SOPHIE: Generative Neural Networks Separate Common and Specific Transcriptional Responses.

ABSTRACT: Genome-wide transcriptome profiling identifies genes that are prone to differential expression (DE) across contexts, as well as genes with changes specific to the experimental manipulation. Distinguishing genes that are specifically changed in a context of interest from common differentially expressed genes (DEGs) allows more efficient prediction of which genes are specific to a given biological process under scrutiny. Currently, common DEGs or pathways can only be identified through the laborious manual curation of experiments, an inordinately time-consuming endeavor. Here we pioneer an approach, Specific cOntext Pattern Highlighting In Expression data (SOPHIE), for distinguishing between common and specific transcriptional patterns using a generative neural network to create a background

SUBMITTER: Lee AJ 

PROVIDER: S-EPMC10025681 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature