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Nucleic Acids Res. 2018 Jan 4;46(D1):D956-D963. doi: 10.1093/nar/gkx1090.

LinkedOmics: analyzing multi-omics data within and across 32 cancer types.

Author information

1
Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA.
2
Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
3
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA.

Abstract

The LinkedOmics database contains multi-omics data and clinical data for 32 cancer types and a total of 11 158 patients from The Cancer Genome Atlas (TCGA) project. 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. In total, LinkedOmics has more than a billion data points. To allow comprehensive analysis of these data, we developed three analysis modules in the LinkedOmics web application. 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. Using five case studies, we 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. LinkedOmics is freely available at http://www.linkedomics.org.

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