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Analysis of electrophoretic patterns of arbitrarily primed PCR profiling
Author(s) -
Trifunović Dragana,
Radović Milan,
Ristić Zoran,
Gužvić Miodrag,
Dimitrijević Bogomir
Publication year - 2005
Publication title -
electrophoresis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.666
H-Index - 158
eISSN - 1522-2683
pISSN - 0173-0835
DOI - 10.1002/elps.200500381
Subject(s) - electrophoresis , algorithm , computer science , profiling (computer programming) , offset (computer science) , matrix (chemical analysis) , biological system , pattern recognition (psychology) , artificial intelligence , chemistry , chromatography , biology , programming language , operating system
We present a mathematical algorithm for the analysis of electrophoretic patterns resulting from arbitrarily primed PCR profiling. The algorithm is based on the established mathematical procedures applied to the analysis of digital images of gel patterns. The algorithm includes (a) transformation of the image into a matrix form, (b) identification of every electrophoretic lane as a set of matrix columns that are further mathematically processed, (c) averaging of matrix columns corresponding to electrophoretic lanes that define lane representatives, (d) elimination of “smiling” bands, (e) solving the problem of a lane offset, and (f) removal of the background. Representation of individual electrophoretic lanes in the form of functions allows interlane comparisons and further mathematical analysis. Direct comparison of selected lanes was obtained by employing correlation analysis. Gel images were those obtained after arbitrarily primed PCR analysis of DNA that underwent damage induced by gamma radiation from a 60 Co source. The applied method proved to be useful for elimination of subjectivity of visual inspection. It offers the possibility to avoid overlooking important differences in case of suboptimal electrophoretic resolution. In addition, higher precision is achieved in the assessment of quantitative differences due to better insight into experimental artifacts. These simple mathematical methods offer an open‐type algorithm, i.e. , this algorithm enables easy implementation of different parameters that may be useful for other analytical needs.