Fig. 1: Cellar’s workflow.
a–c Preprocessing (optional). Cellar can filter cells based on the number of expressed genes, and genes which are rarely expressed. Next the input is normalized. d, e Dimensionality reduction and visualization. Several methods for dimensionality reduction are implemented as part of Cellar. The reduced data is then visualized by running another (possibly the same) dimensionality reduction method. f–i Clustering. Cellar supports several unsupervised and semi-supervised clustering methods. It also implements supervised label transfer methods. j–l Cell-type assignment. Cellar enables the use of several functional annotation databases for the assignment of cell types.
