> return. >>> >>> Right. Note that something like the MoGene ST chip measures mRNA, >>> whereas >>> the mirna 3.0 measures miRNA, which is a completely different class >>> of RNA. >>> While some miRNAs have Entrez Gene IDs, they don't have symbols or names >>> that I know of. >>> >>> miRNAs target various mRNA species for either silencing (by binding >>> to the >>> mRNA transcript, making it double stranded in a particular region, >>> thereby >>> eliminating translation to protein) or for premature degradation. >>> >>> To make things more complicated, the mRNA that are thought to be >>> targeted by >>> a given miRNA are based on one or more of sequence homology, >>> conservation, >>> thermodynamic properties and something else that escapes me right >>> now. In >>> other words, the targeting of mRNA by miRNA is almost always >>> computationally >>> derived. So depending on which algorithm (and what cutoffs you use), >>> you can >>> get from zero to thousands of mRNAs targeted by a given miRNA. >>> >>> As an example, go here: >>> >>> http://www.mirbase.org/cgi-bin/mirna_entry.pl?acc=MI0003205 >>> >>> this is just some random miRNA I searched for. Now scroll down to the >>> 'Mature sequence' section, and click on some of the links for Predicted >>> targets. Fun, huh? >>> >>> Also note that the miR 3.0 chip has miRNA for lots of different >>> species, as >>> well as the hairpin configuration (which AFAICT is all garbage, but >>> YMMV). >>> So you may or may not want to be filtering out miRNA for uninteresting >>> species, depending on whether or not you (or your PI) think a particular >>> miRNA from say M. nemestrina is also expressed in the species you are >>> working with. >>> >>> Also note that RMA is sort of silly for these arrays anyway. A mature >>> miRNA >>> is 21-23 bases long, and the affy chip uses 25 mers. So the replicate >>> probes >>> in a probeset are usually just the same thing in a different place on >>> the >>> chip. You could make the argument that the algorithm used in the >>> miRNA QC >>> tool that Affy will give you for free does a better job. >>> >>> So is the goal here to just find differentially expressed miRNAs? >>> >>> Best, >>> >>> Jim >>> >>> >>> >>>> Many thanks, >>>> >>>> Stephen >>>> >>>> On Thu, Nov 8, 2012 at 10:32 AM, Benilton Carvalho >>>> <beniltoncarvalho at="" gmail.com=""> wrote: >>>>> The problem is that you have both affy and oligo loaded simultaneously >>>>> (I'll >>>>> add this to my todo list, so in the future users do not need to worry >>>>> about >>>>> it). >>>>> >>>>> Option 1) (don't load oligo) >>>>> >>>>> By using ReadAffy(), you're importing the data via affy package, which >>>>> does >>>>> not know how to handle miRNA-3.0 arrays. >>>>> >>>>> If you rather stick to your original workflow, you'd need to follow >>>>> the >>>>> "unrecommended" path of converting a PGF to a CDF (I rather not say >>>>> much >>>>> about this), and then build the required annotation packages yourself. >>>>> >>>>> >>>>> Option 2) (don't load affy) (disclaimer: I'm the author of oligo) >>>>> >>>>> If you don't load affy and use read.celfiles (from oligo), you'll >>>>> get the >>>>> rma() part done easily. At this point, I'd be happy to work with >>>>> you to >>>>> incorporate tools to simplify the use of the other packages that >>>>> you have >>>>> in >>>>> your workflow. >>>>> >>>>> >>>>> best, >>>>> benilton >>>>> >>>>> >>>>> On 8 November 2012 15:12, Stephen Turner<vustephen at="" gmail.com=""> wrote: >>>>>> Just wanted to resurrect this issue. I routinely analyze gene 1.0 ST >>>>>> chips in my core, but this is the first time I'm looking at the miRNA >>>>>> 3.0 chip (or any Affy miRNA chip for that matter). >>>>>> >>>>>> I understand that there's no 3.0 CDF environment available. How might >>>>>> I go about building one and incorporating that into my workflow? >>>>>> >>>>>> My typical [Hu/Mo]Gene 1.0 ST workflow goes something like this: >>>>>> >>>>>> ############################################ >>>>>> ## Load data >>>>>> affybatch<- ReadAffy(filenames) >>>>>> eset<- rma(affybatch) >>>>>> >>>>>> ## Annotate >>>>>> ID<- featureNames(eset) >>>>>> Symbol<- as.character(lookUp(ID, "hugene10sttranscriptcluster.db", >>>>>> "SYMBOL")) >>>>>> Name<- as.character(lookUp(ID, "hugene10sttranscriptcluster.db", >>>>>> "GENENAME")) >>>>>> fData(eset)<- data.frame(ID=ID, Symbol=Symbol, Name=Name) >>>>>> >>>>>> ## Typical QC with arrayQualityMetrics and analysis with limma >>>>>> ############################################ >>>>>> >>>>>> I'm getting this error when using rma() on the affybatch object: >>>>>> >>>>>>> rma(affybatch) >>>>>> Error in function (classes, fdef, mtable) : >>>>>> unable to find an inherited method for function "rma", for >>>>>> signature >>>>>> "AffyBatch" >>>>>> >>>>>> And additionally when I try to view the affybatch: >>>>>> >>>>>> AffyBatch object >>>>>> size of arrays=541x541 features (19 kb) >>>>>> cdf=miRNA-3_0 (??? affyids) >>>>>> number of samples=6 >>>>>> Error in getCdfInfo(object) : >>>>>> Could not obtain CDF environment, problems encountered: >>>>>> Specified environment does not contain miRNA-3_0 >>>>>> Library - package mirna30cdf not installed >>>>>> Bioconductor - mirna30cdf not available >>>>>> >>>>>> Thanks. >>>>>> >>>>>> >>>>>>> sessionInfo() >>>>>> R version 2.15.0 (2012-03-30) >>>>>> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) >>>>>> >>>>>> locale: >>>>>> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 >>>>>> >>>>>> attached base packages: >>>>>> [1] grid stats graphics grDevices utils datasets >>>>>> methods base >>>>>> >>>>>> other attached packages: >>>>>> [1] pd.mirna.3.0_3.6.0 oligo_1.22.0 >>>>>> oligoClasses_1.20.0 >>>>>> [4] RSQLite_0.11.2 DBI_0.2-5 >>>>>> biomaRt_2.14.0 >>>>>> [7] VennDiagram_1.5.1 SPIA_2.8.0 >>>>>> pvclust_1.2-2 >>>>>> [10] genefilter_1.40.0 gplots_2.11.0 >>>>>> MASS_7.3-22 >>>>>> [13] KernSmooth_2.23-8 caTools_1.13 >>>>>> bitops_1.0-4.1 >>>>>> [16] gdata_2.12.0 gtools_2.7.0 >>>>>> limma_3.14.1 >>>>>> [19] arrayQualityMetrics_3.14.0 annotate_1.36.0 >>>>>> AnnotationDbi_1.20.2 >>>>>> [22] affy_1.36.0 Biobase_2.18.0 >>>>>> BiocGenerics_0.4.0 >>>>>> [25] BiocInstaller_1.8.3 >>>>>> >>>>>> loaded via a namespace (and not attached): >>>>>> [1] affxparser_1.30.0 affyio_1.26.0 affyPLM_1.34.0 >>>>>> beadarray_2.8.1 >>>>>> [5] BeadDataPackR_1.10.0 Biostrings_2.26.2 bit_1.1-9 >>>>>> Cairo_1.5-1 >>>>>> [9] cluster_1.14.3 codetools_0.2-8 colorspace_1.2-0 >>>>>> ff_2.2-9 >>>>>> [13] foreach_1.4.0 gcrma_2.30.0 GenomicRanges_1.10.3 >>>>>> Hmisc_3.10-1 >>>>>> [17] hwriter_1.3 IRanges_1.16.4 iterators_1.0.6 >>>>>> lattice_0.20-10 >>>>>> [21] latticeExtra_0.6-24 parallel_2.15.0 plyr_1.7.1 >>>>>> preprocessCore_1.20.0 >>>>>> [25] RColorBrewer_1.0-5 RCurl_1.95-1.1 reshape2_1.2.1 >>>>>> setRNG_2011.11-2 >>>>>> [29] splines_2.15.0 stats4_2.15.0 stringr_0.6.1 >>>>>> survival_2.36-14 >>>>>> [33] SVGAnnotation_0.93-1 tools_2.15.0 vsn_3.26.0 >>>>>> XML_3.95-0.1 >>>>>> [37] xtable_1.7-0 zlibbioc_1.4.0 >>>>>> >>>>>> >>>>>> On Sat, Oct 13, 2012 at 12:56 AM, Dana Most<danamost at="" gmail.com=""> >>>>>> wrote: >>>>>>> Hi All, >>>>>>> >>>>>>> Have you managed to find a cdf for the miRNA 3.0? >>>>>>> I keep getting the error : "...cdf=miRNA-3_0 (??? affyids)..." >>>>>>> >>>>>>> When I spoke to Affymetrix they said that the 3.0 version doesn't >>>>>>> have >>>>>>> a >>>>>>> .cdf and that a .cdf format wouldn't be compatible... >>>>>>> They said I should use the 'xps' package on the bioconductor website >>>>>>> together with a .pgf from their website. >>>>>>> 'xps' doesn't work with Windows 7, which unfortunately is what I >>>>>>> have. >>>>>>> >>>>>>> Can anyone help me? >>>>>>> >>>>>>> Thanks, >>>>>>> >>>>>>> Dana >>>>>>> >>>>>>> [[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 >>>>>> _______________________________________________ >>>>>> 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 >>> >