NETBAGs: a network-based clustering approach with gene signatures for cancer subtyping analysis.
OBJECTIVE
To evaluate gene signature and network-based approach for cancer subtyping and classification.


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.


CONCLUSIONS
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.
Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Leihong
L
Wu
Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Zhichao
Z
Liu
Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Joshua
J
Xu
Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Minjun
M
Chen
Office of Scientific Coordination, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Hong
H
Fang
Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Weida
W
Tong
Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA.
Wenming
W
Xiao
D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification* / Q000175:diagnosis / Q000235:genetics* / Q000378:metabolism; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D014644:Genetic Variation; D023281:Genomics; D006801:Humans; D011379:Prognosis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D064726:Triple Negative Breast Neoplasms / Q000145:classification / Q000175:diagnosis / Q000235:genetics
D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human
RNA-seq; cancer subtyping; cluster; expression; gene network; microarray