Fractal MapReduce decomposition of sequence alignment

In this report we describe a solution to sequence comparison that can be thoroughly decomposed into multiple rounds of map and reduce operations. The route taken makes use of iterated maps, a fractal analysis technique, that has been found to provide a "alignment-free" solution to sequence analysis and comparison. That is, a solution that does not require dynamic programming, relying on a numeric Chaos Game Representation (CGR) data structure. This claim is demonstrated in this report by calculating the length of the longest similar segment by inspecting only the USM coordinates of two analogous units: with no resort to dynamic programming.The procedure described is an attempt at extreme decomposition and parallelization of sequence alignment in anticipation of a volume of genomic sequence data that cannot be met by current algorithmic frameworks. The solution found is delivered with a browser-based application (webApp), highlighting the browser's emergence as an environment for high performance distributed computing.Public distribution of accompanying software library with open source and version control at http://usm.github.com webcite. Also available as a webApp through Google Chrome's WebStore http://chrome.google.com/webstore webcite: search with "usm".Since 2008 the decrease in sequencing costs is far steeper than of those of computing [1]. Projecting from these trends promises to deliver the $1000 genome by 2014, making it inescapable that the costs of analyzing the raw sequence data will exceed those of its generation. In contrast, the algorithms used to process and compare sequences largely rely on the dynamic programming solutions proposed by Smith-Waterman and Needleman-Wunsch in the 70's and 80's [2,3]. This is not to say that the implementation of alignment algorithms has not become more efficient, quite the opposite has taken place. For example, there are several capable algorithmic solutions [4] to align the vast number of short reads that next genera