Sparse and Skew Hashing of K-Mers

Abstract

Motivation

A dictionary of k-mers is a data structure that stores a set of n distinct k-mers and supports membership queries. This data structure is at the hearth of many important tasks in computational biology. High-throughput sequencing of DNA can produce very large k-mer sets, in the size of billions of strings – in such cases, the memory consumption and query efficiency of the data structure is a concrete challenge.

Results

To tackle this problem, we describe a compressed and associative dictionary for k-mers, that is: a data structure where strings are represented in compact form and each of them is associated to a unique integer identifier in the range [0, n). We show that some statistical properties of k-mer minimizers can be exploited by minimal perfect hashing to substantially improve the space/time trade-off of the dictionary compared to the best-known solutions.

Availability

The C++ implementation of the dictionary is available at https://github.com/jermp/sshash.

Contact

giulio.ermanno.pibiri@ 123456isti.cnr.it