Dear Lucia, We have compared RNA-seq to microarrays on exactly the same RNA samples for several studies. We consistently find that sequence depths of 10 millions reads or so are sufficient to get substantially more sensitivity from RNA-seq than from microarrays, but only when using some RNA-seq analysis pipelines. Our RNA-seq pipeline uses Rsubread and featureCounts to get genewise counts, then either voom or edgeR to the differential expression analysis. Voom is attractive for this comparison because it ensures closely comparable analyses for RNA-seq as for the microarrays. See slides 40-43 of a talk I gave last year: http://bioinformatics.org.au/ws12/program for a comparison of Illumina microarrays vs Illumina sequencing for a particular set of RNA samples. This shows that both microarrays and sequencing performs well, but RNA-seq gives a greater dynamic range and finds more genes. In particular it finds lots of genes that were not even represented on the microarrays. This is our typical experience. Best wishes Gordon > Date: Wed, 22 May 2013 15:57:52 -0400 > From: Lucia Peixoto <luciap at="" iscb.org=""> > To: Wolfgang Huber <whuber at="" embl.de=""> > Cc: bioconductor at r-project.org list [bioconductor at r-project.org] > <bioconductor at="" r-project.org=""> > Subject: Re: [BioC] [Bioc] RNAseq less sensitive than microarrays? Is > it a statistical issue? ... > In any case, I have not been able to find a study in which microarrays and > RNAseq are compared head to head in multiple biological replicates of the > same samples. I am not that familiar with the RNASeq literature but, > can it be possible that when dealing with biological (not technical ) noise > at the gene level it is still better to use microarrays? > > Lucia ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}