I thank you for your replies Kasper. The answer on the first one: nrow(RGset) gives me 622399 features. On Tue, Sep 4, 2012 at 3:02 PM, Kasper Daniel Hansen < kasperdanielhansen@gmail.com> wrote: > On Tue, Sep 4, 2012 at 4:09 AM, pooja mandaviya > <pooja.mandaviya@gmail.com> wrote: > > Hi all, > > > > I am kind of new to using R and I have recently started working with > > Illumina 450K methylation chip and am trying to use the package "minfi" > for > > my 780 sample data. While I run my data, I was stuck at small errors and > > doubts which I wanted to ask and request for your help. I here list them > > below. > > > > 1) densityPlot (RGset, sampGroups = pd$Sample_Group, main = "Beta", xlab > = > > "Beta") > > > > For this, i get an error saying, > > Error in density.default(newX[;i],...): > > need at least 2 points to select a bandwidth automatically. > > I get the above error most of the time with most of the datasets i run. > > Could you help me know how do I get rid with it? > > This looks weird, given that I would expect your RGset to have > 100,000's of rows. What does > nrow(RGset) > tell you? > > > 2)Mset.swan <- preprocessSWAN(RGsetEx, MsetEx) > > > > While running this command, it always says, > > Normalizing array 1 of 6 > > Normalizing array 2 of 6 > > & so on.. > > My question here is that it always shows this and always normalizes the > > first 6 arrays/samples, but how about the other datasets having more > than 6 > > samples? I sometimes run a dataset of 100-150 samples. It still shows > > normalizing 6 samples. How about the rest of the samples? > > Well, I hope you use your own data instead of RGsetEx, MsetEx. The i > out of n message uses the number of columns (samples) of the input > data. > > > 3) Most of the test datasets run fine, apart from small errors which i > > listed above. I am also able to get the final plots. However, my main > > dataset which i have to work on, contains 780 samples. I have tried > running > > this through minfi as well. But I always get errors running through most > of > > the commands with it. Just to list them here; For commands like QCReport, > > densityBeanPlot, controlStripPlot, MSet.norm getBetam getM & mdsPlot, I > get > > similar errors like > > > >> Error: cannot allocate vetor of size 3.6 Gb. > >> Warning: BISULFITE Conversion 2 probes outside plot range. > > So my question is that, is minfi not able to support very large datasets? > > (In my case: 780 samples) > > You either need more RAM or you need to run a 64bit R, perhaps both. > > > 4) Last question: While normalizing, does minfi also take care of all the > > batch effects? > > No, in general you do not remove batch effects by normalization. > > > -- > > Best Wishes, > > > > Pooja Mandaviya > > Department of Clinical Chemistry > > Erasmus Medical Center, Rotterdam > > The Netherlands > > p.mandaviya@erasmusmc.nl > > > > > -- Best Wishes, Pooja Mandaviya Department of Clinical Chemistry Erasmus Medical Center, Rotterdam The Netherlands p.mandaviya@erasmusmc.nl [[alternative HTML version deleted]]