Table 3

The Not-N algorithm and its implementation by the Minimum SNPs computer program. A. Data for seven hypothetical sequence types (STs) at six single-nucleotide polymorphisms (SNPs). B. Not-N analysis output of the alignment at A. Four sets of two SNPs are identified, all of which reach 100% discrimination. C. Result obtained if positions 3 and 4 are excluded.

A.

Sequence ID

SNP 1

SNP 2

SNP 3

SNP 4

SNP 5

SNP 6

ST 1*

G

G

G

A

T

T

ST 2*

A

G

T

T

T

G

ST 3*

G

G

G

C

T

G

ST 4

A

G

A

G

A

T

ST 5

A

A

A

G

T

T

ST 6

A

G

T

C

A

A

ST 7

A

A

A

G

T

G

Consensus (STs 1, 2 & 3)

Not informative

Not-ACT

Not-AC

Not-G

Not-ACG

Not-AC

>ST4

n/a

+

-

-

-

+

>ST5

n/a

-

-

-

+

+

>ST6

n/a

+

+

+

-

-

>ST7

n/a

-

-

-

+

+

Confidence (%)

Position not used

50

75

75

50

25

*"Group of interest" sequences

B.

SNP set

SNP 1 position and consensus

Cumulative discriminatory power (%)

SNP 2 position and consensus

Cumulative discriminatory power

1

3, NOT AC,

75

5, NOT ACG

100

2

3, NOT AC

75

6, NOT AC

100

3

4, NOT G

75

5, NOT ACG

100

4

4, NOT G

75

6, NOT AC

100

C.

SNP set

SNP 1 position and consensus

Cumulative discriminatory power (%)

SNP 2 position and consensus

Cumulative discriminatory power (%)

1

2, NOT ACT,

50

5, NOT ACG

100

Price et al. BMC Bioinformatics 2007 8:278   doi:10.1186/1471-2105-8-278