In genetic studies, complex diseases are often analyzed searching for marker patterns that play a significant role in the susceptibility to the disease. In this paper we consider a dataset regarding periodontitis, that includes the analysis of nine genetic markers for 148 individuals. We analyze these data by using a novel subgroup discovering algorithm, named APRIORI-B, that is based on APRIORI and bootstrap techniques. This algorithm can use different metrics for rule selection. Experiments conducted by using as rule metrics novelty and confirmation, confirmed some previous results published on periodontitis.
Combining apriori and bootstrap techniques for marker analysis
GAMBERONI, Giacomo;LAMMA, Evelina;RIGUZZI, Fabrizio;STORARI, Sergio;SCAPOLI, Chiara
2007
Abstract
In genetic studies, complex diseases are often analyzed searching for marker patterns that play a significant role in the susceptibility to the disease. In this paper we consider a dataset regarding periodontitis, that includes the analysis of nine genetic markers for 148 individuals. We analyze these data by using a novel subgroup discovering algorithm, named APRIORI-B, that is based on APRIORI and bootstrap techniques. This algorithm can use different metrics for rule selection. Experiments conducted by using as rule metrics novelty and confirmation, confirmed some previous results published on periodontitis.File in questo prodotto:
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