Finding Top- k Covering Irreducible Contrast Sequence Rules for Disease Diagnosis

Abstract EN

Diagnostic genes are usually used to distinguish different disease phenotypes.

Most existing methods for diagnostic genes finding are based on either the individual or combinatorial discriminative power of gene(s).

However, they both ignore the common expression trends among genes.

In this paper, we devise a novel sequence rule, namely, top- k irreducible covering contrast sequence rules (Top k IRs for short), which helps to build a sample classifier of high accuracy.

Furthermore, we propose an algorithm called MineTop k IRs to efficiently discover Top k IRs.

Extensive experiments conducted on synthetic and real datasets show that MineTop k IRs is significantly faster than the previous methods and is of a higher classification accuracy.

Additionally, many diagnostic genes discovered provide a new insight into disease diagnosis.