Hi Jarod On 14/07/14 17:12, jarod_v6 at libero.it wrote: > So I have attached all the mails. Please always take your time to read through the replies before asking the next question. And please structure your question in the form of eplaining first what you did, then what you expected to get that way, and finally what you got instead. Just pasting together all the various pieces of code you have tried so far is not helpful for us to figure out the issue. And, as both Mike and I asked you before multiple times: Please do not crosspost to the bioc-level list but do keep the bioconductor list on CC. These two lists are not the same! > However the problem remain and I think it is always the same. You have posted below snippets of all the different pieces of code that you have posted so far. Of course, your problem remains, if you keep using the same code. What you should do is to use resGA2 <- results(dds, lfcThreshold=1, altHypothesis="greaterAbs") to do the test you want. Why are you still trying to use other ways to call 'results' even though I have explained to you twice that they are not what you want and you agreed? Then, you should use 'subset' to find the significant genes. You don't get any significant hits this way. It seems that your noise level is too high to say for any of your genes with statistical confidence that the log2 fold change is stronger than +/-1. Maybe you should use a smaller threshold. Note in this context that our suggestion to test for significance of exceeding a threshold is not (yet?) that established in expression analysis. A more common approach is to get a list of all genes whose fold-change is significantly different from zero, and then narrow down this list to those genes whose _estimate_ shows a log2 fold change stronger than +/-1. As we explain in our paper, we feel that this standard procedure is not appropriate to do what people actually want to do. However, in terms of stringency, _testing_ for an absolute log2 fold change of more than 1 is much more stringent than testing for a non-_zero_ fold-change and then using only those with an LFC estimate exceeding 1. Hence, if you want to get a significance level comparable to the latter by doing the former, you need to be more lenient with your threshold. Simon