Dear all My name is Pepijn Kooij, PhD student at the Centre for Social Evolution, Copenhagen University. I was grateful to find the ReadqPCR and NormqPCR packages to analyze my rt-qPCR data. I managed to use both packages, loading in my data and normalizing it. In the end using the deltaDeltaCt() function I am able to retrieve the table with all the data I need. My question now is, is there a way or package to go further from this? As in, I am interested to see which of the genes have a foldchange above a threshhold of 1, is there a way to see that? And, is it possible to plot the 2^∆∆Ct values in a bargraph with SD's or SE's? I hope you can help me out with this, Best regards Pepijn Kooij _______________________________________ Pepijn Kooij, PhD student Centre for Social Evolution, Department of Biology University of Copenhagen Universitetsparken 15, bygning 12 2100 Copenhagen Ø Denmark Tel: (+45) 35 32 13 41 Email: pkooij@bio.ku.dk CSE website: http://www.bi.ku.dk/cse [[alternative HTML version deleted]]

HI Pepijn Thanks for your interest. >My question now is, is there a way or package to go further from this? As in, I am interested to see which of the genes have a foldchange above a threshhold of 1, is there a way to see that? By a "foldchange threshold of 1", do you mean a doubling or halving? i.e. |logFC | > 1? If so you can find everything in your ddCt output data.frame that meets this criteria and look at only these genes. ddCtRes[abs(log2(as.numeric(as.vector(ddCtRes$`2^-ddCt`)))) > 1,] For the gene IDs alone this will work: ddCtRes[abs(log2(as.numeric(as.vector(ddCtRes$`2^-ddCt`)))) > 1,"ID"] This is assuming you have done something with the undetermined values, if you have "+"s and "-"s for your 2^ddCt values it gets a bit more involved. >And, is it possible to plot the 2^∆∆Ct values in a bargraph with SD's or SE's? I hope you can help me out with this, It is possible, you could use something like barplot2 from gplots and plot the min 2^-ddCt.min and max values 2^-ddCt.max as upper and lower confidence intevals. The min and max values are calculated along the lines of http://www.ncbi.nlm.nih.gov/pubmed/11846609, and the error bars will be assymetric if you plot the x axis in non-log space, since the Ct values from which SD worked out on arithmetic scale but then gets 2^ddCT+/-SD. arguments to barplot2 something like: plot.ci=TRUE, ci.l=MIN2^DDCTS, ci.u=MIN2^DDCTS, Hope this helps, let me know if you have any issues with the plotting, and if you want to send me a more concrete example I can give some more focused code. Cheers, Jim On 8 February 2012 16:32, Pepijn Kooij <pkooij@bio.ku.dk> wrote: > Dear all > > My name is Pepijn Kooij, PhD student at the Centre for Social Evolution, > Copenhagen University. > I was grateful to find the ReadqPCR and NormqPCR packages to analyze my > rt-qPCR data. I managed to use both packages, loading in my data and > normalizing it. In the end using the deltaDeltaCt() function I am able to > retrieve the table with all the data I need. > My question now is, is there a way or package to go further from this? As > in, I am interested to see which of the genes have a foldchange above a > threshhold of 1, is there a way to see that? > And, is it possible to plot the 2^∆∆Ct values in a bargraph with SD's or > SE's? > I hope you can help me out with this, > > Best regards > Pepijn Kooij > _______________________________________ > Pepijn Kooij, PhD student > Centre for Social Evolution, Department of Biology > University of Copenhagen > Universitetsparken 15, bygning 12 > 2100 Copenhagen Ø > Denmark > > Tel: (+45) 35 32 13 41 > Email: pkooij@bio.ku.dk > CSE website: http://www.bi.ku.dk/cse > > > [[alternative HTML version deleted]] > > > _______________________________________________ > 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 > [[alternative HTML version deleted]]