Cellular proliferation biases clonal lineage tracing and trajectory inference.

ABSTRACT:

Motivation

Lineage tracing and trajectory inference from single-cell RNA-sequencing data hold tremendous potential for uncovering the genetic programs driving development and disease. Single cell datasets are thought to provide an unbiased view on the diverse cellular architecture of tissues. Sampling bias, however, can skew single cell datasets away from the cellular composition they are meant to represent.

Results

We demonstrate a novel form of sampling bias, caused by a statistical phenomenon related to repeated sampling from a growing, heterogeneous population. Relative growth rates of cells influence the probability that they will be sampled in clones observed across multiple time points. We support our probabilistic derivations with a simulation study and an analysis o

SUBMITTER: Bonham-Carter B 

PROVIDER: S-EPMC11316616 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature