Effective algorithms for fusion gene detection

Authors:
Dan He;Eleazar Eskin
Affiliations:
Dept. of Comp. Sci., Univ. of California Los Angeles, Los Angeles, CA;Dept. of Comp. Sci., Univ. of California Los Angeles, Los Angeles, CA
Venue:
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
Year:
2010

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Abstract

Chromosomal rearrangements which shape the genomes of cancer cells often result in fusion genes. Several recent studies have proposed using oligo microarrays targeting fusion junctions to detect fusion genes present in a sample. These approaches design a microarray targeted to discover known fusion genes by using a probe for each possible fusion junction. The hybridization of a sample to one of these probes suggests the presence of a fusion gene. Application of this approach is impractical to detect de-novo gene fusions due to the tremendous number of possible fusion junctions. In this paper we develop a novel approach related to string barcoding which reduces the number of probes necessary for de-novo gene fusion detection by a factor of 3000. The key idea behind our approach is that we utilize probes which match multiple fusion genes where each fusion gene is represented by a unique combination of probes.