CoRegNet: unraveling gene co-regulation networks from public RNA-Seq repositories using a beta-binomial statistical model.

ABSTRACT: Millions of RNA sequencing samples have been deposited into public databases, providing a rich resource for biological research. These datasets encompass tens of thousands of experiments and offer comprehensive insights into human cellular regulation. However, a major challenge is how to integrate these experiments that acquired at different conditions. We propose a new statistical tool based on beta-binomial distributions that can construct robust gene co-regulation network (CoRegNet) across tens of thousands of experiments. Our analysis of over 12 000 experiments involving human tissues and cells shows that CoRegNet significantly outperforms existing gene co-expression-based methods. Although the majority of the genes are linearly co-regulated, we did discover an interesting set of genes

SUBMITTER: Wang J 

PROVIDER: S-EPMC10729864 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature