BLEND: a fast, memory-efficient and accurate mechanism to find fuzzy seed matches in genome analysis.Generating the hash values of short subsequences, called seeds, enables quickly identifying similarities between genomic sequences by matching seeds with a single lookup of their hash values.  We introduce BLEND, the first efficient and accurate mechanism that can identify both exact-matching and highly similar seeds with a single lookup of their hash values, called fuzzy seed matches.  BLEND  We show the benefits of BLEND when used in read overlapping and read mapping.  For read overlapping, BLEND is faster by 2.4×-83.9× (on average 19.3×), has a lower memory footprint by 0.9×-14.1× (on average 3.8×), and finds higher quality overlaps leading to accurate de novo assemblies than the state-of-the-art tool, minimap2.  For read mapping, BLEND is faster by 0.8×-4.1× (on average 1.7×) than minimap2.  Source code is available at https://github.com/CMU-SAFARI/BLEND.
BLEND
(i) utilizes a technique called SimHash, that can generate the same hash value for similar sets, and  (ii) provides the proper mechanisms for using seeds as sets with the SimHash technique to find fuzzy seed matches efficiently. 
SimHash
For read overlapping, BLEND is faster by 2.4×-83.9× (on average 19.3×), has a lower memory footprint by 0.9×-14.1× (on average 3.8×), and finds higher quality overlaps leading to accurate de novo assemblies than the state-of-the-art tool, minimap2.  For read mapping, BLEND is faster by 0.8×-4.1× (on average 1.7×) than minimap2. 
minimap2