http://permalink.gmane.org/gmane.science.biology.informatics.conductor hourly 1 1901-01-01T00:00+00:00 http://gmane.org/img/gmane-25t.png http://gmane.org http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48354 <pre>Hi Alicia, Unfortunately I replied to the previous email off list, but let's get back on list now: You've just identified the row,col indices of the values in your count matrix that do not look like integers. As Simon and I tried to explain in the initial responses, this command: R&gt; which( spercysts_vs_embryos != round (spercysts_vs_embryos), arr.ind=TRUE ) Finds the elements in `spercysts_vs_embryos` that are not rounding to each other. As you included in the previous email, one of these elements is (44259,1), so what is it? R&gt; spercysts_vs_embryos[44259, 1] The point is that DESeq needs *integers*, you have stuff in your data.frame that are not integers. Likely they are some decimal number, I guess. You need to input raw count data to DESeq, not some mean count, RPKM, or whatever. HTH, -steve -- Steve Lianoglou Computational Biologist Bioinformatics and Computational Biology Genentech _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;pu</pre> Steve Lianoglou 2013-05-24T23:20:31 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48353 <pre>If i do: arr.ind=TRUE ) I get: comp203811_c0_seq3 44259 1 comp203811_c0_seq4 44260 1 comp203818_c0_seq2 44266 1 comp203818_c0_seq4 44268 1 comp203827_c0_seq2 44281 1 comp203827_c0_seq3 44282 1 comp203827_c0_seq7 44286 1 comp203828_c0_seq1 44287 1 [ reached getOption("max.print") -- omitted 166743 rows ] If i do: I get: Error: unexpected ',' in "which(round(spercysts_vs_embryos) != spercysts_vs_embryos)," On Fri, May 24, 2013 at 4:51 PM, Steve Lianoglou &lt;lianoglou.steve-RuTDbSqP/YI&lt; at &gt;public.gmane.org&gt;wrote: [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor</pre> Alicia R. Pérez-Porro 2013-05-24T22:51:17 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48352 <pre>Hi Alicia, On Fri, May 24, 2013 at 2:38 PM, Alicia R. Pérez-Porro &lt;alicia.r.perezporro-Re5JQEeQqe8AvxtiuMwx3w&lt; at &gt;public.gmane.org&gt; wrote: Everything isn't fine :-) Your columns should be integers, not just "numeric". If you look at the source code of `newCountDataSet`, you'll see right at the very top: countData &lt;- as.matrix(countData) if (any(round(countData) != countData)) stop("The countData is not integer.") Which looks like the error you are getting here: So it's not that you have NA's in your data.frame, but your first problem is that the numbers you are using for your count matrix are not rounding to themselves, which is a quick/easy way to check that they aren't whole numbers, as you would expect by count data, and DESeq requires count data. So, instead of checking for NA here: You might try to check which numbers are suspect: R&gt; which(round(spercysts_vs_embryos) != spercysts_vs_embryos), arr.ind=TRUE) HTH, -steve -- Steve Lianoglou Computational Biologist Bioinformatics and</pre> Steve Lianoglou 2013-05-24T21:51:25 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48351 <pre> May the issue is not an NA but some non-integer number that sneaked in. Try which( spercysts_vs_embryos != round (spercysts_vs_embryos), arr.ind=TRUE ) _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor </pre> Simon Anders 2013-05-24T21:50:34 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48350 <pre>My data are simply transcript identifiers, with the corresponding gene symbol. I just want to merge gene symbol information into the result from transcripts(), using our internal TxDb package. It would fit into an OrgDb package, but the OrgDb package might not be useful by itself (but maybe it would be for others around here). If you think it's straightforward (to what degree?) to create one from a list of data frames, please add support for it to AnnotationDbi or something. The NCBI-based stuff looks pretty complex. Thanks, Michael On Fri, May 24, 2013 at 2:29 PM, Marc Carlson &lt;mcarlson-q9hIisBwmLrYtjvyW6yDsg&lt; at &gt;public.gmane.org&gt; wrote: [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor </pre> Michael Lawrence 2013-05-24T21:50:29 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48349 <pre>Hi, I'm trying to use DESeq to know the differential expressed genes of my datasets and i'm encountering that DESeq is not recognizing my row.names so i can't create my cds. My .csv input file looks like: transcript_id,C4,CRL_2APR10,CRL_1_15JUL11,CRL_2_15JUL11 comp1000201_c0_seq1,5.00,0.00,0.00,0.00 comp1000297_c0_seq1,7.00,0.00,0.00,0.00 comp100036_c0_seq1,0.00,0.00,0.00,0.00 comp10003_c1_seq1,2.00,0.00,0.00,0.00 comp100041_c0_seq1,3.00,0.00,0.00,0.00 comp100041_c0_seq2,0.00,0.00,0.00,0.00 comp100041_c0_seq3,0.00,0.00,0.00,0.00 comp100051_c0_seq1,0.00,0.00,0.00,0.00 comp1000890_c0_seq1,3.00,0.00,0.00,0.00 This is what i'm running: + file.choose(), + header = TRUE, + row.names=1, + sep = ",", + dec = ".") C4 CRL_2APR10 CRL_1_15JUL11 CRL_2_15JUL11 comp1000201_c0_seq1 5 0 0 0 comp1000297_c0_seq1 7 0 0 0 comp100036_c0_seq1 0 0 0 0 comp10003_c1_seq1 2 0 </pre> Alicia R. Pérez-Porro 2013-05-24T21:38:15 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48348 <pre>Hi Michael, You could do it that way. As long as you made a new object type and wrote supporting methods that would work. And we designed it so that this could work, but I would still actually recommend another slightly different approach. My preference would be to make 1) a function that takes a named list of data.frames and generates a simple org database. (This is actually a pretty straightforward function to write). And then 2) another function to call that and wrap that DB in an org package (also straightforward). The reason for this, is that by writing these two functions, you would 1) get all the OrgDb objects methods for free since you would have made a package that creates an existing OrgDb object. (so no need to implement select and it's friends, and no need to introduce any new object types) and 2) We would maintain a consistent database schema with existing org packages. This would help prevent the unnecessary proliferation of DB schemas and associated methods. Those methods</pre> Marc Carlson 2013-05-24T21:29:09 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48347 <pre>Hi Simon, I have not changed the count files (except their file names) or the flattened GFF after running dexseq_count.py. For example: --- lsa-579-005:DEXSeq_tra2b_Named darwin$ grep 'bmp2\b' CTR1.txt bmp2:001160 bmp2:00245 bmp2:00347 lsa-579-005:DEXSeq_tra2b_Named darwin$ grep 'bmp2\b' flat_frog_q1_fixed_v2.gff scaffold_5merged_stranded_q1.GFFaggregate_gene101514148101526061.-.gene_id "bmp2" scaffold_5merged_stranded_q1.GFFexonic_part101514148101516034.-.transcripts "TCONS_00042267"; exonic_part_number "001"; gene_id "bmp2" scaffold_5merged_stranded_q1.GFFexonic_part101522614101522972.-.transcripts "TCONS_00042267"; exonic_part_number "002"; gene_id "bmp2" scaffold_5merged_stranded_q1.GFFexonic_part101525481101526061.-.transcripts "TCONS_00042267"; exonic_part_number "003"; gene_id "bmp2" --- What I tried to say in what you quote is that using the same data set (same aligned reads) and an very similar flat GFF I can run DEXSeq without problems. In that case I took the</pre> Darwin Sorento Dichmann 2013-05-24T21:00:37 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48346 <pre>Hi Darwin Wait, what do you mean by "changed the gene names"? Each count file has two columns, one with the gene IDs, the other with the counts. The flattened GFF file also contains the gene ID, and to make sure that count files and GFF file fit together, DEXSeq compares the gene IDs and complains if they don't match. Simon _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor </pre> Simon Anders 2013-05-24T20:05:27 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48345 <pre>Hi Tim, By default getBM queries go to the central BioMart service, they are lagging a bit behind with the Ensembl version that they host and are running v69. If you do your query on the latest version of Ensembl you get results for one more of your ids: mart &lt;- useMart("ENSEMBL_MART_ENSEMBL", dataset="hsapiens_gene_ensembl",host="www.ensembl.org") attr &lt;- c("refseq_mrna",'hgnc_symbol', 'chromosome_name','start_position','end_position') ids &lt;- c("NM_001270493", "NM_001185076","NM_001185075","NM_001185082") xx &lt;- getBM(attributes=attr,filters = "refseq_mrna", values = ids, mart = mart) refseq_mrna hgnc_symbol chromosome_name start_position end_position 1 NM_001185075 FMR1 X 146993469 147032645 2 NM_001185076 FMR1 X 146993469 147032645 3 NM_001185082 FMR1 X 146993469 147032645 The missing id NM_001270493 might be to novel to have been included in the latest Ensembl build. To find out for sure you could email the Ense</pre> Steffen Durinck 2013-05-24T19:52:40 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48344 <pre>The error may be the result of your call rather than either of the packages. Note that your call has "sdundo=c(0,0), alpha=c(0.5,0.1)" whereas the defaults from the manual is "sdundo=c(1,2), alpha=c(0.05,0.01)." Venkat -----Original Message----- From: wwwrun-Jsn6dHEVml8bj/IP87xzWw&lt; at &gt;public.gmane.org [mailto:wwwrun-Jsn6dHEVml8bj/IP87xzWw&lt; at &gt;public.gmane.org] Sent: Friday, May 24, 2013 10:05 AM To: bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org; gongkn-cXYBEXCxyP//PtFMR13I2A&lt; at &gt;public.gmane.org Cc: Seshan, Venkatraman E./Epidemiology-Biostatistics Subject: Error in sort(abs(diff(genomdat)))[1:n.keep] Hi all, I'm using a package ExomeCNV to call LOH and got an error in step "Combine multiple positions into LOH segments" the.loh = multi.LOH.analyze(normal, tumor, all.loh.ls=list(eLOH), test.alpha=0.001, method="variance.f", sdundo=c(0,0), alpha=c(0.5,0.1)) Analyzing: Sample.1 Error in sort(abs(diff(genomdat)))[1:n.keep] : only 0's may be mixed with negative subscripts In addition: Warning message: In CN</pre> SeshanV-l+TJEeH7cPzYtjvyW6yDsg< at >public.gmane.org 2013-05-24T14:47:20 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48343 <pre>Hi all, I am studying a ChIP-Seq dataset (looking at gene promoter regions in human) where it appears that different experimental groups have widely different dispersions/variances using edgeR/limma. I have 4 timepoints, and if I use edgeR to compute the dispersion for each timepoint separately, I get: 0 hours: 0.407 24 hours: 0.505 120 hours: 0.115 2 weeks: 0.0531 So the dispersion seems to range from 0.05 to 0.5. I am looking to test for "differential modification" between these timepoints, as well as between cell types at each timepoint, etc., and I was wondering if there is any differential expression test (or dispersion estimation method?) that can handle groups with different dispersions/variances. For reference, here is my experimenal design as an Excel spreadsheet: https://www.dropbox.com/s/3vnk4mai3dh39yv/chipseq-samples.xlsx And here is the result of plotBCV on each group (look at the last 4 pages for the time point groups): https://www.dropbox.com/s/s4caq1p0h3e4zhm/groupdisps.pdf (</pre> Ryan C. Thompson 2013-05-24T19:10:09 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48342 <pre>Greetings, I created the count files using dexseq_count.py according to the instructions. However, when I attempt to create ExonCountSets using read.HTSeqCounts I get the following error: --- Error in read.HTSeqCounts(countfiles = file.path(inDir, countfiles), design = tra2bdata, : Count files do not correspond to the flattened annotation file --- I *know* that the ecs files corresponds to the flat GFF and I have rerun that step thrice. So, I assume that the error message is really about something else and I would appreciate any help at getting to it. FWIW, DEXSeq works on the same data set, but with a slightly different flat GFF (the one that gives me trouble have been changed the gene names). The GFF is flattened from a Cufflinks GTF. This is the minimal code that reproduce the error: # R version 2.15.2 (2012-10-26) -- "Trick or Treat" # Load DEXSeq and setwd. source("http://bioconductor.org/biocLite.R") biocLite("DEXSeq") library(DEXSeq) setwd("~/Dropbox/DEXSeq_tra2b_Named/") # Create data fram</pre> Darwin Sorento Dichmann 2013-05-24T18:59:37 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48341 <pre>Dear List, I am looking for a method or package to use RNA-Seq or microarray data to detect genes whose expression in a single or small number of tissues is significantly different than in other tissues. For example, I have an RNASeq data in platelet cell. How can I find a list of genes specifically expressed in platelet by comparing to the Illumina Boby Map RNAseq data which includes 16 tissues/cells. Many thanks, Shirley _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor </pre> shirley zhang 2013-05-24T17:40:20 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48340 <pre>We are running experiments where there are technical difficulties in getting a pure template of interest. What we have is a mix of template-1 (our template of interest) and template-2 (the contaminating template). We have pure samples of template-2 that we run alongside the mix. We also run several HSK genes to use for normalization. Using HTqPCR, is there a way to remove the signal in the mix due to template-2 ? Thanks. Susanne [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor </pre> Penny, Susanne 2013-05-24T17:16:46 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48339 <pre>Great, thank you Alejandro - I will check out the code and let you know how it goes. In the mean time, I also found a small typo in the DEXSeqHTML function. The line results[which(is.na(results$pvalue)), ][, c("pvalue", "padjust")] = 1 breaks with an error if there are no NA pvalues, and can be patched by changing to: results[which(is.na(results$pvalue)),c("pvalue", "padjust")] = 1 While you are at it, it would also be useful if extraCols is indexed by geneIDs as rownames - that way we can send in extra info for as many genes in any order and it would be properly added to genetable for display in the DEXSeqHTML report. In detail, if you could change: genetable &lt;- cbind(extraCols, genetable) to genetable &lt;- cbind(extraCols[match(genetable$geneID, rownames(extraCols)),], genetable]) or something similar and change the documentation appropriatley, that would be quite helpful to users too! Thanks, Mani ________________________________________ From: Alejandro Reyes [alejandro.reyes-ge2Rx4W</pre> Narayanan, Manikandan (NIH/NIAID) [E] 2013-05-24T15:08:35 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48338 <pre>Fixed in minfi 1.7.4. Fixed an issue with GenomicMethylSet() and GenomicRatioSet() caused by a recent change to a non-exported function in the GenomicRanges package (Reported by Gustavo Fernandez Bayon &lt;gbayon-Re5JQEeQqe8AvxtiuMwx3w&lt; at &gt;public.gmane.org&gt;). Best, Kasper On Fri, May 24, 2013 at 8:57 AM, Kasper Daniel Hansen &lt; kasperdanielhansen-Re5JQEeQqe8AvxtiuMwx3w&lt; at &gt;public.gmane.org&gt; wrote: [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor</pre> Kasper Daniel Hansen 2013-05-24T14:27:54 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48337 <pre> Hi all, I'm using a package ExomeCNV to call LOH and got an error in step "Combine multiple positions into LOH segments" the.loh = multi.LOH.analyze(normal, tumor, all.loh.ls=list(eLOH), test.alpha=0.001, method="variance.f", sdundo=c(0,0), alpha=c(0.5,0.1)) Analyzing: Sample.1 Error in sort(abs(diff(genomdat)))[1:n.keep] : only 0's may be mixed with negative subscripts In addition: Warning message: In CNA(data$baf, strip.chr.name(data$chr), data$position, data.type = "binary") : markers with missing chrom and/or maploc removed ExomeCNV actually implement package DNAcopy in this step, and I can't tell how to bypass this problem since the "n.keep" isn't from ExomeCNV's code. I would really appreciate your expertise, thank you. -- output of sessionInfo(): R version 3.0.1 (2013-05-16) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] L</pre> Conan [guest] 2013-05-24T14:04:59 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48336 <pre>This sounds like the correct analysis; I will have a look today. Best, Kasper (maintainer) On Fri, May 24, 2013 at 4:35 AM, Gustavo Fernández Bayón &lt;gbayon-Re5JQEeQqe8AvxtiuMwx3w&lt; at &gt;public.gmane.org&gt;wrote: [[alternative HTML version deleted]] _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor</pre> Kasper Daniel Hansen 2013-05-24T12:57:54 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48335 <pre>Dear Manikandan Narayanan, Sorry for the delayed reply! Thanks for your e-mail! It has led us to spot two minor bugs and therefore modified the DEXSeq code in two aspects: Firstly, redundant terms were removed in DEXSeq in a very naive way: a lm.fit model was first fitted and the columns from the model matrix with NA coefficients were removed from the model matrix, now a proper function has been written for this purpose (with basically the code to what you also proposed). Secondly, our "if" statement that you mentioned was wrongly located within the function, which was causing your error message. It has been relocated and now it seems to work for its purpose ( I tested with your model frame and formula). You will find the changes in the last version of the svn (1.7.2). Let me know if it works for you or if you have additional questions. Best regards, Alejandro Reyes _______________________________________________ Bioconductor mailing list Bioconductor-0bNBQ1PAWB4BXFe83j6qeQ&lt; at &gt;public.gmane.org</pre> Alejandro Reyes 2013-05-24T12:19:07 http://permalink.gmane.org/gmane.science.biology.informatics.conductor/48334 <pre>Hi, I was trying to get the gene details of refseq ids (these are output from blastn) with the following code: =================   library(biomaRt)   mart &lt;- useMart("ensembl", dataset="hsapiens_gene_ensembl")   attr &lt;- c("refseq_mrna",'hgnc_symbol', 'chromosome_name','start_position','end_position')   ids &lt;- c("NM_001270493", "NM_001185076","NM_001185075","NM_001185082")     xx &lt;- getBM(attributes=attr,               filters = "refseq_mrna", values = ids, mart = mart)     print(xx) =============== The results are:    refseq_mrna hgnc_symbol chromosome_name start_position end_position 1 NM_001185075        FMR1               X      146993469    147032645 2 NM_001185076        FMR1               X      146993469    147032645 How can I get details of the other two refseq ids that do not show up in the results? thanks! Tim [[alternative HTML version deleted]] _______________________________________________ Bioconduct</pre> Tim Smith 2013-05-24T11:46:30 Search the mailing list at Gmane query http://search.gmane.org/?group=$group=gmane.science.biology.informatics.conductor