BaCoN (Balanced Correlation Network) improves prediction of gene buffering

ABSTRACT: Buffering between genes, where one gene can compensate for the loss of another gene, is fundamental for robust cellular functions. While experimentally testing all possible gene pairs is infeasible, gene buffering can be predicted genome-wide under the assumption that a gene's buffering capacity depends on its expression level and its absence primes a severe fitness phenotype of the buffered gene. We developed BaCoN (Balanced Correlation Network), a post-hoc unsupervised correction method that amplifies specific signals in expression-vs-fitness correlation networks. We quantified 147 million potential buffering relationships by associating CRISPR-Cas9-screening fitness effects with transcriptomic data across 1019 Cancer Dependency Map (DepMap) cell lines. BaCoN outperformed state-of-the-ar

SUBMITTER: Thomas Rohde 

PROVIDER: S-SCDT-10_1038-S44320-025-00103-7 | biostudies-other |

REPOSITORIES: biostudies-other