I have just come into contact with Qiime2. Recently, when I used the ‘qiime feature-classifier classified-sklearn’ to classify the public data of a study, the annotation results I got were inconsistent with the results in that study, as shown in:
no lactococcus, more streptococcus.(the study noted that lactococcus had a high abundance in most samples, while streptococcus had only 7.51%±11.61%.).
The processing tool used in that study was Qiime1.The reason may be that Q2 classified-sklearn misclassified lactococcus as streptococcus,so I tried to modify the confidence level of classified-sklearn and use the qiime feature-classifier classified-consensus-vsearch, but the effect was not good.
Therefore, I want to know the working principle of ‘qiime feature-classifier classified-sklearn’ or the specific data processing steps (which related to the confidence threshold). Can someone help me?