Approximate Trace Reconstruction from a Single Trace
Xi Chen, Anindya De, Chin Ho Lee, Rocco A. Servedio and, Sandip Sinha

TL;DR
This paper investigates the approximate reconstruction of a binary string from a single trace affected by deletions, providing algorithms and bounds across different deletion regimes and source models.
Contribution
It introduces algorithms and lower bounds for approximate trace reconstruction from a single trace in various deletion regimes and source models.
Findings
Single trace can significantly improve worst-case reconstruction accuracy.
In average-case, a single trace offers limited improvement over no traces.
Efficient algorithms match lower bounds in several regimes.
Abstract
The well-known trace reconstruction problem is the problem of inferring an unknown source string from independent "traces", i.e. copies of that have been corrupted by a -deletion channel which independently deletes each bit of with probability and concatenates the surviving bits. The current paper considers the extreme data-limited regime in which only a single trace is provided to the reconstruction algorithm. In this setting exact reconstruction is of course impossible, and the question is to what accuracy the source string can be approximately reconstructed. We give a detailed study of this question, providing algorithms and lower bounds for the high, intermediate, and low deletion rate regimes in both the worst-case ( is arbitrary) and average-case ( is drawn uniformly from ) models. In several cases the lower bounds…
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Taxonomy
TopicsMolecular Biology Techniques and Applications · Environmental DNA in Biodiversity Studies · Algorithms and Data Compression
