Efficient Computation of Sequence Mappability

Abstract

AbstractSequence mappability is an important task in genome resequencing. In the (k, m)-mappability problem, for a given sequence T of length n, the goal is to compute a table whose ith entry is the number of indices $$j \ne i$$ j ≠ i such that the length-m substrings of T starting at positions i and j have at most k mismatches. Previous works on this problem focused on heuristics computing a rough approximation of the result or on the case of $$k=1$$ k = 1 . We present several efficient algorithms for the general case of the problem. Our main result is an algorithm that, for $$k=O(1)$$ k = O ( 1 ) , works in $$O(n)$$ O ( n ) space and, with high probability, in $$O(n \cdot \min \{m^k,\log ^k n\})$$ O ( n · min { m k , log k n } ) time. Our algorithm requires a careful adaptation of the k-errata trees of Cole et al. [STOC 2004] to avoid multiple counting of pairs of substrings. Our technique can also be applied to solve the all-pairs Hamming distance problem introduced by Crochemore et al. [WABI 2017]. We further develop $$O(n^2)$$ O ( n 2 ) -time algorithms to compute all (k, m)-mappability tables for a fixed m and all $$k\in \{0,\ldots ,m\}$$ k ∈ { 0 , … , m } or a fixed k and all $$m\in \{k,\ldots ,n\}$$ m ∈ { k , … , n } . Finally, we show that, for $$k,m = \Theta (\log n)$$ k , m = Θ ( log n ) , the (k, m)-mappability problem cannot be solved in strongly subquadratic time unless the Strong Exponential Time Hypothesis fails. This is an improved and extended version of a paper presented at SPIRE 2018.