Azfar Basunia

This paper shows that molecular subtypes and gene signatures in ovarian cancer are influenced by stromal cell content, suggesting that bulk tissue analysis may be unreliable without accounting for cell admixture.

MOGSA integrates multiple omics data to improve gene set analysis by combining features across data types and reducing noise, revealing molecular subtypes in bladder cancer.

The paper introduces MultiAssayExperiment, a Bioconductor package for integrating multi-omics data, demonstrating its use with TCGA datasets to simplify analysis and visualization.