Figure 6.

Training logistic regression on denoised V5 'Divergent' data. Good sequences are shown as black dots, chimeras red and reference sequences magenta. We used the denoised V5 'Divergent' data set, classified either good or chimeric by comparison with the references, and the reference sequences, all good, to train a one dimensional logistic regression on the 'chimera index' I using the R software package [30]. An intercept, α = - 183.25, and coefficient, β = 10.56, were obtained despite the fact that the algorithm did not converge (see text), and the corresponding P50 classification value, 17.35, is shown (blue line).

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