Extended Data Fig. 5: Comparison of STELLAR to baseline methods on the Barrett’s esophagus (BE) dataset.

(a) Accuracy of STELLAR and scANVI on the BE dataset. Performance was evaluated as a mean score across n=5 runs of each method. Error bars are from standard deviation. scANVI stands for the setting evaluated in the same manner as STELLAR in which we train the model on tonsil dataset and evaluate on BE dataset. scANVI_leaky stands for the approach in which we use fraction of labels from BE dataset as the training data and use the rest of the BE dataset as the test set. Although the setting in which scANVI_leaky is evaluated does not present a fair comparison to STELLAR and other baselines, it indicates that the performance of drop of scANVI is caused by differences between tonsil and BE datasets. (b-d) Performance of STELLAR and alternative baselines on the BE dataset evaluated as (b) mean macro F1-score, (c) macro precision score, and (d) macro recall score across n=5 runs of each method. Error bars are from standard deviation. XGB stands for XGBoost, SVM for Support Vector Machine, RF for Random Forest, ADA for ADABoost, and Seurat for Seurat V4.