Hi Pap a few comments in addition to what has already been said: - If you have very different library sizes, it is normal that you see less changes in direction from the shallowly sequenced condition to the deeply sequenced one. This is because your power depends on the abolute read count, due to Poisson noise. Hence, if a gene has many reads in the shallow condition and few in he deep one, you have better power to say whether this is real than in the opposite case. - However, in your case, the differences in size are less than 1:2, which is usually not much a problem. Must be something else. Maybe post an MA plot. - I am worried that you used RSEM for quantification. RSEM infers isoform abundances, i.e., each count value has a specific uncertainty attached due to the ambiguity in assigning reads mapping to shared exons, and this uncertainty can be huge and dramatically inflate false positives if a subsequent test is not informed of them. DESeq is not designed to work with RSEM, and the uncertainty information will get a lost. (Actually, it isn't even calculated, if you run RSEM in EM rather than Bayes mode, IIRC.) - I'm not convinced that removing PCR duplicates in RNA-Seq is a good idea. If you have 50 bp single-end reads, you constrain the value range of your counts to 0:50, i.e., you lose all the advantages in dynamic range that RNA-Seq has over microarrays. Simon

Thanks Simon, Can you please recommend me on different tool for quantification that suitable with DESeq? Thanks, Pap On Mon, Jun 18, 2012 at 10:20 AM, Dror Hibsh <drordh@gmail.com> wrote: > i am doing de novo assembly, that is why i am using raw reads(unaligned) > Thanks! > > > On Mon, Jun 18, 2012 at 8:24 AM, Dror Hibsh <drordh@gmail.com> wrote: > >> Hi Tim, Thanks for the response! >> No i didnt.. >> Is there any recommended tool for removing the pcr duplicates from raw >> reads? >> >> Thanks, >> Pap >> >> >> >> On Sun, Jun 17, 2012 at 7:29 PM, Tim Triche, Jr. <tim.triche@gmail.com>wrote: >> >>> you say you are "new to this field" yet you seem to have done almost >>> everything right. >>> >>> have you tried removing PCR dupes that might be skewing your results, >>> before transcript assembly with RSEM and DE testing? >>> >>> >>> >>> On Sun, Jun 17, 2012 at 9:23 AM, papori [guest] <guest@bioconductor.org>wrote: >>> >>>> >>>> Hi all, >>>> First of all, I am new to this field so i am sorry if i am not clear.. >>>> >>>> I will try to explain what is my aim, and what i did before DESeq. >>>> >>>> I am trying to do Differential expression analysis using DESeq for >>>> De-Novo invertebrate . >>>> >>>> We had an experiment of 3 conditions with 3 biological replicate for >>>> each.(total of 9 samples) >>>> We used hiseq2000 50bp single end reads. >>>> We had a different library size for each.(that was single cell >>>> experiment so we had amplification step.. what yield variance in the >>>> library sizes..) >>>> >>>> We reconstructed the transcriptome using Trinity. >>>> Estimating counts with RSEM. >>>> >>>> And then i used DESeq.. >>>> >>>> i have weird behavior of the data, and i dont know if it is because >>>> something wrong that i did.. >>>> >>>> i am always getting down-expression from condition 1 to condition 2 and >>>> high-expression from condition 2 to condition 3.(for all the transcripts, >>>> no out-layers..) >>>> >>>> The number of counts that got for each condition to reference >>>> transcriptome was: >>>> 32M, 27M, 40M respectively.. >>>> What made me to think that because cond 2 has lowest count it has a >>>> behavior of down-expression from 1 to 2 and high-expression from 2 to 3.. >>>> >>>> if my conclusion is right, i am in a big mass..(Normalization??) >>>> >>>> my DESeq script is: >>>> Conditions = c("C1", "C2", "C3", "C1", "C2", "C3","C1", "C2", "C3") >>>> Counts<-round(MultiGeneMat,0) >>>> cds <- newCountDataSet(Counts,Conditions) >>>> cds <- estimateSizeFactors(cds) >>>> cds <- >>>> estimateDispersions(cds,method="per- condition",sharingMode="maximum",fitType="local") >>>> >>>> res_1vs2 <- nbinomTest(cds,condA="C1",condB="C2") >>>> sigDESeq_1vs2 <- res_1vs2[res_1vs2$padj <= 0.1, ] >>>> sigDESeq_1vs2 <- na.omit(sigDESeq_1vs2) >>>> >>>> res_2vs3 <- nbinomTest(cds,condA="C2",condB="C3") >>>> sigDESeq_2vs3 <- res_2vs3[res_2vs3$padj <= 0.1, ] >>>> sigDESeq_2vs3 <- na.omit(sigDESeq_2vs3) >>>> >>>> res_1vs3 <- nbinomTest(cds,condA="1",condB="C3") >>>> sigDESeq_1vs3 <- res_1vs3[res_1vs3$padj <= 0.1, ] >>>> sigDESeq_1vs3 <- na.omit(sigDESeq_1vs3) >>>> >>>> >>>> >>>> Is there anything wrong here? or anywhere else?? >>>> If i wasnt clear enough so tell me in what and i will try to explain.. >>>> Any help will be appreciate here! >>>> Thanks, >>>> Pap >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> -- output of sessionInfo(): >>>> >>>> R version 2.14.0 (2011-10-31) >>>> Platform: x86_64-unknown-linux-gnu (64-bit) >>>> >>>> locale: >>>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C >>>> LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 >>>> [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=C >>>> LC_NAME=C >>>> [9] LC_ADDRESS=C LC_TELEPHONE=C >>>> LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C >>>> >>>> attached base packages: >>>> [1] stats graphics grDevices utils datasets methods base >>>> >>>> other attached packages: >>>> [1] edgeR_2.4.6 limma_3.10.3 DESeq_1.6.1 locfit_1.5-8 >>>> Biobase_2.14.0 >>>> >>>> loaded via a namespace (and not attached): >>>> [1] annotate_1.32.3 AnnotationDbi_1.16.19 DBI_0.2-5 >>>> genefilter_1.36.0 geneplotter_1.32.1 >>>> [6] grid_2.14.0 IRanges_1.12.6 lattice_0.20-6 >>>> RColorBrewer_1.0-5 RSQLite_0.11.1 >>>> [11] splines_2.14.0 survival_2.36-14 tools_2.14.0 >>>> xtable_1.7-0 >>>> > >>>> >>>> >>>> -- >>>> Sent via the guest posting facility at bioconductor.org. >>>> >>>> _______________________________________________ >>>> Bioconductor mailing list >>>> Bioconductor@r-project.org >>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>> Search the archives: >>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>> >>> >>> >>> >>> -- >>> *A model is a lie that helps you see the truth.* >>> * >>> * >>> Howard Skipper<http: cancerres.aacrjournals.org="" content="" 31="" 9="" 1173.full.pdf=""> >>> >>> >> >> >> -- >> ----------------- >> Dror Hibsh >> 0507-669599 >> ------------------ >> >> > > > -- > ----------------- > Dror Hibsh > 0507-669599 > ------------------ > > -- ----------------- Dror Hibsh 0507-669599 ------------------ [[alternative HTML version deleted]]