name acession size (bp) 8 16 32 64 128 256 512 1024 2048 4096 8192 16384 32768 BMC Genomics 2009, 10:640 http://www.biomedcentral.com/1471-2164/10/640 Table 2: gGCSI values of genomes with different sizes calculated with varying numbers of windows chromosomes B.subtilis NC_000964 4,214,630 M.genitalium NC_000908 580,076 plasmids cp32 NC_000952 30,800 0.2093 0.2096 0.2139 0.2137 0.2142 0.2142 0.2143 0.2141 0.2141 0.2141 0.2144 0.2147 0.2145 0.1391 0.1388 0.1361 0.1341 0.1319 0.1290 0.1280 0.1286 0.1282 0.1276 0.1276 0.1260 0.1266 0.4758 0.4552 0.4399 0.4377 0.4349 0.4304 0.4267 0.4299 0.4327 n.a. n.a. n.a. n.a. mean ± SD 0.2135 ± 0.002 0.1309 ± 0.005 0.4403 ± 0.016 0.2887 ± 0.035 0.4225 ± 0.020 genomes used in this work: the 99.5% quantile was 0.035, and the lower 95% mean was 0.005, whereas for the GCSI, the values were 1.205 and 0.180, respectively. These results indicate that the gGCSI is independent of the win- dow size and can be used to compare genomes with dif- ferent sizes, such as bacterial chromosomes and plasmids. Although the gGCSI is independent of the window size, in practice a sufficiently large window size should be chosen such that it is not affected by the local nucleotide compo- sitional bias. In most genomes, a window size of 1000 bp, which corresponds to the average length of coding genes, is sufficient. This leads to the use of 512 to 4096 windows in bacteria for optimal performance, considering the dis- tribution of genome size in the range of 0.5 to 5 Mbp. However, for small plasmids that are only several kilo- bases in size, the use of 1000 bp windows results in only 4 or 8 windows, which is not sufficient for the calculation of SA. Because there is a trade-off between window number and size, the use of 16 to 32 windows of more than 100 bp is desirable for these small genomes. In order to identify the optimal window size, we further calculated gGCSI using number of windows from 8 to 32768 in all bacterial genomes used in this work, and identified the windows size where the change in gGCSI value is minimum compared to adjacent window counts. For example, in Table 1, window number of 4096 has the least difference with the next window counts (0.0001 dif- ference with 2048 windows and 0.0003 difference with 8192 windows). As shown in Supplemental Figure S1 [see Additional File 1], the median of optimal window pT181 J01764 4,439 0.2650 0.2674 0.2590 0.2762 0.3213 0.3432 n.a. n.a. n.a. n.a. n.a. n.a. n.a. pWCFS102 NC_006376 2,365 0.3949 0.4153 0.4501 0.4218 0.4305 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. Page 4 of 10 (page number not for citation purposes)