GeneRaMeN enables integration, comparison, and meta-analysis of multiple ranked gene lists to identify consensus, unique, and correlated genes.

ABSTRACT: High-throughput experiments often produce ranked gene outputs, with forward genetic screening being a notable example. While there are various tools for analyzing individual datasets, those that perform comparative and meta-analytical examination of such ranked gene lists remain scarce. Here, we introduce Gene Rank Meta Analyzer (GeneRaMeN), an R Shiny tool utilizing rank statistics to facilitate the identification of consensus, unique, and correlated genes across multiple hit lists. We focused on two key topics to showcase GeneRaMeN: virus host factors and cancer dependencies. Using GeneRaMeN 'Rank Aggregation', we integrated 24 published and new flavivirus genetic screening datasets, including dengue, Japanese encephalitis, and Zika viruses. This meta-analysis yielded a consensus list of

SUBMITTER: Yousefi M 

PROVIDER: S-EPMC11410378 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature