SOLA: dissecting dose-response patterns in multi-omics data using a semi-supervised workflow.

ABSTRACT: An increasing number of ecotoxicological studies have used omics-data to understand the dose-response patterns of environmental stressors. However, very few have investigated complex non-monotonic dose-response patterns with multi-omics data. In the present study, we developed a novel semi-supervised network analysis workflow as an alternative to benchmark dose (BMD) modelling. We utilised a previously published multi-omics dataset generated from Daphnia magna after chronic gamma radiation exposure to obtain novel knowledge on the dose-dependent effects of radiation. Our approach combines 1) unsupervised co-expression network analysis to group genes with similar dose responses into modules; 2) supervised classification of these modules by relevant response patterns; 3) reconstructio

SUBMITTER: Lai W 

PROVIDER: S-EPMC11647027 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature