R help - Apr 2008 - Suggestions: Terminology & Pkgs for following spectra over time

Hi Folks... No code to troubleshoot here.  I need some suggestions about the
right terminology to use in further searching, and any suggestions about R
pkgs that might be appropriate.

I am in the planning stages of a project in which IR, NMR and other spectra
(I'm a chemist) would be collected on various samples, and individual
samples would be followed over time.  The spectra will be feature
rich/complex, so one can't see the changes by visual inspection.  The
spectra are basically 2D matrices: peaks as a function of frequencies.  So
the data set is in the form of spectra of a single sample over time, for
multiple samples.

I am wondering about methods & R pkgs that can be used to analyze changes in
the spectra over time.  For instance, I would like to find specific peaks
that are changing over time, sets of peaks that are changing in a correlated
way over time etc.  I'd like to do this in an efficient and statistically
valid way.  What I am thinking of is somewhat like a time series, somewhat
like image analysis (but only 2D), but it's not quite either of those and I
need to know what it's really called to investigate further.

Any suggestions as to R pkgs and key words/phrases will be appreciated.

TIA, Bryan
*************
Bryan Hanson
Professor of Chemistry & Biochemistry
DePauw University, Greencastle Indiana USA

Hello,

I've found the function isPeak from the Bioconductor package  
"PROCess" very useful for peak finding. My data was similar to yours  
(spectroscopy, i'm a physicist) but not time dependent. It may be a  
starting point to work on one spectrum, retrieve a few relevant  
informations (peak positions, widths, intensities,...), and process  
similarly at regular time intervals.

< www.bioconductor.org/packages/2.0/ bioc/vignettes/PROcess/inst/doc/ 
howtoprocess.pdf  >

hope this helps,

baptiste

On 17 Apr 2008, at 02:26, Bryan Hanson wrote:
> Hi Folks... No code to troubleshoot here.  I need some suggestions  
> about the
> right terminology to use in further searching, and any suggestions  
> about R
> pkgs that might be appropriate.
>
> I am in the planning stages of a project in which IR, NMR and other  
> spectra
> (I'm a chemist) would be collected on various samples, and individual
> samples would be followed over time.  The spectra will be feature
> rich/complex, so one can't see the changes by visual inspection.  The
> spectra are basically 2D matrices: peaks as a function of  
> frequencies.  So
> the data set is in the form of spectra of a single sample over  
> time, for
> multiple samples.
>
> I am wondering about methods & R pkgs that can be used to analyze  
> changes in
> the spectra over time.  For instance, I would like to find specific  
> peaks
> that are changing over time, sets of peaks that are changing in a  
> correlated
> way over time etc.  I'd like to do this in an efficient and  
> statistically
> valid way.  What I am thinking of is somewhat like a time series,  
> somewhat
> like image analysis (but only 2D), but it's not quite either of  
> those and I
> need to know what it's really called to investigate further.
>
> Any suggestions as to R pkgs and key words/phrases will be  
> appreciated.
>
> TIA, Bryan
> *************
> Bryan Hanson
> Professor of Chemistry & Biochemistry
> DePauw University, Greencastle Indiana USA
>
> ______________________________________________
> 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.
_____________________________

Baptiste Augui?

Physics Department
University of Exeter
Stocker Road,
Exeter, Devon,
EX4 4QL, UK

Phone: +44 1392 264187

http://newton.ex.ac.uk/research/emag
http://projects.ex.ac.uk/atto

Dear Bryan,

For work in that general direction, look at the R News that was on 'R in
chemistry' (Volume 6/3, August 2006,
http://www.r-project.org/doc/Rnews/Rnews_2006-3.pdf) and the special vol.
of the Journal of Statistical Software on 'Spectroscopy and Chemometrics
in R' (vol 18, http://www.jstatsoft.org/v18)

For ideas about modeling spectra resolved in time and frequency, the
papers of Sabine van Huffel at K U Leuven may be of interest
(http://www.esat.kuleuven.be/~sistawww/cgi-bin/newsearch.pl?Name=Van+Huffel+S)

If you decide that you want to describe the time domain with a parametric
model, then look at the package TIMP (and perhaps contact me off list).

On Wed, 16 Apr 2008, Bryan Hanson wrote:
> Hi Folks... No code to troubleshoot here.  I need some suggestions about
the
> right terminology to use in further searching, and any suggestions about R
> pkgs that might be appropriate.
>
> I am in the planning stages of a project in which IR, NMR and other spectra
> (I'm a chemist) would be collected on various samples, and individual
> samples would be followed over time.  The spectra will be feature
> rich/complex, so one can't see the changes by visual inspection.  The
> spectra are basically 2D matrices: peaks as a function of frequencies.  So
> the data set is in the form of spectra of a single sample over time, for
> multiple samples.
>
> I am wondering about methods & R pkgs that can be used to analyze
changes in
> the spectra over time.  For instance, I would like to find specific peaks
> that are changing over time, sets of peaks that are changing in a
correlated
> way over time etc.  I'd like to do this in an efficient and
statistically
> valid way.  What I am thinking of is somewhat like a time series, somewhat
> like image analysis (but only 2D), but it's not quite either of those
and I
> need to know what it's really called to investigate further.
>
> Any suggestions as to R pkgs and key words/phrases will be appreciated.
>
> TIA, Bryan
> *************
> Bryan Hanson
> Professor of Chemistry & Biochemistry
> DePauw University, Greencastle Indiana USA
>
> ______________________________________________
> 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.
>