One-Way Matching of Datasets with Low Rank Signals

A major motivation of the present work is the prevalence of data matching in analyzing single-cell multi-omics data . In single-cell biology research, it is routine to compile datasets obtained in different batches but with similar measurement protocols or under similar experiment conditions. When handling such datasets, matching similar cells in different datasets is often a critical step for the correction of technical variations and batch effects [39]. As another common practice, cell biologists routinely integrate datasets with (partially) overlapping biological (e.g., transcriptomic and proteomic) information collected from different experiment conditions, profiling technologies, tissues, or species (e.g., [38, 41, 23]) to better understand and define cell states. To achieve such goals, it is necessary to (identify and) align cells in comparable states across related datasets.