Re: [R] Curve fitting,FDA for biological data
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
>>> 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@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
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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@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@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.
>
>
--
View this message in context:
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and provide commented, minimal, self-contained, r
Re: [R] Curve fitting,FDA for biological data
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 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@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@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@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.
Re: [R] Curve fitting,FDA for biological data
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 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@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@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. > > -- View this message in context: http://www.nabble.com/Curve-fitting%2CFDA-for-biological-data-tp22868069p22906065.html Sent from the R help mailing list archive at Nabble.com. __ R-help@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.
Re: [R] Curve fitting,FDA for biological data
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 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@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@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.
Re: [R] Curve fitting,FDA for biological data
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@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] Curve fitting,FDA for biological data
Dear all, Another newbie just got attracted to this mailing list. I am a biologist currently working my way through R, had sort play around with python earlier this year. I have some data exhibiting periodicity ** my data consists of peaks and valleys, with peaks arising due to the presence of a repetitive structural unit,** with x being a reference grid (position along a chromosome) and y being strength of signal (this y signal fluctuates to give rise to the peaks and valleys). ie presence of a structural unit along a chromosome gives rise to a peak in my data. I would like to use a curve fitting algorithm (I guess something like a fourier analysis and/or splines). Due to the nature of the data I would like to look for periodicities at different scales (along the x grid). So say 2-4 different splines/curves are probably enough to describe the 40,000 occourences of the repetitive structural unit in my data, while say 4-6 of these units could exhibit certain patterns in the way they group together. I assume in my case, I can consider my x axis (position) to be equivalent to a time x axis as in signal processing. I considered using the FDA package (silverman and ramsey I think). Does anyone have an ideas if this is the right way to go or suggestions etc PS I have highlighted in the attached gif with red, the occourence of the repetitive signal (differences in the wavelength for example could be important but not more than 4 would be required to fit all data), and in yellow a hypothetical occourence of a periodicity in a different scale Thanks a lot Dr Triantafyllos Gkikopoulos The University of Dundee is a registered Scottish charity, No: SC015096 __ R-help@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.
