GoKawiilStudy models sampling limits in mouse forebrain lineage-tracing data
Researchers used simulations built from ground-truth clonal lineages to test how partial sampling and varying capture rates affect the ability to reconstruct clonal architecture in the newborn mouse forebrain. They quantified how many recovered multicellular clones are needed to detect all cell types within a lineage and how accurately observed cell-type proportions match the true underlying clone composition.
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These simulations suggest that conclusions drawn from lineage-tracing experiments can be highly sensitive to sampling depth and capture efficiency, meaning apparent clonal relationships between cell types could partly reflect undersampling rather than true biology. This framework could help researchers set benchmarks for how much data is needed before trusting inferred clonal patterns in developmental studies.
- A simulation framework compared inferred clonal architecture against known ground-truth lineages to test sampling reliability.
- The number of recovered multicellular clones strongly affects whether all cell types in a lineage are detected and how well proportions match reality.
- Findings imply that capture rate and sample size should be carefully considered when interpreting clonal lineage data in developmental neuroscience.
Source: nature.com — Yuan, 2026-09-30
Published there as: “Spatiotemporal clonal architecture of the newborn mouse forebrain”
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