Estimation of cell lineage trees by maximum-likelihood phylogenetics

摘要: CRISPR technology has enabled large-scale cell lineage tracing for complex multicellular organisms by mutating synthetic genomic barcodes during organismal development. However, these sophisticated biological tools currently use ad-hoc and outmoded computational methods to reconstruct the tree from mutated barcodes. Because are agnostic mechanism, they unable take full advantage of data's structure. We propose a statistical model mutation process develop procedure estimate topology, branch lengths, parameters iteratively applying penalized maximum likelihood estimation. In contrast existing techniques, our method estimates time along each branch, rather than number events, thus providing detailed account tissue-type differentiation. Via simulations, we demonstrate that is substantially more accurate approaches. Our reconstructed trees also better recapitulate known aspects zebrafish development reproduce similar results across fish replicates.