There were no significant differences when all patients in clusters were compared with all patients with non-clustered isolates.
Two gene clusters were compared using the online software anti-SMASH, Glimmer 3.02 and Subsystem Technology (RAST).
The 40 clusters were compared with Japanese geological and geomorphological data and were then reclassified into 12 groups that had different geomorphological and geological characteristics.
Grouping methods, including urban rural division, in situ vegetation type, land use types in different scales and numerical clustering, were compared for both single soil attributes and "soil set" defined by multiple variables.
The observed counts in our original clustering were compared with those obtained from the reordered list.
The genomic locations of each sequence, within a cluster, were compared in order to identify cases when proteins with similar sequences were derived from different genomic locations.
The predicted protein translations were clustered using CD-HIT at 97% identity using default parameters, and representative sequences from each cluster were compared against the custom MetaCyc associated protein database described above using blastp.
The optimal clustering parameters were applied to the full GenBank dataset, and the resulting clusters were compared with the organism entries of the respective accessions to screen for discrepancies.
To assess potential contributions to host- and tissue-specificity, pathogenesis-associated gene clusters were compared across genomes of eight Xanthomonas strains representing vascular or non-vascular pathogens of rice, brassicas, pepper and tomato, and citrus.
However, the inclusion of the duplicate isoforms of A of D. mojavensis, D. virilis and D. grimshawii increased θ to 0.28 0.38 (P<0.0001), when the A and B clusters were compared.
