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NETBAGs: a network-based clustering approach with gene signatures for cancer subtyping analysis
Leihong Wu1, Zhichao Liu1, Joshua Xu1
1Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Aim:
To evaluate gene signature and network-based approach for cancer subtyping and classification.
Materials & Methods:
Here we introduced NETwork Based clustering Approach with Gene signatures (NETBAGs) algorithm, which clustered samples based on gene signatures and identified molecular markers based on their significantly expressed gene network profiles.
Results:
Applying NETBAGs to multiple independent breast cancer datasets, we demonstrated that the clustering results were highly associated with the clinical subtypes and clearly revealed the genomic diversity of breast cancer samples.
Conclusion:
NETBAGs algorithm is able to classify samples by their genomic signatures into clinically significant phenotypes so that potential biomarkers can be identified. The approach may contribute to cancer research and clinical study of complex diseases.
