Figure 1: Cluster analysis of mouse HCCs. | Nature Genetics

Figure 1: Cluster analysis of mouse HCCs.

From: Application of comparative functional genomics to identify best-fit mouse models to study human cancer

Figure 1

(a) Unsupervised hierarchical cluster analysis of 68 mouse HCC tumors. Genes with an expression ratio that differed by a factor of at least 2 from the reference in at least four tissues were selected for hierarchical analysis (2,313 gene features). A hierarchical clustering algorithm based on Pearson correlation coefficients was applied to group genes on the basis of similarity in the pattern over all tissues and tissues on the basis of similarity in the pattern over all genes. The data are presented in matrix format in which columns represent individual tissue and rows represent each gene. Each cell in the matrix represents the expression level of a gene feature in an individual tissue. The red and green colors in cells reflect high and low expression levels, respectively, as indicated in the scale bar (log2-transformed scale). (b) Dendrogram of cluster analysis. Mouse HCC tissues were separated into three main groups.

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