HAMSTER: visualizing microarray experiments as a set of minimum spanning trees.

Source Code for Biology and Medicine
Raymond WanPaul Horton

Abstract

Visualization tools allow researchers to obtain a global view of the interrelationships between the probes or experiments of a gene expression (e.g. microarray) data set. Some existing methods include hierarchical clustering and k-means. In recent years, others have proposed applying minimum spanning trees (MST) for microarray clustering. Although MST-based clustering is formally equivalent to the dendrograms produced by hierarchical clustering under certain conditions; visually they can be quite different. HAMSTER (Helpful Abstraction using Minimum Spanning Trees for Expression Relations) is an open source system for generating a set of MSTs from the experiments of a microarray data set. While previous works have generated a single MST from a data set for data clustering, we recursively merge experiments and repeat this process to obtain a set of MSTs for data visualization. Depending on the parameters chosen, each tree is analogous to a snapshot of one step of the hierarchical clustering process. We scored and ranked these trees using one of three proposed schemes. HAMSTER is implemented in C++ and makes use of Graphviz for laying out each MST. We report on the running time of HAMSTER and demonstrate using data sets from the ...Continue Reading

References

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Citations

Dec 7, 2013·Hypertension in Pregnancy : Official Journal of the International Society for the Study of Hypertension in Pregnancy·Johannes StubertToralf Reimer

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Datasets Mentioned

BETA
GDS2771
GDS3069

Software Mentioned

Autotools
agnes
Graphviz
GPL
build
layout
Linux
TreeView
Cluster
MPI

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