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Figure 4 | BMC Bioinformatics

Figure 4

From: AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

Figure 4

Fuzzy cluster network highlights variation among tumor cell lines. (A) Network diagram illustrating the AutoSOME transcriptome analysis of 42 Diffuse Large B-cell Lymphoma (DLBCL) cell lines (circular nodes), 9 Follicular Lymphoma (FL) cell lines (diamond nodes), and 11 Chronic Lymphocytic Leukemia (CLL) cell lines (rounded-square nodes) [5, 23]. Nodes are colored by cluster membership. Numbers represent individual cell lines according to their order on the original microarrays. Edges represent the pairwise affinity between any two cell lines, defined as the extent to which particular pairs of cell lines are co-clustered by AutoSOME (0 = cells are never co-clustered to 1 = cells are always co-clustered). The diagram was generated in Cytoscape 2.6.0 using the Edge-weighted Spring Embedded layout algorithm [34]. (B) HC of the same cell lines using Uncentered Correlation and Average-Linkage. Cell lines are numbered and colored as in Panel A. The cancer dataset was hierarchically clustered using the software tool, Cluster [1] and the resulting dendrogram was visualized using Java TreeView [57].

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BMC Bioinformatics

ISSN: 1471-2105

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