Dear Jose, It seems to me that you have a vary good idea about R and Bioconductor. I'm a bit new in this R and Bioconductor. could you please tell me how can I get spot mean intensity and standard deviation from a .CEL file? Best regards, -- Mamun
Jose de las Heras-2 wrote: > > > You could attempt to normalise with Excel. But it's not the best way. > If you're going to analyse microarrays, I recommend you use something like > Limma (linear models for microarray data). > > You can use Limma to take your raw data and so several type of diagnostic > tests to check the quality. Then you can apply a number of types of > background correction, normalisation (both within each array for Cy3/Cy5, > and between arrays), and producing a list of differentially expressed > genes > with stats etc. > And all kinds of plots, highlighting genes individually or in groups... > In addition, the sorting and subsetting abilities of limma are more > powerful > and faster than Excel. > > Ok, the downside is that limma is command-line based. So you do have to > spend a little time learning how to use it. But it's easy. There's a users > guide that takes you step by step through several worked examples showing > you how to do most things you'd want to do, and in a couple of days you'd > be > running with your data. It'll be a good investment. > > Limma is a package from the BioConductor project. BioConductor is a group > of > packages designed for the analysis of microarray data. You'll find apart > from limma other tools that will allow you to do clustering analysis, > linking to gene ontology databases and all sorts of stuff. I am only > really > familiar with Limma. > All these are based around the statistical-oriented programming language > R. > > All these are free, with extensive help documentation and there's also a > BioConductor forum where you can get very useful help if you get stuck > somewhere. > > All you need to do is go to: > > http://cran.r-project.org/ > > and download and install the latest version of R for your platform > (windows, > mac, unix) > > then, from the same page above, on the left you find a number of links. > One > is "packages". Go there, and download the zip file for "limma". Next, run > R, > and from the top menu select "install package from zip file", and select > the > limma one. You're done. Then check the user's guide included in the limma > folder and start working through the example. > > It's also useful to go to the BioConductor site: > > http://www.bioconductor.org/ > > The BioConductor site has lots of information and there you can find the > link to the BioC forum I mentioned. It gets updated less frequently than > the > info in the R project site above, so it's best to get your R and Limma > from > the first website. > > That would be my preferred option, and one that will serve you well > forever. > > If you find the command-line version of Limma a bit hard going, there's a > version with a graphical interface (GUI) called limmaGUI. You can get it > from: > > http://bioinf.wehi.edu.au/limmaGUI/ > > If you use windows, you can download a single file that will install R > version 2.1.1 and LimmaGUI and all the packages to make it work together > in > one go. > This is the simplest way to get started, in 20 minutes, you'll be up and > running with your data normalised etc. The problem I see is that the > options > are limited, compared to straight command-line based limma. But you can > get > around it by typing your own commands ina window that you can open from > LimmaGUI. Still... if you're going to use limma commands I'd rather do it > all from the beginning, but... you may prefer it, check it out. > > In addition to that, I find the TM4 suite for microarray analysis from > TIGR > very useful.And it's also free. Check it out at: > > http://www.tm4.org/ > > There you get SpotFinder, which you can sue to quantitate your images (you > won't need that as I guess you use GenePix... I also use GenePix now, but > started with SpotFinder, and I still go back to SpotFinder a lot. I like > how > you can click on spots on a plot and it'll show you the actual spot > intensities, annotation etc... I know GenePix does something similar, but > I > like SpotFinder's evrsion better). > > You also get MIDAS. MIDAS allows you to normalise data and so some > filtering > based on a number of conditions. MIDAS takes the output from SpotFinder, > but > you can convert your GPR files to MEV format (the one used by SpotFinder) > using their tool ExpressConverter, and then use that for MIDAS. Apparently > the new version of MIDAS (notout yet) will take GPR files directly, and > other nice improvements, but they haven't told me when it'll be out. > > And you also get TMEV. You can use MEV and GPR files as input. TMEV does > clustering analysis and it's quite nice. > > I mainly use Limma to start, and later use TMEV (either from GPR files of > the MEV ones) if I want to do clustering etc. > > I am very slowly writing a little "easy" guide to use these programs to d > some simple data normalisation and analysis, for use in our lab... it > saves > me a lot of time if I can give it to a new person and they familiarise > themselves before we start. It's still unfinished and has many gaps.. but > the Limma and LimmaGUI part is pretty much complete.. if you want it I'll > email it to you. > > I hope this helps! > > good luck with you arrays > > Jose > > > > > > "gberna" <gbe...@gmail.com> wrote in message > news:1145462502.719792.29...@u72g2000cwu.googlegroups.com... >> Dears, >> I have some problems about how to analyze my data: >> I'm processing some microarray with protein . >> On every slide, I made an hybridization on slide with peptides and my >> antibody was colored with Cy3 and Cy5. >> In this case the the spots would have to be the same one (becouse cy3 >> and cy5 are the same one), in fact I see a yellow spot >> Query: >> How can I process this data? >> Using excel I calculated log 2 (cy3median-bkg/cy5median-bkg) >> How can I normalize the data? >> Can you help me? >> >> I want to see the report between for example the prtA_phosfo/prtA (2 >> peptides on slides)and I don't know which data I must consider. >> >> I hope that someone have understood this delirious post. >> thanks, >> >> guido >> >> PS >> sorry for my english >> I use GPR file >> > > > _______________________________________________ > Methods mailing list > Methods@net.bio.net > http://www.bio.net/biomail/listinfo/methods > > -- View this message in context: http://old.nabble.com/microarray_normalization_Help%21%21%21-tp3993932p28803828.html Sent from the Bio.net - Methods mailing list archive at Nabble.com. _______________________________________________ Methods mailing list Methods@net.bio.net http://www.bio.net/biomail/listinfo/methods
