Suhas’ paper LinkedOmics: analyzing multi-omics data within and across 32 cancer types has been published in...

Suhas’ paper LinkedOmics: analyzing multi-omics data within and across 32 cancer types has been published in Nucleic Acids Research. LinkedOmics is a new and unique resource for disseminating and analyzing The Cancer Genome Atlas (TCGA) data. It is also the first multi-omics database that integrates mass spectrometry (MS)-based global proteomics data generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) on selected TCGA tumor samples. LinkedOmics has three analysis modules. The LinkFinder module allows flexible exploration of associations between a molecular or clinical attribute of interest and all other attributes, providing the opportunity to analyze and visualize associations between billions of attribute pairs for each cancer cohort. The LinkCompare module enables easy comparison of the associations identified by LinkFinder, which is particularly useful in multi-omics and pan-cancer analyses. The LinkInterpreter module transforms identified associations into biological understanding through pathway and network analysis. In this paper, we used five case studies to demonstrate that LinkedOmics provides a unique platform for biologists and clinicians to access, analyze and compare cancer multi-omics data within and across tumor types. Although the current version of LinkedOmics includes only TCGA and CPTAC data, it can be easily extended to support other cohort-based multi-omics studies.