Figure 2
An overview of the TripletCell pipeline for cell-type annotation. (A) The query and reference datasets are respectively projected into the cell-signature space using TripletCell-FE. (B) The cell embedding of the reference dataset is used to train a KNN classifier. Then, the types of query cells are predicted according to the predicted probability of the type generated by the KNN classifier for each query cell.

An overview of the TripletCell pipeline for cell-type annotation. (A) The query and reference datasets are respectively projected into the cell-signature space using TripletCell-FE. (B) The cell embedding of the reference dataset is used to train a KNN classifier. Then, the types of query cells are predicted according to the predicted probability of the type generated by the KNN classifier for each query cell.

Close
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close

This PDF is available to Subscribers Only

View Article Abstract & Purchase Options

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Close