Center for Bioinformatics and Molecular Biostatistics

Translocation, a physical movement of genetic material from one chromosome to another, can aberrantly juxtapose portions of two cellular genes. This type of fusion may disrupt cellular function by producing novel, biologically-active fused genes, or by the activation of normally quiescent growth-associated genes. Either of these mechanisms provides a putative oncogenic stimulus and, indeed, several gene fusions from translocations have been identified in leukemias, lymphomas, and sarcomas. While the biological activity of the oncogenic effects of genes involved in translocations are under intensive study, little is known regarding the formation of translocation fusions themselves. The locations of these fusions are typically independent of the resultant oncogenic protein as long as they take place within certain bounded regions within the genes. Because of this independence a patterned, in particular clustered, distribution of fusion breakpoints within a given region will potentially yield relevant information about the etiology of the fusion. The statistical analysis of translocation breakpoints has, accordingly, focused on the extent to which they cluster. Somewhat questionable methods have been employed in this regard. After highlighting these shortcomings, we introduce a variety of approaches including scan statistics, smoothed bootstrap, and gap statistics, that provide a comprehensive means for appraising clustering. We apply this battery to TEL-AML1 translocations, the most common translocation in childhood acute lymphoblastic leukemia. Results obtained indicate generally weaker evidence for clustering than previously reported, and also highlight differences between the statistical approaches.