Pixel-based analysis of multiple images for the identification of changes: a novel approach applied to unravel proteome patterns [corrected] of 2-D electrophoresis gel images.
A novel approach for revealing patterns of proteome variation among series of 2-DE gel images is presented. The approach utilises image alignment to ensure that each pixel represents the same information across all gels. Gel images are normalised, and background corrected, followed by unfolding of the images to 1-D pixel vectors and analysing pixel vectors by multivariate data modelling. Information resulting from the data analysis is refolded back to the image domain for visualisation and interpretation. The method is rapid and suitable for automatic routines applied after the gel alignment. The approach is compared with spot volume analysis to illustrate how this approach can solve persistent problems like mismatch of protein spots, erroneous missing values and failure to detect variation in overlapping proteins. The method may also detect variation in the border area of saturated proteins. The approach is given the name pixel-based analysis of multiple images for the identification of changes (PMC). The method can be used for multiple images in general. Effects of pretreatment of the images are discussed.
Faergestad
Ellen Mosleth
EM
Matforsk AS, Norwegian Food Research Institute, As, Norway. ellen.mosleth.fargestad@matforsk.no
Rye
Morten
M
Walczak
Beata
B
Gidskehaug
Lars
L
Wold
Jens Petter
JP
Grove
Harald
H
Jia
Xiaohong
X
Hollung
Kristin
K
Indahl
Ulf G
UG
Westad
Frank
F
van den Berg
Frans
F
Martens
Harald
H
D000465:Algorithms; D000818:Animals; D002417:Cattle; D015180:Electrophoresis, Gel, Two-Dimensional / Q000295:instrumentation / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D015999:Multivariate Analysis; D010363:Pattern Recognition, Automated / Q000379:methods*; D020543:Proteome / Q000032:analysis*
D020543:Proteome