Table 1

Overview of model fits

fitting error

fluidity


G

M

ΔA

ΔB

ΔC

ΔD

φobs

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B. anthracis

13

5523

80

21

78

13

0.08

0.09

0.08

0.09

0.08

E. coli

15

4576

98

58

47

2.6

0.25

0.30

0.25

0.29

0.25

Staph. aureus

19

2651

29

16

21

4.3

0.16

0.19

0.16

0.19

0.16

Strep. pneumonia

26

2095

42

21

30

4.3

0.23

0.32

0.24

0.30

0.23

Strep. pyogenes

14

1786

26

10

25

7.5

0.20

0.24

0.20

0.24

0.21

N. meningitidis

12

2080

53

26

31

2.4

0.28

0.33

0.28

0.32

0.28


Model A assumes a constant population size, and the same gene transfer process for all genes. Model B assumes an exponentially growing population size. Model C assumes that a part of the genome is shared by all genomes (a rigid core); the other part is subjected to the same gene transfer process as in model A. Model D assumes two parts in the genomes, governed by different gene transfer rates. We determined for the four models the parameters that minimize the distance Δ between the empirical and the theoretical gene frequency distribution (see Materials and Methods for the definition of Δ). For each of the 6 bacterial species analyzed, we report the number of analyzed genomes G, the genome size M (average number of genes per genome), the distance Δ for the model fits, the genomic fluidity φobs estimated on the data, and the fluidity φpred for the model fits. Recall that model A has one parameter, models B and C have two parameters, and model D has three parameters.

Haegeman and Weitz BMC Genomics 2012 13:196   doi:10.1186/1471-2164-13-196

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