Table 8

Chimera classification accuracies for ChimeraSlayer applied to the three denoised V2 'Uneven' data sets.

Dataset

Uneven1

Uneven2

Uneven3


Classification

Good

Chimeric

Good

Chimeric

Good

Chimeric


Good

86 (91.5%)

8 (8.5%)

72 (93.5%)

5 (6.5%)

72 (96.0%)

3 (4.0%)

Bimera

125 (15.3%)

688 (84.3%)

98 (14.6%)

571 (85.4%)

108 (12.8%)

735 (87.2%)

Trimera

20 (24.7%)

61 (75.3%)

13 (18.3%)

58 (81.7%)

15 (18.3%)

67 (81.7%)

Quadramera

0(0.0%)

1 (100.0%)

(0.0%)

1 (50.0%)

--

--

Unclassified

55 (41.7%)

76 (57.6%)

15 (37.5%)

26 (62.5%)

27 (50.9%)

24 (45.3%)


Each row gives a separate category of denoised sequence according to its true classification as 'Good', 'Bimera', 'Trimera', 'Quadramera' and 'Unclassified'. The columns are then split across data sets and give the number flagged as good or chimeric by ChimeraSlayer at 50% bootstrap. Occasionally a sequence remained unclassified probably because there was no good NAST alignment. Consequently rows do not alway sum to 100%. The Broad Institute 'Gold' 16S rRNA sequences were used as references.

Quince et al. BMC Bioinformatics 2011 12:38   doi:10.1186/1471-2105-12-38

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