Recently, I’ve been working my way through Ben Langmead’s excellent introduction to “Algorithms for DNA sequencing” on Coursera.com. The class is a fascinating and well-taught intro to concepts about DNA short read alignment and assembly methods.
As part of the course, we have implement or modify python code relating to several simple matching algorithms, including the “naive exact” (NEM) matching method, the “boyer-moore” (BM) method, and a k-mer index approach.
I was curious about speed, so I made a figure showing the computational time that each approach takes. P and T refer to the length of the short read to be aligned and the genome to align to, respectively.
Note that the y-axis is a log scale in units of microseconds. Right away, it is obvious that k-mer index methods are orders of magnitude faster than ‘online’ methods like NEM and BM.
Also of interest is the fact that as the pattern gets shorter, the advantage of BM preprocessing of the pattern gets smaller. You can see that going from 30 to 11 pattern length negates any advantage to BM searching.