Estimating clonal heterogeneity and interexperiment variability with the bifurcating autoregressive model for cell...

Area of Science:

• Statistics
• Cell Biology
• Quantitative Biology

Background:

• Cell cycle modeling requires accounting for clonal heterogeneity and interexperimental variability.
• Existing variance-component models can be extended for analyzing cell lineage data.

Purpose of the Study:

• To analyze NIH3T3 cells using an extended variance-components model.
• To investigate correlations within cell lineages grown in different media.
• To estimate experimental effects and obtain robust parameter estimates.

Main Methods:

• Utilized an extension of variance-components models for cell lineage data.
• Applied the model to NIH3T3 cells cultured in two distinct media.
• Incorporated a built-in correlation structure for familial members.

Main Results:

• Confirmed significantly positive sister-sister correlations in both rich and poor media.
• Observed negative mother-daughter correlations in poor medium.
• Found significant positive mother-daughter correlations in rich medium, contrasting with previous findings.

Conclusions:

• The extended variance-components model provides robust estimates and standard errors for statistical inference.
• Cellular correlations are influenced by the growth medium.
• The model effectively captures familial correlations in cell lineage data.