A versatile information retrieval framework for evaluating profile strength and similarity.

ABSTRACT: In profiling assays, thousands of biological properties are measured across many samples, yielding biological discoveries by capturing the state of a cell population, often at the single-cell level. However, for profiling datasets, it has been challenging to evaluate the phenotypic activity of a sample and the phenotypic consistency among samples, due to profiles' high dimensionality, heterogeneous nature, and non-linear properties. Existing methods leave researchers uncertain where to draw boundaries between meaningful biological response and technical noise. Here, we developed a statistical framework that uses the well-established mean average precision (mAP) as a single, data-driven metric to bridge this gap. We validated the mAP framework against established metrics through simulations

SUBMITTER: Kalinin AA 

PROVIDER: S-EPMC11014546 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature