Clonal embeddings allow exploratory analysis of lineage-resolved single-cell data (opens in new tab)

Assays coupling high-throughput lineage tracing with single-cell transcriptomics are transforming studies of development and disease biology, revealing not only major differentiation routes but also continuous fate biases and their putative regulators. Yet, analysis of such data at scale presents challenges due to the sparse nature of clonal data and annotation dependencies. Towards that aim we developed a machine learning approach - clone2vec - which learns informative clone embeddings direc...