Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing
Fig 3
A) An initial pruning based on global length, mean and standard deviations of the squiggle ensemble from the Sequin study provides a more homogeneous data set than present in Fig 1. There remain obvious long and short insertion distortions (solid and dashed arrows). B) More intensive pruning based on extreme inconsistencies between the local standard deviation statistics of the squiggle to the ensemble statistics leaves only a few obvious insertion distortions (dashed arrow). However, the majority of the streams are significantly longer than the gold standard, indicating the presence of many individual base insertions (dotted line).