Sunbear framework. (A) Sunbear takes as input a collection of measurements of single cells at multiple time points in two or more biological conditions (top) or data modalities (bottom). (B) During the training phase, Sunbear learns to decompose the original time-series profiles into four components: cell embedding, time point, batch, and condition. Batch and condition factors are represented by one-hot encodings. The time factor is represented by a sinusoidal encoding. The cell embedding is learned from the original profile and is conditionally independent of the other factors. In the multimodal setting, cell identities are aligned between data modalities. (C) In the prediction phase, Sunbear concatenates the query cell's identity factor while varying other factors to impute the cell's profile across time and conditions. By sharing cell embeddings across modalities, Sunbear allows joint temporal modeling of multimodal profiles.
