seer - 1.1.4-8 main

Bacterial genomes vary extensively in terms of both gene content and
gene sequence - this plasticity hampers the use of traditional SNP-based
methods for identifying all genetic associations with phenotypic
variation. SEER provides a computationally scalable and widely
applicable statistical method for the identification of sequence
elements that are significantly enriched in a phenotype of interest.
SEER is applicable to even tens of thousands of genomes by counting variable-
length k-mers using a distributed string-mining algorithm. Robust
options are provided for association analysis that also correct for the
clonal population structure of bacteria. Using large collections of
genomes of the major human pathogen Streptococcus pneumoniae, SEER
identifies relevant previously characterised resistance determinants for
several antibiotics.