c version of VSN ? and Wolfgang's answer
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Roger Liu ▴ 260
@roger-liu-2141
Last seen 10.2 years ago
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@wolfgang-huber-3550
Last seen 3 months ago
EMBL European Molecular Biology Laborat…
Dear Roger, normalization (in the sense of vsn, and of most other people) is a procedure between arrays that have the same features, but different samples. What you have is the different feature but the same samples. Still, you have answered my questions that I asked in response to yours: - what version are you using? - have you seen and used the "subsample" option? Best wishes Wolfgang ------------------------------------------------------------------ Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber Roger Liu wrote: > As suggested by Wolfgang, I send this question to bioconductor mail list and > I would like to hear other expert's feedback the message is as below with a > bit modification: > > > another question: > which way you think is a better solution for normalization with using vsn, > you suggested normalize each array separately, in fact the 30 arrays form a > whole genome data set, should normalizing them as a whole data set be a > better way? > >> I have been using vsn package of R to normalize NimbleGen's ENCODE tiling > arrays >> (383000 probes), and vsn gave us very good results. Now,We are trying data >> analysis for NimbleGen whole genome tiling arrays, which is a very large >> dataset (30 arrays,total more than 22000000 probes). I combined all of > these >> array intensity data together, and tried doing within array vsn > normalization >> for this combined large dataset. Since in fact the 30 arrays should be > consider a whole array set > Apparently, because of the size of the data >> set, I can not run vsn packages of R (memory problem). Therefore, I am >> wondering if you have a c version vsn or any other methods to deal with > such >> huge datasets. >> >> Thank you very much. >> >> roger > > > > which version are you using? Please consider version >= 2.0.35 (from > www.bioconductor.org), the function "vsn2" is already written in C. Also > please consult the function parameter "subsample". > > I think you should normalize each array separately. I have very > successfully used vsn for tiling arrays with 6.5 Mio probes. > > Also, for this type of question of general interest, please use the > bioconductor mailing list! (See link on > http://www.bioconductor.org<https: webmailapp4.cc.utexas.edu="" horde-="" 2.2.9-assign="" util="" go.php?url="http%3A%2F%2Fwww.bioconductor.org&amp;Horde=0" be2d1ba79b54c02c71a2cf118f20902=""> > ) > That way you get feedback from many other experts as well, other users > also benefit, and the discussion remains searchable in the archives. > > Best wishes > Wolfgang
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Dear Roger, > But I still have the question about normalization, > As for ENCODE tiling arrays which have about 383k probes, I have two > biological replicates, which permitted me to perform BetweenArray > normalization with vsn. The result is great. > > Now, as for whole genome tiling array set that has 30 arrays ( as you said > different features but the same sample) I only have one biological > replicate, therefore, I can only do WithinArray normalization.Which way you > think it's a better solution, or the results are similar: > 1. perform vsn for each array, > 2. combine the 30 arrays together(as a large single array), then perform > vsn Both of these will not work. vsn is for normalizing between multiple arrays of the same design, on which there are different (but related) samples. I have no good idea how to normalize your data, maybe you should ask the people who designed the experiment. Best wishes Wolfgang ------------------------------------------------------------------ Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber
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