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Articles 1 - 4 of 4
Full-Text Articles in Computational Biology
Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh
Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from these procedures. While much work has been done on assessing the global question of number of clusters in a dataset, relatively little research exists on assessing stability of individual clusters. A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will …
Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li
Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li
UW Biostatistics Working Paper Series
Theoretically, many modern statistical procedures are trivial to parallelize. However, practical deployment of a parallelized implementation which is robust and reliably runs on different computational cluster configurations and environments is far from trivial. We present a framework for the R statistical computing language that provides a simple yet powerful programming interface to a computational cluster. This interface allows the development of R functions that distribute independent computations across the nodes of the computational cluster. The resulting framework allows statisticians to obtain significant speed-ups for some computations at little additional development cost. The particular implementation can be deployed in heterogeneous computing …
Literate Statistical Practice, Anthony Rossini, Friedrich Leisch
Literate Statistical Practice, Anthony Rossini, Friedrich Leisch
UW Biostatistics Working Paper Series
Literate Statistical Practice (LSP, Rossini, 2001) describes an approach for creating self-documenting statistical results. It applies literate programming (Knuth, 1992) and related techniques in a natural fashion to the practice of statistics. In particular, documentation, specification, and descriptions of results are written concurrently with writing and evaluation of statistical programs. We discuss how and where LSP can be integrated into practice and illustrate this with an example derived from an actual statistical consulting project. The approach is simplified through the use of a comprehensive, open source toolset incorporating Noweb, Emacs Speaks Statistics (ESS), Sweave (Ramsey, 1994; Rossini, et al, 2002; …
The Problem With The Paleoptera Problem: Sense And Sensitivity, T. Heath Ogden
The Problem With The Paleoptera Problem: Sense And Sensitivity, T. Heath Ogden
T. Heath Ogden
While the monophyly of winged insects (Pterygota) is well supported, phylogenetic relationships among the most basal extant pterygote lineages are problematic. Ephemeroptera (mayflies) and Odonata (dragonflies) represent the two most basal extant lineages of winged insects, and determining their relationship with regard to Neoptera (remaining winged insects) is a critical step toward understanding insect diversification. A recent molecular analysis concluded that Paleoptera (Odonata +Ephemeroptera) is monophyletic. However, we demonstrate that this result is supported only under a narrow range of alignment parameters. We have further tested the monophyly of Paleoptera using additional sequence data from 18SrDNA, 28S rDNA, and Histone …