Censcyt: censored covariates in differential abundance analysis in cytometry.

ABSTRACT:

Background

Innovations in single cell technologies have lead to a flurry of datasets and computational tools to process and interpret them, including analyses of cell composition changes and transition in cell states. The diffcyt workflow for differential discovery in cytometry data consist of several steps, including preprocessing, cell population identification and differential testing for an association with a binary or continuous covariate. However, the commonly measured quantity of survival time in clinical studies often results in a censored covariate where classical differential testing is inapplicable.

Results

To overcome this limitation, multiple methods to directly include censored covariates in differential abundance analysis were examined with the use of simulati

SUBMITTER: Gerber R 

PROVIDER: S-EPMC8108359 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature