Table 4

The classification of denoised sequences from the nine test data sets

Name

Unique

Good

Bimera

Trimera

Quadramera

Unclassified


Divergent


AmpliconNoise

79

56(70.9%)

21(26.6%)

1(1.3%)

0 (0.0%)

1(1.3%)

SLP 1%

305

210 (68.9%)

23 (7.5%)

1 (0.3%)

0 (0.0%)

71(23.3%)

SLP 2%

60

29 (48.3%)

22 (36.7%)

0 (0.0%)

0 (0.0%)

9(15.0%)

DeNoiser

37

28 (75.7%)

7 (18.9%)

1 (2.7%)

0 (0.0)

1(2.7%)


Artificial


AmpliconNoise

118

94(79.7%)

21(17.8%)

0 (0.0%)

0 (0.0%)

3(2.5%)

SLP 1%

230

168 (73.0%)

21 (9.1%)

0 (0.0%)

0 (0.0%)

41(17.9%)

SLP 2%

62

36 (58.1%)

20 (32.3%)

0 (0.0%)

0 (0.0%)

6(9.7%)

DeNoiser

59

46 (78.0%)

8 (13.6%)

0 (0.0%)

0 (0.0%)

5(8.5%)


Even1


AmpliconNoise

2341

89 (3.8%)

1847 (78.9%)

244 (10.4%)

4 (0.2%)

157(6.7%)

SLP 1%

2205

108 (4.9%)

1631 (74.0%)

253 (11.5%)

4 (0.2%)

209(9.5%)

SLP 2%

894

38 (4.3%)

638 (71.4%)

142 (15.9%)

4 (0.4%)

72(8.1%)

DeNoiser

289

63 (21.8%)

161 (55.7%)

36 (12.5%)

3 (1.0%)

26(9.0%)


Even2


AmpliconNoise

2082

90 (4.3%)

1651 (79.3%)

227 (10.9%)

4 (0.2%)

110(5.3%)

SLP 1%

1958

97 (5.0%)

1448 (74.0%)

235 (12.0%)

4 (0.2%)

174(8.9%)

SLP 2%

789

44 (5.6%)

553 (70.1%)

134 (17.0%)

4 (0.5%)

54(6.8%)

DeNoiser

285

64 (22.5%)

171 (60.0%)

22 (7.7%)

4 (1.4%)

24(8.4%)


Even3


AmpliconNoise

2210

91 (4.1%)

1781 (80.6%)

188 (8.5%)

3 (0.1%)

147(6.7%)

SLP 1%

2164

117 (5.4%)

1635 (75.6%)

194 (9.0%)

3 (0.1%)

215(9.9%)

SLP 2%

874

40 (4.6%)

649 (74.3%)

105 (12.0%)

1 (0.1%)

79(9.0%)

Denoiser

287

64 (22.3%)

170 (59.2%)

24 (8.4%)

0 (0.0%)

29(10.1%)


Uneven1


AmpliconNoise

1124

94 (8.4%)

816 (72.6%)

81 (7.2%)

1 (0.1%)

132(11.7%)

SLP 1%

1040

90 (8.7%)

682 (65.6%)

88 (8.5%)

2 (0.2%)

178(17.1%)

SLP 2%

439

51 (11.6%)

278 (63.3%)

49 (11.2%)

1 (0.2%)

60(13.7%)

Denoiser

212

61 (28.8%)

111 (52.4%)

9 (4.2%)

0 (0.0%)

31(14.6%)


Uneven2


AmpliconNoise

859

77 (9.0%)

669 (77.9%)

71 (8.3%)

2 (0.2%)

40(4.7%)

SLP 1%

814

81 (10.0%)

570 (70.0%)

77 (9.5%)

2 (0.2%)

84(10.3%)

SLP 2%

330

36 (10.9%)

226 (68.5%)

36 (10.9%)

2 (0.6%)

30(9.1%)

Denoiser

154

49 (31.8%)

87 (56.5%)

9 (5.8%)

1 (0.6%)

8(5.2%)


Uneven3


AmpliconNoise

1053

75 (7.1%)

843 (80.1%)

82 (7.8%)

0 (0.0%)

53(5.0%)

SLP 1%

1031

89 (8.6%)

745 (72.3%)

92 (8.9%)

0 (0.0%)

105(10.2%)

SLP 2%

399

45 (11.3%)

259 (64.9%)

49 (12.3%)

0 (0.0%)

46(11.5%)

Denoiser

202

55 (27.2%)

124 (61.4%)

7 (3.5%)

0 (0.0%)

16(7.9%)


Titanium


AmpliconNoise - σs = 0.1

163

76 (46.6%)

77 (47.2%)

1 (0.6%)

0 (0.0%)

9(5.5%)

AmpliconNoise - σs = 0.04

304

91 (29.9%)

174 (57.2%)

2 (0.7%)

0 (0.0%)

37(12.2%)

SLP 1%

765

520 (68.0%)

157 (20.5%)

1 (0.1%)

0 (0.0%)

87(11.4%)

SLP 2%

182

72 (39.6%)

92 (50.5%)

1(0.5%)

0 (0.0%)

17(9.3%)

DeNoiser

151

14 (9.3%)

70 (46.4%)

6(4.0%)

0 (0.0%)

61(40.4%)


The number of unique denoised sequences classified into the five categories, 'Good', 'Bimera', 'Trimera', 'Quadramera' and 'Unclassified', as defined in the text are given together with percentages of the total in parentheses.

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

Open Data