[R] Curve fitting,FDA for biological data

[trias]

Hi Thanks a lot,

 I think you have covered the things I want to do for now so I will try to
implement them as soon I can.

<< A finite Fourier series could be the best tool IF the the multiple
periodicities are all integer fractions of a common scale.>>

 This is certainly true for my repetitive "unit" (the smallest data peak) so
I hope this makes things easier.

 Thanks



spencerg wrote:
> 
> Dear Dr Gkikopoulos: 
> 
> 
>       1.  Have you looked at "bioconductor.org"?  They have substantive 
> extensions to R specifically for "genomic data", which I assume would 
> include chromosome. 
> 
> 
>       2.  To "identify periodicities at different timescales", I agree 
> with Stephen that "spectrum" would likely help. 
> 
> 
>       3.  The best software to "fit data into discrete number of curves" 
> depends on the particular "discrete number of curves" you want to 
> consider and how you want to "fit data into" them.  A finite Fourier 
> series could be the best tool IF the the multiple periodicities are all 
> integer fractions of a common scale.  In that case, using a "fourier" 
> base in the "fda" package could be your method of choice.  Otherwise, 
> you might consider Bayesian Model Averaging.  RSiteSearch("Bayesian 
> Model Averaging") produced 80 hits for me just now, and 
> RSiteSearch("Bayesian Model Averaging", "function") produced 60.  
> "RSiteSearch.function" in the "RSiteSearch" package [available via 
> install.packages("RSiteSearch",repos="http://r-forge.r-project.org")] 
> told me that 27 of the 60 were in the "ensembleBMA" package, and another 
> 14 were in the "BMA" package. 
> 
> 
>       4.  The best way to "compare data from different experiments" 
> depends on your evaluation of "3" above.  The "fda" package includes an 
> "fRegress" function that might be useful. 
> 
> 
>       Hope this helps. 
>       Spencer Graves
>       
> 
> trias wrote:
>> There are a couple of different goals for this projects
>>
>>  *identify periodicities at different timescales (ie different dT)
>>  *fit data into discrete number of curves, ie 6 different basic functions
>> should be enough to describe the basic repeating elements in this data
>> (ie 6
>> different categories of peaks)
>>  *comapre data from different experiments of the same "time" reference
>> (in
>> my case this is location on chromosome) for changes in the underlying
>> basic
>> elements (ie changes of the basic funtions,periodicity etc)
>>
>>  I think if I can find a strategy to answer some of these question I be
>> in a
>> good position to explore this data analysis further if needed.
>>
>>  Thanks a lot
>>
>>
>>
>> stephen sefick wrote:
>>   
>>> What is your end goal?  If it is to try and account for the
>>> variability of the "timeseries" you may want to look at ?spectrum
>>> If it is to model the periodicity...
>>>
>>> Stephen Sefick
>>>
>>> On Fri, Apr 3, 2009 at 11:30 AM, trias <t.gkikopoulos at dundee.ac.uk>
>>> wrote:
>>>     
>>>> Here is the gif that didn't come through earlier
>>>> http://www.nabble.com/file/p22870832/signal.gif signal.gif
>>>> --
>>>> View this message in context:
>>>> http://www.nabble.com/Curve-fitting%2CFDA-for-biological-data-tp22868069p22870832.html
>>>> Sent from the R help mailing list archive at Nabble.com.
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org 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.
>>>>
>>>>       
>>>
>>> -- 
>>> Stephen Sefick
>>>
>>> Let's not spend our time and resources thinking about things that are
>>> so little or so large that all they really do for us is puff us up and
>>> make us feel like gods.  We are mammals, and have not exhausted the
>>> annoying little problems of being mammals.
>>>
>>> 								-K. Mullis
>>>
>>> ______________________________________________
>>> R-help at r-project.org 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.
>>>
>>>
>>>     
>>
>>
> 
> ______________________________________________
> R-help at r-project.org 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.
> 
> 

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