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. Author manuscript; available in PMC: 2012 Oct 7.
Published in final edited form as: J Proteome Res. 2011 Aug 25;10(10):4734–4743. doi: 10.1021/pr2005378

Figure 3.

Figure 3

Log-odds score matrix and hierarchical clustering. Each row of the matrix represents a query-result, with some of the corresponding log-odds images shown on the left-hand side. Spots are sorted by (x,y) coordinates; thus they are ordered from the top-left spot to the bottom-right spot, scanning vertically from left to right. When looking at the columns of the matrix, we can see high-scoring columns throughout several rows corresponding to specific morphological features, such as the ganglia in rows 2–5. Certain rows of the matrix also show very high similarity. These rows are clustered together and the result clustered query-result image is shown on the right-hand side. Rows (or query-results) that do not show high similarity to other rows end up in singleton clusters.