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Efficient Heuristic for Decomposing a Flow with Minimum Number of Paths

Mingfu Shao, Carl Kingsford
doi: https://doi.org/10.1101/087759
Mingfu Shao
1Computational Biology Department, School of Computer Science, Carnegie Mellon University
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Carl Kingsford
1Computational Biology Department, School of Computer Science, Carnegie Mellon University
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Abstract

Motivated by transcript assembly and multiple genome assembly problems, in this paper, we study the following minimum path flow decomposition problem: given a directed acyclic graph G = (V,E) with source s and sink t and a flow f, compute a set of s-t paths P and assign weight w(p) for p ∈ P such that Embedded Image, and |P| is minimized. We propose an efficient pseudo-polynomialtime heuristic for this problem based on novel insights. Our heuristic gives a framework that consists of several components, providing a roadmap for continuing development of better heuristics. Through experimental studies on both simulated and transcript assembly instances, we show that our algorithm significantly improves the previous state-of-the-art algorithm. Implementation of our algorithm is available at https://github.com/Kingsford-Group/catfish.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted November 16, 2016.
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Efficient Heuristic for Decomposing a Flow with Minimum Number of Paths
Mingfu Shao, Carl Kingsford
bioRxiv 087759; doi: https://doi.org/10.1101/087759
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Efficient Heuristic for Decomposing a Flow with Minimum Number of Paths
Mingfu Shao, Carl Kingsford
bioRxiv 087759; doi: https://doi.org/10.1101/087759

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