Oligonucleotide microarray technology has been developed to a very powerful and favorable biotechnique. However, it is an explicit challenge to judge the potential biological meaning of such extensive amounts of data. There are various-commercially available or free-software applications for pathway analyses on microarray data on the market. The aim of the present study was to test whether pathway analyses on the same data set using different commercially available devices lead to roughly comparable or massively diverging results and, if so, to give potential explanations. Two different commercially available pathway analysis programs (GeneGo and Pathway Studio 6) have been elected. The programs have been compared concerning their different analyses tools, underlying databases, database constructions, and network-building algorithms. The same data set has been uploaded into two different programs. Pathway analysis was performed according to the following three criteria: the five top networks, the five top diseases, and the five top canonical networks that are associated with the uploaded gene list. The different programs differ in extracting their information from the literature, in database construction, and network-building algorithms. The "top networks," as suggested by the programs as to be "most important," substantially differ from each other and share only one same gene. Concerning the most represented diseases in the data set, there are certain overlaps but no uniform results in the different applications. Pathway analyses of microarray data using preformed software devices offer valuable options for investigating on the biological relevance and function of a focus gene set. However, there is no standard in constructing such programs. This leads to substantial differences when investigating on the same data set using different devices. The intention of this work is to sensitize for the potentialities and also pitfalls doing pathway analysis using automated software tools.     «

Oligonucleotide microarray technology has been developed to a very powerful and favorable biotechnique. However, it is an explicit challenge to judge the potential biological meaning of such extensive amounts of data. There are various-commercially available or free-software applications for pathway analyses on microarray data on the market. The aim of the present study was to test whether pathway analyses on the same data set using different commercially available devices lead to roughly compar...     »