k-SLAM is a highly e cient algorithm for the characterisa-
tion of metagenomic data. Unlike other ultra-fast metage-
nomic classi ers, full sequence alignment is performed allow-
ing for gene identi cation and variant calling in addition to
accurate taxonomic classi cation. A
k
-mer based method
provides greater taxonomic accuracy than other classi ers
and a three orders of magnitude speed increase over align-
ment based approaches. The use of alignments to nd vari-
ants and genes along with their taxonomic origins enables
novel strains to be characterised. k-SLAM's speed allows a
full taxonomic classi cation and gene identi cation to be
tractable on modern large datasets. A pseudo-assembly
method is used to increase classi cation accuracy by up to
40% for species which have high sequence homology within
their genus.