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This latter property has substantial influence on clustering outcome.
The maximum of this peak is well aligned with the best clustering outcome.
Furthermore, the second order derivative also produces a zero value at one of the thresholds associated with the best clustering outcome.
In the case of the SCL dataset both the first and second order derivatives produce multiple local maxima and minima at thresholds associated with the potential best clustering outcome.
Contrasts that compared MB with another region gave the best clustering outcome and therefore only those 3 contrasts CB-MB, OL-MB and TG- MB were used for subsequent pattern analysis.
In the absence of a genomic reference, the influence of chimeric sequences on the clustering outcome becomes a real problem.
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However, the interpretation of the clustering outcomes is often difficult and not intuitive, especially for large datasets with complex topological structures.
Clusters retained a high proportion (mean = 92.29%±7.2 SD) of members across 100 clustering outcomes, each randomly seeded 1000 times.
The quality of the clustering outcomes can be assessed using different clustering validation techniques [ 30].
All clustering outcomes were evaluated by six users, and we report the average quality score for each cluster.
Strong correlation between clustering outcomes and known class labels supports the applicability of this clustering approach to other unlabelled microarray data (Golub et al, 1999).
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