ArticleNature biotechnology2022
Deep distributed computing to reconstruct extremely large lineage trees.
Article in Nature biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 27 citations in OpenAlex.
- Computational approaches for multimodal lineage tracing.Nature reviews. Genetics · 2026Review
- Charting single-cell lineages with synthetic and natural barcodes.Nature reviews. Genetics · 2026Review
- Trajectory inference for a branching SDE model of cell differentiation via lineage tracing.Journal of mathematical biology · 2026Article
- High-resolution spatial mapping of cell state and lineage dynamics in vivo with PEtracer.Science (New York, N.Y.) · 2025Article
- The Japan-UK Synthetic Biology Conference, Spring 2025: Strengthening Global Links to Engineer Biology.ACS synthetic biology · 2025Article
- Edge-guided inverse design of digital metamaterial-based mode multiplexers for high-capacity multi-dimensional optical interconnect.Nature communications · 2025Article
- The lives of cells, recorded.Nature reviews. Genetics · 2025Review
- Mapping lineage-traced cells across time points with moslin.Genome biology · 2024Article
- Toward DNA-Based Recording of Biological Processes.International journal of molecular sciences · 2024Review
- A statistical method for quantifying progenitor cells reveals incipient cell fate commitments.Nature methods · 2024Article
- Enabling technology and core theory of synthetic biology.Science China. Life sciences · 2023Review
- Maximum likelihood pandemic-scale phylogenetics.Nature genetics · 2023Article
- TiDeTree: a Bayesian phylogenetic framework to estimate single-cell trees and population dynamic parameters from genetic lineage tracing data.Proceedings. Biological sciences · 2022Article
- Cellular barcoding to decipher clonal dynamics in disease.Science (New York, N.Y.) · 2022Review
- Maximum likelihood pandemic-scale phylogenetics.bioRxiv : the preprint server for biology · 2022Article
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Authors and funding
12 authors at 4 institutions in 3 countries.
Funding
Abstract
Phylogeny estimation (the reconstruction of evolutionary trees) has recently been applied to CRISPR-based cell lineage tracing, allowing the developmental history of an individual tissue or organism to be inferred from a large number of mutated sequences in somatic cells. However, current computational methods are not able to construct phylogenetic trees from extremely large numbers of input sequences. Here, we present a deep distributed computing framework to comprehensively trace accurate large lineages (FRACTAL) that substantially enhances the scalability of current lineage estimation software tools. FRACTAL first reconstructs only an upstream lineage of the input sequences and recursively iterates the same produce for its downstream lineages using independent computing nodes. We demonstrate the utility of FRACTAL by reconstructing lineages from >235 million simulated sequences and from >16 million cells from a simulated experiment with a CRISPR system that accumulates mutations during cell proliferation. We also successfully applied FRACTAL to evolutionary tree reconstructions and to an experiment using error-prone PCR (EP-PCR) for large-scale sequence diversification.
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