On 7/19/06, hadley wickham <[EMAIL PROTECTED]> wrote: > > Can you be a bit more excact? I a biologist and relatively new to R > > In that case, I would _strongly_ advise that you get advice from a > local statistician.
I am afraid that, by comparison, I am the local statistican. I am also the local R-guru, and neither is saying much - so please bear with me. Do you know of some functions (built in hopefully) that I can try? I did try the density estimate from the Mclust package, but got an out of memory error. I did look at the Ash package, but I am afraid I failed to see how I can use it. At the moment, I am estimating the density, using the stats density(), identify the peaks in the density estimate by Petr's function, and can thus extract a very good suggestion for a mean and intensity for each peak - surely that must be useful for something? Based on the literature I also have a very good suggestion for at upper and lower width of the distribution. > > > I am measureing the amount of DNA in cells, and I need to know the > > percentage of cells in a part of the cell cycle; that the percentage > > of cells in the first peak, in the second peak and so on. I want to > > integrate the area between to two cells, because that apparently is > > how its none (as far as I can tell from the literature) > > That doesn't sound quite right to me, because you also need to take > into account the fact that some cells between peak 1 and 2 belong to > peak 1, and some to peak 2. This is something that will come out > immediately from a mixture based approach. If you know that peaks > correspond to certain parts of the cell cycle, then this is important > information that should be included in the analysis. I realise that some cells between to peaks belong to the peaks, but thought that this was a general problem, usually sacrificed for speed. One of the most widely used programs for analysing cell cycle use a variant of my strategy as far as I can tell; fitting Gaussian distributions to the two peaks and integrate the part between. The reason why I am not using this program is that I cannot afford it, and it does a very poor job when analysing cells with abnormal amounts of DNA. Ulrik -- Blog: http://ulrikstervbo.blogspot.com ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
