Large-Scale Co-Phylogenetic Analysis on the Grid - Cloud, Grid and High Performance Computing: Emerging Applications - page 224

Chapter 14

Large-Scale Co-Phylogenetic
Analysis on the Grid

Heinz Stockinger
Swiss Institute of Bioinformatics, Switzerland

Alexander F. Auch
University of Tübingen, Germany

Markus Göker
University of Tübingen, Germany

Jan Meier-Kolthoff
University of Tübingen, Germany

Alexandros Stamatakis
Ludwig-Maximilians-University Munich, Germany

ABSTRACT

Phylogenetic data analysis represents an extremely compute-intensive area of Bioinformatics and thus
requires high-performance technologies. Another compute- and memory-intensive problem is that of
host-parasite co-phylogenetic analysis: given two phylogenetic trees, one for the hosts (e.g., mammals)
and one for their respective parasites (e.g., lice) the question arises whether host and parasite trees are
more similar to each other than expected by chance alone. CopyCat is an easy-to-use tool that allows
biologists to conduct such co-phylogenetic studies within an elaborate statistical framework based on
the highly optimized sequential and parallel AxParafit program. We have developed enhanced versions
of these tools that efficiently exploit a Grid environment and therefore facilitate large-scale data analy-
ses. Furthermore, we developed a freely accessible client tool that provides co-phylogenetic analysis
capabilities. Since the computational bulk of the problem is embarrassingly parallel, it fits well to a
computational Grid and reduces the response time of large scale analyses.

INTRODUCTION increasingly relies on compute-intensive appli-

cations that require high-performance or large-
scale, distributed high-throughput computing
technology and infrastructure. In the discipline

The generation of novel insights in many scientific
domains such as biology, physics, or chemistry