title: Spot quantification in two dimensional gel electrophoresis image analysis: comparison of different approaches and presentation of a novel compound fitting algorithm.
abstract: BACKGROUND
  Various computer-based methods exist for the detection and quantification of protein spots in two dimensional gel electrophoresis images. Area-based methods are commonly used for spot quantification: an area is assigned to each spot and the sum of the pixel intensities in that area, the so-called volume, is used a measure for spot signal. Other methods use the optical density, i.e. the intensity of the most intense pixel of a spot, or calculate the volume from the parameters of a fitted function.
  
  
  RESULTS
  In this study we compare the performance of different spot quantification methods using synthetic and real data. We propose a ready-to-use algorithm for spot detection and quantification that uses fitting of two dimensional Gaussian function curves for the extraction of data from two dimensional gel electrophoresis (2-DE) images. The algorithm implements fitting using logical compounds and is computationally efficient. The applicability of the compound fitting algorithm was evaluated for various simulated data and compared with other quantification approaches. We provide evidence that even if an incorrect bell-shaped function is used, the fitting method is superior to other approaches, especially when spots overlap. Finally, we validated the method with experimental data of urea-based 2-DE of Aβ peptides andre-analyzed published data sets. Our methods showed higher precision and accuracy than other approaches when applied to exposure time series and standard gels.
  
  
  CONCLUSIONS
  Compound fitting as a quantification method for 2-DE spots shows several advantages over other approaches and could be combined with various spot detection methods.The algorithm was scripted in MATLAB (Mathworks) and is available as a supplemental file.
authors.affiliation: Department of Psychiatry and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nuremberg, Schwabachanlage 6, 091054 Erlangen, Germany. jan.brauner@gmx.de.
authors.forename: Jan M
authors.initials: JM
authors.lastname: Brauner
authors.forename: Teja W
authors.initials: TW
authors.lastname: Groemer
authors.forename: Armin
authors.initials: A
authors.lastname: Stroebel
authors.forename: Simon
authors.initials: S
authors.lastname: Grosse-Holz
authors.forename: Timo
authors.initials: T
authors.lastname: Oberstein
authors.forename: Jens
authors.initials: J
authors.lastname: Wiltfang
authors.forename: Johannes
authors.initials: J
authors.lastname: Kornhuber
authors.forename: Juan Manuel
authors.initials: JM
authors.lastname: Maler
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016011:Normal Distribution; D011506:Proteins / Q000032:analysis*
chemical_list: D011506:Proteins