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Curr Opin Biotechnol. 2012 Feb;23(1):64-71. doi: 10.1016/j.copbio.2011.11.028. Epub 2011 Dec 13.

Advancing analytical algorithms and pipelines for billions of microbial sequences.

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Department of Computer Science, University of Colorado at Boulder, Boulder, CO 80309, USA.


The vast number of microbial sequences resulting from sequencing efforts using new technologies require us to re-assess currently available analysis methodologies and tools. Here we describe trends in the development and distribution of software for analyzing microbial sequence data. We then focus on one widely used set of methods, dimensionality reduction techniques, which allow users to summarize and compare these vast datasets. We conclude by emphasizing the utility of formal software engineering methods for the development of computational biology tools, and the need for new algorithms for comparing microbial communities. Such large-scale comparisons will allow us to fulfill the dream of rapid integration and comparison of microbial sequence data sets, in a replicable analytical environment, in order to describe the microbial world we inhabit.

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