NetWalker: a contextual network analysis tool for functional genomics
1 Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
2 Texas Institute of Biotechnology Education and Research (TIBER), Houston, TX, USA
3 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
4 Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
BMC Genomics 2012, 13:282 doi:10.1186/1471-2164-13-282Published: 25 June 2012
Functional analyses of genomic data within the context of a priori biomolecular networks can give valuable mechanistic insights. However, such analyses are not a trivial task, owing to the complexity of biological networks and lack of computational methods for their effective integration with experimental data.
We developed a software application suite, NetWalker, as a one-stop platform featuring a number of novel holistic (i.e. assesses the whole data distribution without requiring data cutoffs) data integration and analysis methods for network-based comparative interpretations of genome-scale data. The central analysis components, NetWalk and FunWalk, are novel random walk-based network analysis methods that provide unique analysis capabilities to assess the entire data distributions together with network connectivity to prioritize molecular and functional networks, respectively, most highlighted in the supplied data. Extensive inter-operability between the analysis components and with external applications, including R, adds to the flexibility of data analyses. Here, we present a detailed computational analysis of our microarray gene expression data from MCF7 cells treated with lethal and sublethal doses of doxorubicin.