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LAML-Pro: Joint Maximum Likelihood Inference of Cell Genotypes and Cell Lineage Trees.

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Summary
This summary is machine-generated.

This study introduces LAML-Pro, a new computational method for cell lineage tracing. LAML-Pro accurately reconstructs cell family trees by correcting errors in genetic data, improving upon existing lineage tracing techniques.

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Area of Science:

  • Computational Biology
  • Genomics
  • Cell Biology

Background:

  • Dynamic lineage tracing uses genome editing to create heritable mutations for reconstructing cell lineages.
  • Current methods separate genotype identification from lineage tree inference, leading to inaccuracies due to genotyping errors (≈25-50% in imaging).

Purpose of the Study:

  • To develop a computational method that jointly infers cell genotypes and lineage trees, improving accuracy in cell lineage reconstruction.
  • To address the challenge of genotype errors in dynamic lineage tracing data.

Main Methods:

  • Introduced LAML-Pro (Lineage Analysis via Maximum Likelihood with PRobabilistic Observations), a novel algorithm based on the Probabilistic Mixed-type Missing Observation (PMMO) model.
  • The PMMO model accounts for both genome editing and genotype observation processes.
  • Leveraged model sparsity for efficient lineage tree construction from thousands of cells.

Main Results:

  • LAML-Pro corrects genotype errors and infers more accurate cell lineage trees compared to existing methods.
  • Reduced genotype errors by 5-fold in imaging-based lineage tracing data.
  • Produced more spatially coherent lineage trees.

Conclusions:

  • LAML-Pro offers a significant advancement in cell lineage tracing by integrating genotype inference and tree reconstruction.
  • The method improves the accuracy and reliability of lineage trees derived from dynamic lineage tracing experiments.
  • LAML-Pro is available for broader research use.