Because the deep sequencing experiment is very expensive (at least to some not so rich labs), we cannot do a biological replication. We try to find some hints through RNA-seq, then do benchmark experiment to valid the sequencing results. On Tue, Feb 4, 2014 at 9:23 AM, Fabrice Tourre <fabrice.ciup at="" gmail.com=""> wrote: > Alejandro, > > Thank you very much. Yes. I have only one control and one knockdown, > without replication. Do you have any suggestions how can I get the > differences in exon in two condition. Or different alternative > splicing in two different condition. DESeq2 can do this? > > On Tue, Feb 4, 2014 at 9:18 AM, Alejandro Reyes <alejandro.reyes at="" embl.de=""> wrote: >> Dear Fabrice Tourre, >> >> Thanks for your answers. If I understood correctly, you have only one >> control and one knockdown, without replication? The errors are likely >> because of this (sorry if the messages are not informative enough!). >> >> DEXSeq is designed to work with replicated data in order to distinguish >> biological variation from differences between your different biological >> conditions. Unfortunately, if you have no replicates in your experiment you >> won't be able to estimate variation across replicates, therefore not be >> able to test for differences in exon usage across biological conditions. >> There are many papers (e.g. doi:10.1186/gb-2010-11-10-r106, >> 10.1038/nprot.2013.099, 10.1101/gr.133744.111) and discussions (e.g. in >> SeqAnswers) about why this is relevant. >> >> Best regards, >> Alejandro >> >> >> >> >> >> >>> I am analyzing mouse samples. >>> >>>> any( duplicated( paste( geneIDs(ecs), exonIDs(ecs), sep=":") ) ) >>> >>> [1] FALSE >>> >>>> any( duplicated( featureNames(ecs)) ) >>> >>> [1] FALSE >>> >>>> design(ecs) >>> >>> >>> countFile >>> >>> ~/projects/seqdata/data/tophat2/sample1/sample1.counts >>> ~/projects/seqdata/data/tophat2/sample1/sample1.counts >>> >>> ~/projects/seqdata/data/tophat2/sample2/sample2.counts >>> ~/projects/seqdata/data/tophat2/sample2/sample2.counts >>> >>> condition >>> libType >>> >>> ~/projects/seqdata/data/tophat2/sample1/sample1.counts control >>> paired-end >>> >>> ~/projects/seqdata/data/tophat2/sample2/sample2.counts knockdown >>> paired-end >>> >>> On Tue, Feb 4, 2014 at 3:39 AM, Alejandro Reyes <alejandro.reyes at="" embl.de=""> >>> wrote: >>>> >>>> Dear Fabrice Tourre, >>>> >>>> Thanks for your interest in DEXSeq and for the report! >>>> Some questions to get to the details of the warnings and >>>> the error message: >>>> >>>> 1. what is the output of doing: >>>> >>>> any( duplicated( paste( geneIDs(ecs), exonIDs(ecs), sep=":") ) ) >>>> any( duplicated( featureNames(ecs)) ) >>>> >>>> 2. What is the output of design(ecs) of your ExonCountSet object? >>>> >>>> Best regards, >>>> Alejandro >>>> >>>> >>>> >>>>> Dear expert, >>>>> >>>>> When I use DEXSeq to find different expressed exon, I got this error. >>>>> In my analysis, I only have two samples, one is case, one is control. >>>>> >>>>> ecs <- estimatelog2FoldChanges( ecs ) >>>>> Error in `row.names<-.data.frame`(`*tmp*`, value = c("geneID", "exonID", >>>>> : >>>>> duplicate 'row.names' are not allowed >>>>> In addition: There were 50 or more warnings (use warnings() to see the >>>>> first 50) >>>>> >>>>> >>>>> warnings() >>>>> Warning messages: >>>>> 1: In chol.default(XVX + lambda * I, pivot = TRUE) : >>>>> the matrix is either rank-deficient or indefinite >>>>> >>>>> >>>>> >>>>> sessionInfo() >>>>> R version 3.0.0 (2013-04-03) >>>>> Platform: x86_64-unknown-linux-gnu (64-bit) >>>>> >>>>> locale: >>>>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C >>>>> [3] 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 >>>>> [7] LC_PAPER=C LC_NAME=C >>>>> [9] LC_ADDRESS=C LC_TELEPHONE=C >>>>> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C >>>>> >>>>> attached base packages: >>>>> [1] parallel stats graphics grDevices utils datasets methods >>>>> [8] base >>>>> >>>>> other attached packages: >>>>> [1] DEXSeq_1.8.0 Biobase_2.22.0 BiocGenerics_0.8.0 >>>>> >>>>> loaded via a namespace (and not attached): >>>>> [1] biomaRt_2.18.0 Biostrings_2.30.1 bitops_1.0-6 >>>>> [4] GenomicRanges_1.14.4 hwriter_1.3 IRanges_1.20.6 >>>>> [7] RCurl_1.95-4.1 Rsamtools_1.14.2 statmod_1.4.18 >>>>> [10] stats4_3.0.0 stringr_0.6.2 XML_3.98-1.1 >>>>> [13] XVector_0.2.0 zlibbioc_1.8.0 >>>>> >>>>> _______________________________________________ >>>>> 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 >>>>> >>