Classifying Consensus Sequences Using Point-Set Representations

Consensus sequences at sites such as exon-intron boundaries or branch points are succinctly displayed with sequence logos. Implicit in this representation is a presumption of independence of nucleic acids at distinct sites; consequently sequence logos fail to elicit features such as correlations between neighboring sites or sub-sequences which may be crucial for hypothesis testing, especially in searching for principles underlying the nature of consensus sequencing. We introduce a graphical approach to display such secondary features. Probability distribution functions (PDFs) on these point-sets are used to highlight correlations at exon-intron boundaries and at branch points. Differences in PDFs at normal exon-exon boundaries and cancer fusion junctions as well as differential correlations at cancer junctions are evaluated and shown to have similar characteristics. The formation of cancer junctions appears to pass through a more restrictive selection than the creation of normal exon-exon junctions.