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Classifying Consensus Sequences Using Point-Set Representations
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DOI：10.3390/math14111826.png)
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Abstract
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Consensus sequences at sites such as exon-intron boundaries or branch points are 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 higher-order statistical characteristics within nucleic acid sequences. We introduce a graphical approach to display such features. Probability distribution functions on these point-sets are used to highlight correlations at exon-intron boundaries and at branch points. Point-sets provide a more intuitive view of the differences than quantitative tests like the Kolmogorov-Smirnov test. Differences in density functions at normal exon-exon boundaries and cancer fusion junctions can be used to highlight the distinctions between the two classes of junctions. The fractal structure of point-sets for sites within exons and within introns emerges as the neighborhood used for its construction is enlarged. The two sets can be differentiated using their singularity spectra.
Keywords:
gene-splicing
hereditary diseases
92-10
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