Integrated statistical analysis of cDNA microarray and NIR spectroscopic data applied to a hemp dataset.
Both cDNA microarray and spectroscopic data provide indirect information about the chemical compounds present in the biological tissue under consideration. In this paper simple univariate and bivariate measures are used to investigate correlations between both types of high dimensional analyses. A large dataset of 42 hemp samples on which 3456 cDNA clones and 351 NIR wavelengths have been measured, was analyzed using graphical representations. For this purpose we propose clustered correlation and clustered discrimination images. Large, tissue-related differences are seen to dominate the cDNA-NIR correlation structure but smaller, more difficult to detect, variety-related differences can be found at specific cDNA clone/NIR wavelength combinations.
Reijmers
T H
TH
Biometris, Wageningen University and Research Centre, Bornsesteeg 47, 6708 PD Wageningen, The Netherlands. t.h.reijmers@rug.nl
Maliepaard
C
C
van den Broeck
H C
HC
Kessler
R W
RW
Toonen
M A J
MA
van der Voet
H
H
D000465:Algorithms; D002188:Cannabis / Q000235:genetics / Q000378:metabolism*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D016002:Discriminant Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D018506:Gene Expression Regulation, Plant / Q000502:physiology; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010940:Plant Proteins / Q000235:genetics / Q000378:metabolism*; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D013223:Statistics as Topic; D018511:Systems Integration
D010940:Plant Proteins