Abstract:
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In functional data analysis, where both amplitude and phase variability affect individual trajectories, it is often desirable to eliminate (or reduce) the phase variability in order to study a cross-sectional mean function. Techniques like dynamic time warping and curve registration have successfully addressed this question. However, these rely on having a good initial curve against which the others are aligned. We are developing an "iterative curve registration" technique, which yields a more accurate cross-sectional mean function, under appropriate smoothness conditions of the unregistered functions. This development responds to challenges in the analysis of large-scale data from single-DNA molecule measurements arising in nanocoding, a system for whole genome analysis. We will demonstrate the iterative registration to nanocoding data obtained from multiple-myleoma tumor samples and discuss how the findings help to understand genomic variation.
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